Deborah Estrin - US grants

An autonomous Administrative Domain (AD) is a set of resources such as host computers, networks, and gateways, that is governed by a single administrative authority. Interconnections across ADs comes about through interconnection of private networks and by dividing an internet that has grown too large to manage. Common approaches to network interconnection create a fully connected internet out of the constituent networks. Network access control mechanisms have been designed for use in inter-AD gateways to control access to end-systems in interconnected networks. When networks are used for transit purposes as well as for access to end-systems, however, these network access control mechanisms are not adequate. In this project critical aspects of the design, specification, and prototype implementation of a first Inter-Domain Policy Routing protocol suite will be developed. Initial experimentation will carried out in the University of Southern California computer science laboratory and will subsequently be tested over actual, cross-country, multi-administrative domain facilities. Thus, by incorporating policy-related contraints on inter-AD communication into route computation, this research provides for essential maintenance and improvement of the research Internet and the research infrastructure it provides to scientists and engineers.***//

The Internet today has evolved from a model based on a hierarchy to one mainly based on a richly interconnected mesh. Due to this change in topology, in addition to the exponential growth the Internet is currently experiencing, there exists a dire need for new protocols that support both the ability to route traffic based on policy (PB) and/or type of service (TOS) and the ability to scale well with respect to the memory, computational, and bandwidth resources necessary to provide for adaptive routing of traffic. This proposal addresses these requirements by combining the best of three current routing protocols. The Border Gateway Protocol (BGP) was first implemented on the NSFNET backbone as a direct response to the need for a new exterior gateway protocol in the late 1980s to handle the increase in size of the Internet and the non-hierarchical peering that was beginning to appear. It is based on a path-vector routing model which uses static routes with accompanying policies per network and is intended for use with IP-based networks. It is currently being adapted and implemented by major routing vendors in their products. The Inter Domain Routing Protocol (IDRP) is BGP with additional capabilities and adapted for use in the OSI world using CLNP. IDRP is very close to passing its last international standards vote and will then be an ISO/CCITT standard. Its emergence will be very helpful in the deployment of U.S. GOSIP compliant networks. The Inter Domain Policy Routing (IDPR) is a model that allows for the pre-selection of the networks a packet will transit based on the policies and TOS supported by the transit networks in addition to the policies or TOS required by the source. This capability is one that many Federal agencies need in order to select network paths based on security, cost factors, guaranteed bandwidth for multi-media and real time experimental control, in addition to providing the agencies with the tools necessary for implementing their acceptable use policies. The IDPR uses dynamic installation of routes to accomplish its goals. The combination of BGP, IDRP, and IDPR would provide the best of all worlds. Economy of resources would be gained using the aggregation features found in BGP/IDRP, thereby reducing routing table sizes, reducing the computational cycles required to calculate routes, and the bandwidth necessary for transmitting the routing information. In addition, the flexibility found in IDPR, required to handle special cases such as those defined by the federal agencies, and both quality of service and type of service support will be provided. This proposal aims at building on the currently deployed infrastructure and protocols in a manner that would not require a mass scale replacement of current technologies and equipment, and therefore provide for a phased evolution to an Internetwork with enhanced capabilities.

This award is for the acquisition of a network testbed for the experimental networking and distributed database research at the University of Southern California. The primary research activities are concentrated in two main areas: Network Control Protocols and Distributed Databases. The main feature that these two diverse research areas share is a need to (1) solve problems involving multiple nodes, (2) complement existing modeling, simulation, emulation, and small scale implementations with multi-node prototypes, (3) isolate the resulting network from the campus production network, and (4) employ a support staff to maintain and operate the network. The study of distributed networks is important because of the wide availability of inexpensive workstations that can be easily linked together. Not so easy is how to utilize these networks effectively. The study of network protocols is critical to this task as is the study of distributed databases. This award supports both areas.

9406007 Estrin The proposal begins with a brief review of the evolution of multicast routing and identification of the scaling issues raised by the introduction of multicast services in a global-scale internet. We then present criteria for evaluating different solutions to the scaling issues. Given these evaluation criteria we outline our proposed solution, called PIM. PIM could significantly improve the scaling properties of multicast routing and is capable of providing better service quality than alternative scalable multicast schemes such as Core Based Trees. We present preliminary simulation results comparing the performance of different distribution trees. However, fully characterizing the performance of multicast routing schemes in very large, heterogeneous, internetworks is not trivial; and ``learning through experience'' in operational networks that are of the size of our target environment (i.e., the global internet), is not feasible . Characterizing multicast protocols is not only challenging because of the scale of the target internet, but also because of the complexity and flexibility built into the protocols themselves. Moreover, a single multicast protocol such as PIM, may be used (or configured) in a variety of ways that directly impact performance. Therefore, to characterize our proposed multicast approach, and to evaluate it relative to alternatives, we propose extensive simulation studies. The proposed research is composed of three parts: 1) an extensive simulation study to characterize the scaling properties and tradeoffs presented by the proposed mechanisms, 2) an investigation of alternative aggregation mechanisms to further extend scalability (using our constructed simulation tools for their evaluation), and, 3) a prototype implementation of the proposed scheme for testing in laboratory and testbed networks. ***

9321043 USC Postel The major project elements for the routing arbiter include advancement of Internet routing algorithms with respect to scaling and stability issues, routing information registration and dissemination for the network service providers serving the Internet, deployment of route servers to aid in the dissemination and real time maintenance of the global Internet routing system, and coordination and sharing of technical information in support of the Internet operations community. A key task for the routing arbiter will be to enhance the use of new switched services offered by the telecommunications carriers, sucy as ATM, in place of dedicated point to point technology that is widely deployed in wide area internets. This proposal is a part of a collaborative effort with Merit. Although both Merit and USC teams will collaborate in all areas, USC will take the lead with the route servers, advanced routing development, provision of a testbed and routing engineering and Merit will take the lead for management and coordination, transition, and operations. While Merit will take the lead in overall coordination, USC will see that apprpriate collaboration is accomplished in research and development.

Multihop wireless capabilities are enabling communication and coordination among autonomous nodes in unplanned environments and configurations. At the same time wireless channels present challenges of dynamic operating conditions, power constraints for autonomously-powered nodes, and complicated interactions between high level behavior and lower level channel characteristics (e.g. increased synchronized communication significantly degrades channel characteristics).
The major goal of the research proposed here is the development, testing, and characterization of algorithms for scalable, application-driven, wireless network services using a heterogeneous collection of communicating mobile nodes. Some of these nodes will be autonomous (robots) in that their movements will not be human-controlled. The others will be portable, thus making them dependent on humans for transportation. While the focus of the work is on the mobile nodes, the project includs immobile computers on the network as well. The project emphasizes that most (though not all) of the mobile nodes will have modest sensing, computational, and communication resources.
The chief scientific motivation behind the work is the design of robust, efficient, and scalable algorithms. The project hypothesizes that distributed algorithms that rely on local interactions have many compelling characteristics, resulting in these properties. There is significant overlap between the problems of coordinating the autonomous mobile nodes that carry some of the sensors and the algorithms that direct the flow of information from sources(s)to sink(s) in the network. Both sets of algorithms need to be carefully designed to improve robustness, efficiency, and scalability.
As motivation the project proposes that the experimental part of the research be conducted on a testbed which simulates some characteristics of an urban post-earthquake scenario in a building. The sensors in the experiments will be distributed geographically (within the building) and linked by a wireless network. Many of the mobile nodes will be largely autonomous, serving as easily-accessible knowledge collectors and repositories, and exercising a wide range of independent options in the dispatch and control of information flow and resources. Other mobile nodes will be carried about the environment by people. The project will study issues of scale (how many sensor nodes does the application software accommodate), fault tolerance (how robust is the system to loss of sensors and/or communication) and efficiency (e.g. time vs. quality of service).
As part of a one-year pilot study funded by NSF, the project has been conducting initial research in the issues underlying a system such as the one above. The project also recently received a substantial equipment grant from the Office of Naval Research to support the experimental portion of this work. The project has identified two key unsolved sub-problems that are relevant to the overall goals: localization and communication coverage. In this proposal the project discusses the broad research challenges in the area of communication and coordination of autonomous mobile nodes. The project then focuses on the two key problems as concrete questions that will be addressed in the research and describes a method involving simulation and experimentation to study them systematically.

This USC-ISI award supports work on a Collaborative Simulation for Education and Research (CONSER) project. The CONSER system involves development of infrastructure that addresses two purposes: (a) support for research activities in the development and evaluation of networking protocols, and (b) teaching in the areas of networking protocols and networking concepts. Based on a collaborative simulation environment, CONSER is intended to aid understanding of protocol behavior in complex operational environments, over a range of traffic conditions, and on a variety of media. The system will involve simulation and visualization support intended to aid researcher and student understanding, thus
providing benefits in both research and teaching settings. Based on ns and nam, the work is expected to be well received by the research community and industry.

EIA-0121141
Requicha, Aristides
University of Southern California

ITR/SI+AP: Active Sensor Networks with Applications in Marine Microorganism Monitoring





The proposed research combines networking, distributed robotics, nanorobotics, and microbiology in an effort to develop and apply technology for the in-situ, real-time monitoring of microbial populations in aquatic environments, such as the ocean or water supply systems. The application context provides feedback from experiments with realistic systems, and this feedback is essential to the progress of the Information Technology (IT) research proposed here. This project addresses two key challenges for IT during this decade: moving from virtual to physical applications, and moving from macro to micro and nano.

The IT focus is on the study of Physically-Coupled Scalable Information Infrastructures (PCSIIs), which effectively "embed the internet". The sensors and actuators in the proposed PCSII must have small physical dimensions, comparable to those of the microorganisms to be monitored. They must be deployed in very large numbers to achieve the unprecedented spatial and temporal resolution necessary to investigate the causal relationships between environmental conditions and microorganisms. Control and coordination of a multitude of such devices of limited and heterogeneous capabilities raise major challenges for networking, distributed coordination and distributed algorithms. Sensing for detection and identification of microorganisms is another challenge, which will be tackled by using nanorobotic Scanning Probe Microscope technology.

The George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Program is a project funded under the NSF Major Research Equipment Program. This cooperative agreement, under the NEES Program, establishes at the University of California, Los Angeles (UCLA), a NEES equipment site for field testing and monitoring of structural performance. UCLA will design, construct, install, commission, and operate a mobile field laboratory for forced-vibration testing and earthquake aftershock monitoring of full-scale structures. This equipment will be operational by September 30, 2004 or earlier and will be managed as a national shared-use NEES equipment site, with teleparticipation capabilities, to provide new earthquake engineering research capabilities through field experimentation and monitoring through 2014. This NEES equipment site will be connected to the NEES collaboratory through the University's Abilene Internet2 connection, with 1 Gb/sec capabilities. Shared-use access and training will be coordinated through the NEES Consortium. This award is an outcome of the peer review of proposals submitted to program solicitation NSF 00-6, "NEES: Earthquake Engineering Research Equipment." The following equipment is provided under this award: (1) four state-of-the-art forced vibration sources that include one omni-directional eccentric mass vibrator with maximum force of 10 kips (continuous operation) and 20 kips (intermittent operation) over a frequency range of 0.1-4.2 Hz, two uni-directional eccentric mass vibrators with maximum force of 100 kips and frequency range of 0-25 Hz, and one linear inertial shaker with maximum force of 5 kips and programmable arbitrary force (or acceleration) time histories over a wide frequency range (0-60 Hz), (2) wireless sensor and data acquisition system (accelerometers, LVDT's, fiber optic gage readout unit, digitizers, routers, and workstations), (3) a cone penetration truck, equipped with a seismic piezocone, 20-ton hydraulic push capacity, side augers, and in situ soil vibration sensors, and (4) networking equipment (data concentrator, satellite uplink station) to allow for real-time data acquisition, processing, and world wide web broadcasting of experimental results. Large arrays of sensors will be placed in buildings and the surrounding foundation soils to obtain high spatial and temporal resolution response data at levels of detail that have not been previously possible. These structures will be excited in the linear and nonlinear range using linear and eccentric shaker systems, or in some cases, using quasi-static loading with actuators. The data obtained will lead to a better understanding of linear and nonlinear response mechanisms (including damage localization, soil-structure-foundation interaction effects, and nonstructural participation), and will aid in the development and verification of improved numerical models indispensable for the full realization of the performance-based earthquake engineering paradigm. The equipment can also be used for forced vibration experiments and aftershock monitoring of structures in the event of a large earthquake. UCLA will integrate this field testing facility into its undergraduate and graduate curricula and research program, post-earthquake reconnaissance involving students under the guidance of a mentor, and provide training opportunities for outside researchers.

Because of the relentless march of the silicon-based electronics technology as predicted by Moore's Law, computation, storage, and communication are now woven into the fabrics of our lives. The emerging technology of flexible electronics, where electronics components such as transistors and wires are built on a thin flexible material, offers a similar opportunity to weave computation, storage, and communication into the fabric of the very clothing that we wear. The implications of seamlessly integrating a large number of communicating computation and storage resources, mated with sensors and actuators, in close proximity to the human body will transform many aspects of biomedical research and practice. For example, one can imagine biomedical applications where biometric and ambient sensors are woven into the garment of a patient or a person in a medically-critical or hazardous environment to trigger or modulate the delivery of a drug.
To realize this vision outside the laboratory, radical innovation is required in the area of system-level information technology. These systems will not scale to widespread use if they are viewed simply as traditional chips or motherboards based on a different, flexible form factor. Rather, a rethinking of the architecture and the design methodology for all layers of these systems is needed. The reasons are two-fold. First, the underlying technology of electronics in flexible materials has characteristics and computation-communication cost trade-offs that are very different from that of silicon and PCB-based electronics. Second, the natural applications of these systems have environmental dynamics, physical coupling, resource constraints, infrastructure support, and robustness requirements that are very different from those faced by traditional systems.
One of the challenges in developing the needed information technology architecture and design methodology for these systems is that one needs to both conduct experimental work and develop a conceptual understanding of the problem domain. This research studies:
Application: Use as a driver application capability, reconfigurable fabric (R-Fabric) based on a combination of (i) the technology of flexible electronics using organic materials, and (ii) computing, communication, and sensing elements implemented as E-Buttons.
Architecture: Develop the general architecture concepts and cost/performance optimization techniques. The issues that we will focus on will include (i) appropriate primitives for composing the architecture, (ii) system interconnect network optimized for the electrical characteristics of the organic electronics, (iii) techniques to cope with the high ration of communication to computation cost, and (iv) architecture level self-configuration and re-configuration for robust operation.
Programming: Develop techniques and primitives for programming a system composed of hundreds of computation, storage, sensing, and actuation elements that are individually resource constrained and are connected by a structured but fault-prone high-cost interconnect network.
Processors: Develop domain-specific processor architecture optimized for these power-constrained, physically coupled applications.

Design Methodology: Develop techniques and hybrid emulation platform for systematic architecture exploration, simulation, optimization, and reconfiguration of these systems.

ABSTRACT
0120778
U of Calif - Los Angeles

The research focus of the Center for Embedded Networked Sensing (CENS) will be the fundamental science and engineering research needed to create scalable, robust, adaptive, sensor/actuator networks. The vision of densely distributed, networked sensing and actuation requires advances in many areas of information technology. Moreover, there is a critical interplay between the technology and the applications and physical context in which it is embedded. By conducting research in the context of specific and high-impact scientific applications, CENS will enable new scientific discovery through high resolution, in situ monitoring and actuation. At the same time, CENS will explore the fundamental principles and technologies needed to apply embedded networked sensing to a wide range of applications.

The Center will focus initially on fundamental technology and on four experimental application drivers: habitat monitoring for bio-complexity studies, spatially-dense seismic sensing and structure response, monitoring and modeling contaminant flows, and detection and identification of marine microorganisms. To support this scope, CENS will combine the expertise of faculty from diverse engineering disciplines with the expertise of biological, environmental and earth scientists. During the lifetime of the Center, additional opportunities for applying the technology to natural and engineered systems will be pursued.

The CENS educational focus will be twofold: new hands-on experimental capabilities for grades 7-12 science curriculum through access to real-world, real-time, sensor-network interrogation, along with materials for teacher-training, and undergraduate research opportunities in cutting-edge technologies (e.g., wireless systems, MEMS, embedded software) and scientific applications (e.g., bio-complexity, seismic and environmental monitoring), with emphasis on under-represented minority students.

CENS will benefit from and contribute to a large number of related activities on its participating campuses, and in the larger research and education community, including: UCLA's California Nanosystems Institute, Institute for Pure and Applied Mathematics, Nanoelectronics Research Facility; USC's Information Sciences Institute, Wrigley Institute for Environmental Studies; UC Reserve systems; Cal State and GLOBE Teacher training programs; INEEL, JPL government laboratories; DARPA, and NSF-related research activities. Many of the constituent technologies will have near- and long-term commercial relevance.

Cheap and tiny processors, radios, sensors, and actuators resulting from progress in microelectronics are leading to a new class of embedded systems, often called Wireless Sensor Networks, that consist of a large number of individual nodes that are physically-coupled, energy-constrained, spatially-distributed (often in an ad hoc fashion), and wirelessly-networked. Such systems provide information about the physical environment at an unprecedented level of detail, and to manipulate the physical environment based on this information, in diverse applications such as security and surveillance, monitoring of wildlife habitats, smart sensor-instrumented environments, and condition-based maintenance of complex systems. This research involves the study of techniques to systematically design, optimize, and manage Wireless Sensor Networks so as to meet applications requirements such as how long the system should last, what space should it cover, and how accurately and how rapidly should it sense the environment.

Wireless Sensor Networks are autonomous, self-configuring, and adaptive distributed systems that perform collaborative computation among energy-constrained nodes to produce the desired information about the physical world. The study is developing design-time resource allocation and run-time resource management methods for such systems while exploiting the inter-play of energy, space, time, and accuracy dimensions that underlies the notion of quality of service in these systems. The focus is on trade-offs that manifest themselves at the level of the entire "sensor field' as opposed to the individual sensor nodes. This study is important both for understanding the fundamental performance limits of wireless sensor networks, as well as for developing practical methods to systematically deploy and operate sensor networks for specific applications.

University of California Los Angeles, Center for Embedded Networked Sensing (CENS), proposes to design a model undergraduate research experience maximizing those features and components of other undergraduate research programs that are most effective in promoting women's longer-term commitment to science and engineering. The design will be based on a survey of many examples of research experiences for undergraduates (REU's) implemented to date, and, based on published research and evaluation results of REU's. The project will exhibit a model of "REU best practices." CENS has chosen the disciplines of engineering, computer science, and the physical sciences to focus efforts because of the low representation of women in these three doctoral fields. Students will be recruited from Mills College and Harvey Mudd College, in partnership with the UCLA Center for Excellence in Engineering and Diversity.

It is widely accepted that REU's are a significant positive experience for students, but the reasons why are not well known. The project will test its model by conducting a program for female students at CENS, and evaluate the results. The expected outcomes for students include: increased hands-on skill set and research experience; improved teamwork, problem-solving, presentation, and content skills as identified by project; improved self-confidence and increased positive attitudes towards respective disciplines; increased number applying for and participating in undergraduate research experiences; increased retention through graduation in respective disciplines; and increased interest and participation in pursuing graduate study.

The project will use a systems approach as a framework for the three main components of programs currently being implemented at institutions across the country:

1. Environment: A research environment that offers women undergraduates experiences in leading research with direct societal implications (e.g., environmental, safety, educational). The connection between the research environment and the societal implications generates a medium through which successful recruitment can occur.

2. Experience: A research experience structured so as to promote successful and productive outcomes for students.

3. Engagement: A vital support structure to ensure academic and social integration for each student. The model program proposed in this project will allow for a more comprehensive understanding regarding which engagement strategies are most effective for women.

Broader impacts: The work will provide faculty members and administrators of undergraduate research programs in engineering, physical sciences and computer science with tools for developing successful undergraduate research programs for their students, with particular effectiveness for female students.

Environmental monitoring has traditionally been limited by sensors that are very constrained in their information-gathering capacities and that acquire data only at a relatively small number of distinct, widely-separated locations. This severly limits the ability to characterize an environment, to then model it, and to subsequently provide accurate information for policy decisions relating to its management. The Networked Infomechanical Systems (NIMS) program introduces a revolutionary new class of mobile distributed sensors that are networked both physically by infrastructure and electronically to enable monitoring and interaction with the full three-dimensional environments in which biological and other systems exist. NIMS sensors measure changes in the environment, autonomously move to locations of particular interest, collaborate to exploit diverse sensing modalities (imagery, acoustic, chemical and meteorological, etc.) in the detection and characterization of events, and learn from the collective experience of the network.

With members from the University of California, Los Angeles, Merced, and Riverside, and the University of Southern California, the NIMS team brings information technology experts in computer science, information theory, robotics, signal processing, and networked embedded computing together with biologists and public health specialists. The initial demonstration applications of NIMS will focus on 1) monitoring of global change indicators in a mountain riparian stream canyon and 2) detection of biological pathogens in coastal waters and urban rivers. However, the techniques being developed apply across an extremely wide range of environments and applications and have the potental to broadly impact science, policy, and national security. The NIMS program also enables an engaging, explorative Grade 6-8 science instruction program with both hands-on science and remote network access to NIMS.

AWARD ABSTRACT

This proposal will develop the National Ecological Observatory Network (NEON) Coordinating Consortium, NEON Project Office, and preliminary Project Execution Plan. Developing a rigorous Project Execution Plan for NEON will be technically, scientifically, and socially challenging. Thus, the NEON Coordinating Consortium and NEON Project Office are integral mechanisms for facilitating refinement of the NEON conceptual design into a formal Project Execution Plan.

The activities of this proposal will provide a community-vetted Project Execution Plan that will clearly define the scope, schedule and budget at a level that will allow construction and operation of NEON. This proposal proposes organizing a National Design Consortium that will (1) develop the science plan, (2) specify the required infrastructure to implement the plan, (3) craft and integrate a novel education program that uses the uniqueness of NEON, (4) develop the details of the network design, and (5) identify the governance and management structure that could be used to construct and operate NEON. The National Design Consortium will be responsible for incorporating the products of the working committees, the web-based and face-to-face contributions from the broader community, into a preliminary Project Execution Plan.

Through the process orchestrated by this proposal, the ecological community will take a vital step in attaining long sought research opportunities and capabilities. In short, this proposal will enhance research aspirations, embolden future planning horizons, and transform the scale and scope of ecological research. In part, the intellectual merit of this proposal resides in the PIs considerable stature, expertise, and appreciation of the technology, science, and education fields. In addition, the process developed in this proposal is trustworthy because it incorporates effective community outreach, a strong advisory board, experienced consultants, and an efficient meeting and committee plan.

This proposal has considerable broader impacts as it will forge new disciplinary alliances; push interdisciplinary scientific, information, and technological frontiers; and create education and training opportunities leading to new career paths. As an example, postdoctoral associates on this proposal will be trained in the design and development of large scientific enterprises, project management, and collaboratory science, technology, and education. The inclusion of individuals of different gender, institutions, scientific disciplines, and underrepresented groups is a fundamental underpinning of this request. Diversity (demographic, institutional and scientific discipline) is incorporated at all levels of this proposal.

The PIs presented a well-articulated vision for science education and the development of an integrated science and education plan as a main deliverable. The plan outlines comprehensive involvement with the education community, and addresses mechanisms to ensure that participants from minority serving institutions (tribal colleges, HBCU's, etc.) have access to NEON sites. Moreover, during the period of the award, compendiums, resource guides, protocols, models, and directories will be developed to open audiences to NEON's integrated research and education opportunities and plans.

This award provides support for 15 undergraduate students to engage in a summer research experience at the University of California, Los Angeles Center for Embedded Networked Sensing (CENS), an NSF-funded Science and Technology Center. The students will have a unique opportunity at the Center to experience a systems approach to undergraduate research training. Students will spend ten weeks on site and will have the opportunity to have access to various activities and events through the academic year through participation in the CENS Alumni Network program. This program will serve to encourage undergraduates to pursue advanced degrees in engineering and thus impact the nations need to increase the number of U.S. citizens and permanent residents engaged in research-related careers. It is also anticipated that this program will have a Broader Impact on the nations need to have broader participation in the research enterprise of citizens and permanent residents from demographic groups traditionally underrepresented in science and engineering.

0414300 Harmon This proposal by UC Merced and the Center for Embedded Networked Sensing (CENS) at UCLA targets the greater San Joaquin River basin (SJRB) for distributed, networked sensing of watershed quality.
Creating a large-scale sensor network that integrates in-situ and remote sensor data with state-of-the-art simulators and adaptive management tools will require interdiscipline collaboration of the highest caliber, and will result in an observational network that reveals previously unobservable phenomena. The sensor network will serve as a model for elucidating trends and differentiating between cyclical and episodic trend drivers, including interannual and spatially distributed variations in water cycle components from changes created by global warming and intermittent events, such as brush fires, droughts, and El Nino episodes.

A workshop will be held to bring together noted scientists to provide recommendations on the synergy among scientific observing systems funded or proposed for funding by NSF, and the ability of that synergy, and those systems, to address grand environmental challenges identified by the National Research Council. The participants will explore the proposed and potential value of NSF nascent and current observing systems to address these challenges. Of critical importance will be the identification of gaps in knowledge that will remain or become more critical as observing systems are deployed, and how this may affect the role of non-observing system science. Of particular importance will be the identification of synergies among and within
observing systems and system requirements for inter-operability. The anticipated intellectual impact will be the identification of emergent frontiers, unrealized research opportunities, and unique infrastructure capacity that arise from the combined environmental research observing systems and networks. The workshop will have broad impacts by defining the potential of observing systems to generate solutions to environmental problems relevant to society. In addition, the resulting reports will contribute to the planning, funding, implementation, coordination, and use of the observing systems through formulating a set of recommendations for the AC-ERE, NSF, and the wider community.

Wireless embedded systems are invigorating CISE research areas from operating systems, distributed embedded computing, architecture, and networking to signal processing, algorithms, and data management, and opening up new broad-impact applications ranging from wide area environmental management to biomedical monitoring. These systems are increasingly focused on a particularly powerful and exciting class of deployment: the heterogeneous or tiered sensor network. A heterogeneous sensor network contains nodes with different capabilities, such as tiny, low-power "motes" and higher-powered, "microservers". Motes are inexpensive and require no infrastructure for long-term deployments, but also extremely constrained in memory, CPU power, and communication. Microservers, in contrast, are more efficient than motes at many computation- and memory-intensive tasks, and more readily interfaced to high-bandwidth peripherals, such as high-rate ADCs and network interfaces; but their higher energy consumption requires power infrastructure, such as solar panels, in long-term deployments. A heterogeneous system containing both motes and microservers can combine the advantages of both devices, using motes to achieve the desired spatial sensing density and microservers to achieve the desired processing power.

Wireless embedded sensor systems present the CISE community with an array of intertwined research challenges: real time sensing of complex and diverse phenomena, embedded computing constrained in bandwidth, energy, memory, and storage, controlled mobility, and the autonomous coordination of vast numbers of network nodes. But implementing and testing sensor network applications is daunting even aside from these challenges: many of the constraints that yield low-power, long-lifetime systems also undermine traditional methods for instrumenting and understanding program behavior. Coordinated community infrastructure can thus act as a tremendous research accelerator, and without shared infrastructure, research in the field will be significantly hampered. This project addresses a pressing need: wireless sensor network research demands a concentrated effort to develop a community resource for heterogeneous sensor systems.

The investigators will develop a community resource based on Emstar, a highly resilient application methodology for microservers and general heterogeneous deployments. Emstar smoothly combines simulation, emulation, and deployment, leading to qualitatively easier debugging and application analysis. An EmTOS component seamlessly integrates motes and microservers; the EmView visualizer provides unprecedented visibility into wireless sensor network communication patterns.

This will build on the investigators Emstar prototype which has proven its value in deployments of heterogeneous networks.
With expanded functionality, integration, hardening, enhanced usability, and longer-term support, its broad array of tools will become accessible to the computer and information science and engineering community. The project will expand Emstar's flexibility, completeness, robustness, documentation, and programmability; extend its functionality by learning from targeted deployments such as seismic arrays, mobile environmental sensing, and medical informatics; and develop a robust, active Emstar community through workshops, tutorials, and mailing lists. The proposed community resource will act as a tremendous accelerator for research into heterogeneous wireless sensor networks, enabling quick and thorough exploration of socially important applications including environmental monitoring, medical and public health systems, and industrial and civic infrastructure development and management. The project will also support and develop undergraduate and graduate level project courses using Emstar, and explicitly involve an undergraduate research program targeting underrepresented minorities.

The Tenet project is developing an alternative architecture for tiered wireless sensor networks that contain both small-form-factor motes and high-powered nodes called masters. The Tenet project's guiding architectural principle asserts that multi-node data fusion functionality and complex application logic should be implemented only on the masters, since the cost and complexity of implementing this in motes outweighs the performance benefits of doing so.

Tenet thus simplifies and standardizes the design and construction of the most difficult-to-handle software on a sensor network. It restricts mote communication to trees rooted at masters. Tree communication is well understood, leads to more predictable communication patterns and improves the manageability of the mote tier. Direct inter-mote communication would destroy much of this predictability and manageability.

The project is designing and prototyping the Tenet stack. This stack embodies the Tenet architectural principle and can be reused by several applications. The development of such a stack for large-scale sensor networks will greatly accelerate the development of a variety of applications ranging from habitat monitoring to structural monitoring. Without a Tenet-like architecture, sensor network deployments will never truly impact the world.

Mobile sensor networks in which some nodes can move (on their own or through the agency of others) combine advanced concepts in perception, communication, and control to create computational systems capable of interacting in meaningful ways with the physical environment. We are motivated by the vision of providing support for communication, monitoring, and surveillance over areas that lack the infrastructure for traditional computation and communication (e.g. protection and monitoring for large geographical areas such as the Alaska pipeline). By deploying a sensor network along such areas (using humans or flying drones) one can maintain a global view of key attributes of the environment. This research focuses on the following three goals within the broad area of synergy between communication and mobility in sensor networks: 1. Deployment - Distributed algorithms for mobility-assisted network deployment with desired topological properties, 2. Mobility-based Topology Control - Distributed algorithms for adaptive self-organization of the network nodes to support desired information flow, and 3. Link-level Communication Modeling - the development and analysis of a suite of localized algorithms that monitor the connectivity properties of the network locally and give global link characterization for the entire network. We expect this research to impact the deployment and maintenance of real-world sensor-actuator networks in the future via a deep understanding of the fundamental problems outlined above. The educational impact of the project will be the creation of a multi-purpose teaching module using the experimental systems developed in the proposed research.

This project is investigating the impact on the network architecture of a new class of applications involving embedded sensing technology as it moves from scientific, engineering, defense, and industrial contexts to the wider personal, social and urban contexts. These applications draw on sensed information about people, objects, and physical spaces to enable new kinds of social exchange and offer new and unexpected views of our communities. They require new algorithms and software mechanisms because unlike scientific applications of distributed sensing, a single system is widely distributed, intermittently connected, and privately administered; and unlike traditional Internet applications the physical inputs are critical to the behavior. The project is developing principles and abstractions that are vital for the future Internet to incorporate such applications, to identify the network fabric architecture options, and to develop the key components and services to realize them. These include network services for context verification and resolution control to enable privacy-aware and verifiable sensing, and application services for naming, dissemination, and aggregation of sensed data. In addition, the project is developing concrete instances of personal, social and urban embedded networked sensing applications to act as design drivers for the broader community of researchers architecting the new Internet core, as well tools to assist in application authoring.
Broader Impact: Ultimately, this research will yield fundamental understanding of software architectures, networking models and data processing techniques that are needed to support a citizenry actively participating in collection, sharing, and interpretation of physical sensor data in the public sphere at multiple scales.

The purpose of this project is to improve the participation and success of African-American, Latino/a, and Female high school students in computing. In particular, the project concentrates on the Los Angeles Unified School District (LAUSD), the second largest and one of the most diverse school districts in the country.

Most current high school computer science courses, curriculum, and pedagogy do not engage students with innovative, interdisciplinary applications in computing. The computer science pipeline is losing traditionally underrepresented students prior to college. By college, at the nations PhD-granting departments of computer science and engineering, just 7% of the computer science degrees are awarded to African-American and Latino/as of both sexes and just 17% to women (Taulbee Survey, 2006).

This project builds on several successful activities from the past that the project team engaged in involving preparation of the targeted students for success in the computer science AP exam. While there is national recognition that the AP exam may suffer from a narrow programming view of CS, it is important to assure that there is equal access to AP CS for all students and that teachers are qualified to teach this college preparatory course. In addition, however, the project team is expanding the scope of their activities to transcend focused preparation for AP. They will participate in the design of more engaging computer science courses that will also qualify as part of a new core college-prepared/career-ready curriculum.

The implementation plan for this project addresses what is involved in the process of expanding rigorous learning opportunities to underrepresented students; what schools must provide to maximize student success in these higher-level learning opportunities and what more is needed; the role of alliances and how they are built and sustained; and the extent to which a school district and individual schools either embrace the innovations or possibly push back against them. This project to broaden participation in computing takes into account the larger context of urban education and educational reform. This project identifies critical factors around which a national model for introducing and sustaining computer science education reform can coalesce.

The mobile phone network is emerging as the largest sensor network on the planet. Mobile phone users, however, are generally unaware of the dual uses of this network, in which their communication devices are also information gathering devices. In participatory urban sensing, everyday mobile devices become a platform for coordinated investigation of the environment and human activity. But transforming phones into data collection instruments raises both technical and ethical challenges. The PI believes that researchers should utilize this network of sensors with the consent and active participation of users. Facilitating responsible, socially trusted, and participatory ethics for data collection and analysis with urban sensing systems remains an open problem, and is the challenge undertaken in this research and education project. In this project, the PI and her team will formalize and qualitatively assess an important test case in participatory ethics: a participatory approach to managing privacy in urban sensing applications. They will create both an immersion curriculum (using a hands-on laboratory approach) and an interdisciplinary seminar-style curriculum to teach participatory ethics for urban sensing to diverse STEM undergraduate and graduate students, and will evaluate these curricula and synthesize classroom findings into best practices which will then be disseminated for education in participatory urban sensing ethics to urban sensing, ubiquitous computing, and broader technology education communities through white papers, guest lectures, video presentations and discussions, and an active website.

Broader Impacts: This work will benefit many areas of mobile and ubiquitous technology research. The multidisciplinarity and rapid pace of system development, the social diversity of users, and the diversity of urban sensing applications are exhilirating yet pose significant challenges to developing a participatory ethics framework. Much as traditional human subjects research guidelines apply to a broad and diverse research scope, the PI believes that similarly powerful principles can be specified for human sensing research. The pedagogical tools developed in the education phase of this project will train a diverse group of STEM students to align technological advances with human practices and ethics. Involving students in discussions and practical implementation of participatory ethics will integrate considerations of values into their research and design practice. Students and researchers trained in participatory urban sensing ethics will design systems that reflect participatory ethics and balance technical and human values. Students will also bring the ethical thinking and value commitments formed during their education to careers in academia, technology industries, and policy arenas. As a critical test case in participatory ethics for urban sensing, formalizing and refining participatory privacy regulation will contribute to fields struggling with meaningful privacy design, including mobile and ubiquitous computing, social networking, and web community systems design.

Early detection of wildfires is critical to mounting a successful response, and a growing need given trends in both urbanization and climate change. As recently as a few months ago, large wildfires started in inaccessible unmonitored areas threatened large urban areas for weeks (witness the Station Fire in the Angels National Forest). Manned observation towers, the method of choice in decades past, has become unsustainable with the boundaries of urban sprawl growing and the budgets of local governments under strain.

This project tackles the problem head-on by developing algorithmic and engineering tools for remote detection of incipient fires using networked remote optical sensors in the visible and infra-red spectra. While previous efforts suggested blanketing the target area with networked temperature and smoke sensors, this approach does not scale well because it requires sensors to be close to the source in order to trigger an alarm. Remote sensors can detect events at a distance and are only limited by the topography of the environment. Thus one strategically placed camera can monitor an entire valley and would ultimately be suitable for co-deployment with other infrastructure such as cell towers. However, processing these video streams is not trivial since events of interest, such as the inception of a fire, can manifest themselves in a large number of ways depending on time of the day, season, weather, distance from the sensor, fuel etc. The challenge is to tease apart these "nuisance effects" and only detect events of interest. The team will focus on the algorithmic challenge of inferring spatio-temporal events in video streams, and on the systems trade-offs between computation, communication and energy resources.

This Broadening Participation in Computing award funds the extension of the Into the Loop Alliance. The Into the Loop Alliance has a primary goal of helping to strengthen the capacity of the Los Angeles Unified School District (LAUSD), the second largest and one of the most diverse school districts in the country, to offer and support high-quality, college preparatory computer science classes, especially in high schools with high numbers of African-American and Latino students. The goal is also to pursue a strategy that creates sustainable changes in the culture and practices at the school and district level; and to develop a model and repository of best practices that can help spread and inform similar efforts in other school districts. The strategic approaches utilized range from the classroom and school level to the policy level.

This Alliance Extension provides the opportunity to expand and sustain the original alliance work locally and nationally. With its initial funding, the Into the Loop Alliance has created an innovative pre-Advanced Placement (AP) computer science curriculum, Exploring Computer Science (ECS); piloted ECS in approximately 16 LA schools with over 900 students enrolled, predominately Latino/a and African American students; designed an ECS Professional Development program; and developed authentic higher education computer science involvement with K-12 schools and educators . In addition to deepening and extending all of the above, the alliance extension includes a commitment to three new strategic initiatives: designing assessment measures for student learning of computational thinking; launching a statewide policy campaign, the California Computing Initiative (CCI); and providing leadership for state and national expansion of these initiatives. All of these goals are aimed at institutionalization and sustainability of the alliance progress to date.

Intellectual Merit: Improving STEM education and guaranteeing equal access to quality education for all students is one of our country's most pressing challenges. Into the Loop sits at the crux of this national challenge. The underlying project research about increasing rigorous learning of computer science opportunities in schools, about assessing student learning of computational thinking, about professional development for computer science teachers, especially in schools with high numbers of students of color, will shed light on similar challenges in other STEM disciplines.

Broader Impact: Into the Loop will provide a model of what has to be done both on the school, district, state, and national levels to improve quality computer science education for all students. The models of professional development that will be designed and implemented in the second largest and one of the most diverse school district in the country will contribute to efforts underway to broaden participation in computing: specifically, to recruit and train a high school teachers who can impart to students the magic and computational thinking of computer science, to re-position Computer Science at the high school level as an academic subject, and to redesign the high school curriculum so that it is rigorous and engaging for a broad segment of our student population. Creating statewide policy change that can reinforce all of these initiatives will be critical for institutionalizing and sustaining these reforms and will be a model for other states as well.

MOBILIZE: Mobilizing for Innovative Computer Science Teaching and Learning is a Targeted Math and Science Partnership between the University of California Los Angeles (UCLA) as the lead and the Los Angeles Unified School District (LAUSD) as the Core Partner school district. The Computer Science Teachers Association (CSTA) and the Association for Computing Machinery, Inc. are Supporting Partners. The Partnership promotes computational thinking, with an overarching goal of fostering inventiveness and innovation among students and teachers through increasing the computer science instructional capacity of high schools, especially in a large urban school district. This project brings together the Center for Embedded Networked Sensing (CENS), an NSF Science and Technology Center (STC) in the Henry Samueli School of Engineering and Applied Sciences, and Center X in the Graduate School of Education & Information Studies at UCLA. MOBILIZE deploys challenging and engaging hands-on computer science projects and curricula using new participatory sensing technologies in high school mathematics and science courses. MOBILIZE prepares a large number of high school teachers to use inquiry teaching methods with the intent that technologies that are ubiquitous with students today, such as mobile phones, peak the interests of students and motivate them in ways that ultimately increases both students' achievement and their identities as "doers" of science, while enhancing the computer science knowledge and pedagogical acumen of teachers.

MOBILIZE:
--creates exciting, challenging, multi-disciplinary, real-life based, cutting-edge, hands-on inquiry projects, tools, and materials for teaching computer science concepts in high school computer science AND in standards-based mathematics and science classes. Piloting occurs locally with dissemination nationally, with the long term goal of increasing student engagement and achievement in computer science, mathematics, and the other sciences. High school teachers work with STEM and education faculty to develop new computer science materials that build on the CENS Participatory Sensing systems, which involve students in observing and analyzing environmental and social processes where they live, work, and play;
--develops an innovative model of professional development for current and future high school teachers around the implementation of these projects, to include multi-disciplinary teams of teachers organized into learning communities with STEM and Education faculty, coaching, and a new pre-service computer science methods course, in order to create a cadre of teachers with expertise in both computer science content and pedagogy; and
--informs state and national policy changes (including changing the academic status of computer science from vocational to academic and establishing a computer science teaching credential) necessary to improve the quality of high school computer science instruction.

The research hypotheses explored focus on: students as computer scientists, whether in mathematics, science or computer science courses; teachers as computer scientists, whether teaching mathematics, science or computer science; and impact on pre-service teachers in terms of their likelihood to utilize inquiry-based instructional strategies during their early years of teaching.

While the Internet has far exceeded expectations, it has also stretched initial assumptions, often creating tussles that challenge its underlying communication model. Users and applications operate in terms of content, making it increasingly limiting and difficult to conform to IP's requirement to communicate by discovering and specifying location. To carry the Internet into the future, a conceptually simple yet transformational architectural shift is required, from today's focus on where ? addresses and hosts ? to what ? the content that users and applications care about.
This project investigates a potential new Internet architecture called Named Data Networking (NDN). NDN capitalizes on strengths ? and addresses weaknesses ? of the Internet's current host-based, point-to-point communication architecture in order to naturally accommodate emerging patterns of communication. By naming data instead of their location, NDN transforms data into a first-class entity. The current Internet secures the data container. NDN secures the contents, a design choice that decouples trust in data from trust in hosts, enabling several radically scalable communication mechanisms such as automatic caching to optimize bandwidth. The project studies the technical challenges that must be addressed to validate NDN as a future Internet architecture: routing scalability, fast forwarding, trust models, network security, content protection and privacy, and fundamental communication theory. The project uses end-to-end testbed deployments, simulation, and theoretical analysis to evaluate the proposed architecture, and is developing specifications and prototype implementations of NDN protocols and applications.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

This project involves the renovation of sections of Boelter Hall, part of UCLA's School of Engineering and Applied Science. The building houses the departments of Chemical and Biomolecular Engineering, Civil and Environmental Engineering, and Computer Science. The unifying theme of the space to be renovated is its use for "sustainability research." Four research "collaboratories" will be created and core mechanical, electrical and plumbing infrastructure will be renovated to support these. The collaboratories are: a Structural Sustainability Collaboratory, a Bio-Sustainability Collaboratory, an Energy and Water Sustainability Collaboratory, and a Sustainable Enviro-Bio-Nano-Technology Collaboratory.

The renovated facility will be used for research in technologies for renewable and alternative energy production and storage, and environmental engineering. Some of the research goals include: the development of the biosynthesis of pharmaceuticals to replace current processes involving organic solvents and to convert renewable resources into pharmaceuticals; a study of the effect of biofuel combustion products on mammalian cells; the discovery, development and optimization of new methods for designing metabolic pathways, new enzymes for biosensors, and new biodegradable polymers; understanding microbial processes at the sub-cellular level; the biotransformation of pollutants, nanoparticles, and pathogens to solve hazardous waste problems and improve public health; and understanding how site-specific physiological and hydrogeochemical conditions and engineered manipulations affect biodegradation activities, microbial community structures, and the fate and transport of pollutants.

In addition to providing infrastructure for research, the renovated facility will be used by undergraduates, graduate students and post-doctoral researchers for research training. The outcomes of some of the research activities may translate into technologies that industry can commercialize and that society can use to provide new energy streams, enhance environmental stewardship, and mitigate the adverse consequences of environmental change.

At a recent EESE Program PI meeting, educators from across science and engineering expressed frustration with the way in which ethics is perceived by STEM undergraduate and graduate students, who seem to view it as a constraint or punitive, something that stands in the way of creativity and innovation. The PI argues that constraining behavior (don't cheat, don't falsify data) is only one of the roles ethics plays in science and engineering; another is as a creative and generative force that contributes to the development of new knowledge. In this project the PI's goal is to address this seeming contradiction, by building and disseminating new understandings on the role of formal and informal ethical inquiry in science and engineering as an essential catalyst of new discoveries from the industrial revolution through modern times. To this end the PI has assembled a team drawn from the domains of film, theater and television, information studies, and science and technology studies, and which also includes working media artists. They will harness their diverse perspectives to jointly develop a set of case studies centered around original documentary film shorts, which will be gathered in an accessible Web portal. These multimedia educational materials, including interviews, location footage, and motion graphics, will be the first to use professional media to tell stories about the creative power of ethical debate, and will impart a new, positive and generative perspective to undergraduate and graduate STEM ethics training.

Broader Impacts: Online and video media are key ways of engaging students. High production values (i.e., careful research, professional screenwriting, and compelling motion graphics) will not only engage the target student audience, but are necessary to convey the complexity of the selected topics. In addition to the curricular materials, the project will contribute methodological experience in the creation of multimedia and video content using ethics-focused approaches, which the PI will document and share in order to encourage educators and STEM researchers to pursue similar studies of ethics as a catalyst for innovation. The PI recognizes that the project format provides an opportunity to highlight the contributions of diverse and traditionally under-represented communities to ethical inquiry in science and engineering in a unique and highly visible way, and he plans to carefully consider questions of representation during selection and production of the case studies.

The University of California Los Angeles, in partnership with the University of Oregon and the Los Angeles Unified School District (LAUSD), propose an extension to the Into the Loop Alliance. The goal is to build and support the capacity of the LAUSD to offer high-quality, college preparatory computer science classes, especially in high schools with high numbers of African-American and Latino students, and to develop a model and repository of best practices that can help spread and inform similar efforts to other school districts nationwide. The project is committed to affecting the depth and scale of change that is necessary to integrate the teaching and learning of computer science into the national education enterprise with the intent of engaging all students. Their focus is on the secondary school level because this is when students are being prepared for pursuing their careers and interests in college. Into the Loop proposal builds upon five previous years of accomplishments, most notably the creation of the Exploring Computer Science (ECS) curriculum and the ECS teacher professional development program. The scope of work for years 6-10 is focused on:

-- Deepening, institutionalizing, and sustaining the reforms in the LAUSD;
-- Expanding the research base and designing authentic assessment measures for student engagement with and learning of computational
thinking practices;
-- Creating and evaluating resources for best and promising practices around ECS curriculum and pedagogy, teachers professional
development and learning community, and ECS assessments; and
-- Studying the scalability and replicability of ECS curriculum and PD.

In years 6-10, the partnership will serve as a national resource for others pursuing CS education/broadening participation in computing initiatives.

The vision of patient-centric, personalized, precision medicine and wellness will be fully realized only when an individual?s self-care and clinical decision making are informed by a rich, predictive model of that individual?s health status. The evolution and dissemination of mobile technology has created unprecedented opportunities for highly detailed and personalized data collection in a far more granular, unobtrusive, and even affordable way; these data include activity levels, location patterns, sleep, consumption, and communication and social interaction. However, turning this potential into practice requires that we develop the algorithms and methodologies to transform these raw data into actionable information. The research will develop novel and generalizable techniques to derive robust measures relevant to individual health and clinical decision making. The team will develop and evaluate tools that convert raw human-activity data into clinically actionable behavioral biomarkers. This demands creative uses of the underlying technical capabilities (i.e., passive data capture, data analysis and machine learning, data visualization, user experience), as well as rigorous understanding of the underlying health condition and management (i.e. functional health measures, achievable and optimal health outcomes, patient challenges in adherence, risks and benefits associated with medication and other aspects of treatment, and clinical decision making). The approach has broad applicability across disease management (e.g., auto-immune, gastrointestinal, depression, cognitive decline, and neurologic disorders), but also calls for tailoring to specific conditions and individuals. Therefore, we will conduct this initial work in a specific context, that of chronic pain management for three prominent conditions: rheumatoid arthritis, osteoarthritis, and lower back pain. The behavioral biomarkers associated with our initial target domain, pain management, center around: (i) decline in activity levels; (ii) increase in stress; (iii) decrease in sleep quality; (iv) drop in function, e.g., reduction in travel distance or inability to go to work. The effectiveness of passive sensing capabilities of the mobile phone to track sleep, changes in activity level, stress, social isolation, geographic location and several other indicators that are likely antecedents or symptoms of pain interference has been demonstrated previously.

While behavioral biomarkers rely extensively on passively captured data streams (such as activity, location, communication, application usage and audio), there remain important cases in which self-report data is required to augment or clarify passively collected data. However, the standardized patient survey instruments that assess relevant symptoms and behavior are not suitable for use on a daily basis because of length, question design, or both. Further, traditional forms of self report are often intrusive, burdensome, and suffer high rates of attrition. A new approach, contextual recall, aims to mitigate the issues related to self-report through three key mechanisms: optimizing the delivery of prompts, providing the user with key contextual cues to improve recall, and employing visual input techniques as an alternative to long-form measures that do not scale well to frequent mobile self-reports. The approach to personalizing disease management is intentionally scalable in terms of affordability and accessibility. Passive data collection requires no user attention, and contextual recall is a form of self-report designed for busy individuals with a range of demands and constraints on their time, as well as potential literacy and numeracy constraints. The clinician-facing components of this approach are also designed to work in resource-constrained clinical settings where clinicians are under particular time pressure. The team will recruit patients and clinicians from typically underserved communities to engage in the participatory design process. The overall contributions of this work will include development and evaluation of: (1) software techniques to combine and transform passively monitored and self-reported data streams into clinically meaningful, actionable, and personalized indicators, which we call behavioral biomarkers; (2) contextual recall that allows the collection of highly granular and contextually specific self-report data to enhance passively captured data with information from the patient perspective, while balancing the tension faced in balancing recall bias and usability; and (3) a methodology that systematizes the collaboration with clinical domain experts to develop and integrate behavioral biomarkers into clinical decision making for specific diseases. We will create and evaluate a modular and extensible suite of analytics and user interaction techniques designed to facilitate iterative implementation and evaluation. These modules will themselves be a contribution, but equally important will be the evaluation of the overall approach of behavioral biomarkers as a driver of precision medicine.

PI: Erickson, David
Proposal: 1343058
Title: INSPIRE Track 2: Public Health, Nanotechnology, and Mobility (PHeNoM)

This INSPIRE award brings together research areas traditionally supported by: the Biophotonics and Nanobiosensing Programs in the Chemical, Bioengineering, Environmental, and Transport Systems Division (CBET) of the Engineering Directorate (ENG); the Communications, Circuits and Sensing Systems Program in the Electrical, Communications and Cyber Systems Division (ECCS) of the ENG Directorate; the Science, Technology and Society Program in the Social and Economical Sciences Division of the Social, Behavioral and Economic Sciences Directorate (SBE); and the Smart Health and Wellbeing Program in the Information and Intelligent Systems Division (IIS) of the Computer & Information Science Engineering Directorate (CISE).

Significance
The science and technology enabled by the Public Health, Nanotechnology and Mobility (PHeNoM) project may ultimately lead to widespread access to health information obtainable from lab-on-chip technology. This research project could alter the domestic healthcare landscape by enabling earlier-stage detection of disease, reducing the cost of public healthcare delivery, and allowing individuals to take better control of their own well-being. Such advances require the integration of the social and technical contexts of health care device deployment. This integration is accomplished by gathering feedback on early versions of the technology and modifying future designs based on that initial feedback. Iterations between feedback and design are facilitated by research efforts that interpret the feedback and guide the development process. The ultimate transfer of the technology to the marketplace is enabled by a new education effort that involves a unique combination of coursework, business plan development, pre-seed grant workshops, and collaborations with existing start-ups in the mobile health space.

Technical Description
Advancements in nanotechnology and microfluidics have enabled the development of lab-on-chip devices that can detect and quantify protein, genetic, and other biochemical markers of diseases with precision. Currently-available personalized diagnostic devices are limited to conditions that require either frequent monitoring (e.g. glucose for diabetics) or "binary" results (e.g. pregnancy). The goals of the PHeNoM program are to demonstrate that deployment of lab-on-chip technology can be fundamentally altered by taking advantage of ubiquitous smartphone technology and show that the fusion of physical sensing and molecular assays on mobile platforms enable healthcare diagnostics that are more informative than either technology alone.

To meet these aims, the investigators are focusing their efforts on developing and deploying three systems that may have an immediate impact on advancing personalized healthcare in the United States: a Stress-Phone for long term stress management, a Nutri-Phone for bloodwork-enabled nutritional awareness, and a Hema-Phone for monitoring viral loading in HIV+ patients. Beyond the immediate merits of these technologies, the broader merit of this project is the demonstration of new "bioinfo-mobile" diagnostics that intertwine the advantages of mobility, computation, physical sensing, and biomolecular assays.

Small Data Research Infrastructure: Workshop Proposal

This project is for a workshop series to assess the research needs and opportunities in small data research. Small data refers to the collection of digital traces that individuals generate implicitly and explicitly during their everyday lives. As the use of big data analytics has exploded, a growing community of computer and information science researchers has started to focus on the capture, processing, governance, and use of these small data streams. The research challenges raised by small data cut across the computer science community and include: 1) Personal data mining and modeling: parsing and fusion of diverse and noisy data streams to create informative, descriptive, and predictive models of individuals and their behaviors; 2) Data Privacy and sharing: constructs, architecture, and policies, for protecting and sharing raw and derived personal data streams; and 3) User-centered applications and human-computer interaction: design methods and tools to create meaningful and engaging experiences for individuals. In order to make progress across these three research thrusts, at a scale and pace that matches the potential for impact to individuals and society, this project aims to run a series of workshops to convene the technical community. The output of the workshop series will include the articulation of a small data research agenda, and a plan for a shared community research infrastructure to support real world experiments with real participants and their small data streams.

This project brings together expertise from across computer and information sciences and engineering for a series of workshops to develop a research agenda and community infrastructure for small data research. To develop and evaluate realistic systems using "small data" requires user involvement and an end-to-end system test bed involving data streams controlled by various companies and further, that such a test bed should be a shared community infrastructure, since no single research group can afford to build it. The infrastructure development at the center of the proposed workshops has the potential to change how investigators do research, which broadly impacts the research community.

One of the crucial ideas behind Privacy by Design (PbD) is that privacy should be taken into consideration in the process of design, not merely after-the-fact, as so often happens. Yet, this ideal has failed to gain widespread practical traction, challenged, in part, by the lack of developed methodologies and also because of privacy's conceptual complexity, which hampers its operationalization. This project addresses both challenges simultaneously, seeking (i) to demonstrate how a robust operationalization of privacy can lead to meaningful PbD and (ii) to contribute methodological insight by engaging with ongoing research and development in the area of small data applications, namely, systems that advance wellness and personal productivity by utilizing digital traces from individuals' day-to-day activities, such as e-mail, grocery shopping, TV watching, transportation, mobile devices, and so forth. Adopting the definition of privacy as contextual integrity, the project will focus on selected small-data applications currently "on the drawing board" in PI Deborah Estrin's Small Data lab. With these design cases, the project rises to one of the PbD challenges, namely consideration of privacy early on in development and, as a research enterprise, its primary aim is to uncover more and less productive methodological approaches for doing so, resulting in system characteristics well correlated with privacy requirements.

At the same time, the project will provide invaluable insight into how to operationalize contextual integrity, which conceives of privacy as appropriate flow of personal information, modeling appropriate flow as conformance with context-specific informational norms, which, prescribe (and prohibit) information flows according to three parameters: actors (subject, sender, recipient), information types, and transmission principles (functional constraints on flow). Adopting contextual integrity as an operational definition means that researchers will assess privacy properties by carefully mapping data flows, and evaluating these flows in terms of the context of application and use. The project also extends past work on formal representations of informational norms by demonstrating how they may be integrated into design practices. In addition to its substantive contributions this project embodies an innovative collaborative model -- a novel pairing of a computer scientist, Deborah Estrin (Cornell), with a philosopher, Helen Nissenbaum (NYU), in an equal partnership to forge technologies that embody meaningful privacy.

Individuals today generate an immense amount of data as a byproduct of their daily activities through use of mobile phones, wearable devices, and online services. These small bits of data are called microscale data. The availability of microscale data creates new opportunities for solving a variety of complex planning problems at the institutional level, but it also raises concerns about security and privacy for the individual whose data is collected. The ability to realize the beneficial uses of microscale data is threatened by these concerns over privacy. This project develops and evaluates an architecture that allows individuals to monitor and manage sharing of their microscale data in order to maximize individual and institutional utility.

This project develops a software framework to support the implementation of data-driven planning applications where individuals have fine-grained control over use of their data. Work on the project focuses on: (i) creating a campus testbed capable of acquiring microscale data streams from sources such as wireless access points, card readers, room sensors, and point-of-sale systems; (ii) building a data management platform that offers flexible controls for imposing use-based restrictions on queries and transformations of microscale data; (iii) developing applications that use microscale data to solve practical planning problems related to transportation, space, and food in a campus setting. Having an open-source platform that addresses fundamental security and privacy challenges for microscale data has the potential for large impact on real applications and industry. Under the auspices of this funding, the investigators will also develop masters-level projects on microscale data-driven planning, providing the next generation of engineers with training in an emerging interdisciplinary area.

This work strives to create a future in which hyper-personalized content, digital services, and personal information management tools let individuals benefit from the data they generate more directly, selectively, and transparently. Individuals will then be empowered to gain insights into their own behavior, personalize their own experiences, and ultimately more effectively utilize the services to achieve their goals. Moreover, the systems that engage end-users with the data they generate can promote local processing and selective sharing of personal information. Given the pervasiveness of online tools in a person's work, personal, and social life, the actions they take are increasingly shaped by recommendation systems. Today's approaches to personalization and recommendation are provider centric. Society as a whole will benefit from broader exploration of personalization and recommendation from the consumers' perspective. Also along these lines, there is increasing concern about the shifts in expectations for individual control over data sharing. This project's user-centered and personal-sharing-policy-aware design is a potential solution to address this tension between providers and users, allowing people to more directly benefit from their data.

The research objective is to develop novel user modeling techniques, policy-aware systems, and rich user interactions that allow individuals to harness their own diverse digital traces ("small data"), enable novel applications, and receive more personally-relevant recommendations while limiting privacy exposure. This research will contribute the novel user modeling and interaction techniques needed to put the individual at the center of their personalization, in particular: (1) Immersive user modeling techniques that analyze diverse types of user data, including social media streams, private text communications, web browsing, geo-location traces, and personal images, to incorporate users' diverse and idiosyncratic interests. (2) Novel recommendation models and policy-aware software architecture that consists of open source building blocks designed to facilitate generalization of this approach to ingest diverse personal data traces and feed diverse application targets. (3) Methods to understand and address key human-centered challenges in immersive recommender systems through participatory design of the user experience, as well as qualitative and quantitative evaluation of deployed systems and applications.

Home health aides are an important group of frontline health workers and one of the fastest-growing sectors of the U.S. workforce. Largely employed by public agencies (Medicare and Medicaid), home health aides currently care for 48 million Americans. However, these workers face numerous challenges as they provide in-home care for people with serious illnesses such as heart failure, diabetes, dementia, and others. Despite spending more time with patients than any other care provider, home health aides, who are mostly women and minorities, are overworked, poorly compensated, and experience high levels of stress and burnout. Their existing tools and technology ecosystems are outdated, hard to use, and largely revolve around monitoring home health aides' labor rather than supporting their work. home health aides find changes in patients' health conditions frightening and struggle to reach supervising clinicians by phone when they need clinical help. Finally, home health aides largely operate day-to-day in isolation, without the ability to be mentored by peers and supervisors, or to grow their skills and advance.

This project addresses some of the challenges home health aides face via five complementary research activities that aim to improve the work satisfaction of home health aides, the care received by patients, and the integration of the care team. The first two activities provide new mechanisms for home health aides to obtain care-related information and support by assisting with routine care tasks via multi-modal conversational agents that provide voice-, video-, and text-based guides for completing tasks safely, and providing decision support for clinical questions via a conversational agent that delivers medically-verified information. In parallel, there is a critical need for new mechanisms that enable reliable and timely communication and coordination between home health aides and the rest of the care team. The next two activities engage with this challenge by developing an asynchronous communication tool that connects home health aides directly with clinical staff; and enables data-driven cooperative work and care coordination via new multi-stakeholder and multiple timescale data collection and reporting mechanisms. Taken together, these innovations provide rich opportunities for home health aides to learn and practice new skills, demonstrate their expertise, receive recognition, and meaningfully shape patient care. The final activity creates opportunities for learning and career advancement via new training programs that sustain a sense of progress and advancement while improving patient outcomes. This project, taken as a whole, will improve the skills, well being, and careers of home health aides of the future.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.