Elizabeth M. Belding - US grants

This project, conducting research in the areas of sensor networks and distributed and cluster computing, experiments with precision-based query processing over sensor networks and wireless networking. Since sensor devices are powered by ordinary batteries, power constitutes a limiting resource in sensor networks. To address this limitation, power-aware query techniques are proposed for aggregation queries. Instead of providing users with exact answers, precision is introduced, giving full control to the users of the tradeoff between precision and energy usage. Another project studies the design and implementation of a self-organizing storage cluster built upon commodity components, investigating performance and availability of large-scale storage clusters as well as load balancing and data replication support, suitable for data intensive applications. Off loading techniques that effectively partition computation across devices are also under study, since these techniques can significantly extend the life of hand-held devices. Still another project investigates techniques to effectively partition computation across devices conserving the "virtual battery life" of the system. improving the efficacy of future partitioning decisions. Considering feedback from the system, the techniques should be able to "adapt" to changing conditions in the system. The off-loading techniques for heterogeneous systems include three categories of devices: sensors, mobile devices, and power workstations. The research seeks lightweight service discovery solutions that can determine the resources provided by nodes in the heterogeneous network. The infrastructure enables research in the following areas:
Sensor Information Processing,
Sensor Data Collection,
Cluster-Based Data Storage,
Power Management of Sensor-Based System Components, and
Wireless and Service and Resource Discovery in Sensor Networks.
The proposed infrastructure will be used to experiment with precision-based query processing over sensor networks.

Broader Impact: The lab infrastrucure provides means to integrate a variety of sensing devices with different characteristics. Academic, as well as commercial research will benefit. Software artifacts and experience into novel curricular directions impact the training of students.

NeTS-NR: Real-Time Communication Support in an Ubiquitous Next-Generation Internet

Elizabeth Belding-Royer, UC Santa Barbara

Award 0435527

Abstract

The trend in Internet deployment is for more advanced, more capable, and more sophisticated applications combined with a growing part of the infrastructure as untethered, mobile nodes. These trends create a requirement for a truly capable and robust network infrastructure to seamlessly deliver data, including real-time streaming data (e.g. voice and video), even though nodes may have heterogeneous capabilities, be on the move, and/or be connected via a wireless link.

To meet the challenges of the evolving Internet, we are developing new solutions to better handle the emerging network and traffic challenges for the next-generation Internet. The next-generation Internet will need to support traditional services (e.g. streaming voice), next-generation applications (e.g. gaming,
social computing), and a set of applications we have not yet even conceptualized. We are building a network to support the significant functionality demanded by these applications. Our set of integrated research projects attempts to develop revolutionary cross-layer solutions for the support of voice and multimedia services in mobile networks. Specifically, we focus on three problems: (i) Coding support for real-time voice; (ii) Routing solutions for real-time applications; and (iii) Formalizing and extending wireless network testbeds.

As an educational impact, not only are we able to achieve traditional key educational objectives, but we are able to connect our work with specific projects at UCSB that expand education opportunities and diversity.

As the ubiquity and acceptance of mobile devices increases, a variety of new applications are emerging. One noticeable trend is the desire for media-rich content. The delivery of media-rich content is poised to transform computing. One specific area that will reap significant benefit from this new content is on-line collaboration. The focus of this work is the mobile network support of collaboration services for on-line collaborations, and the target application is a Collaborative Learning Environment. The requirements for this environment include the integrated use of real-time multimedia streaming, stored media streaming and voice streams, as well as automatic detection of services embedded in the environment. To support the collaborative environment, the following challenges are being addressed: (i) the design and analysis of network support for advanced media that is optimized for the characteristics of mobile wireless environments; (ii) the specification of mechanisms for resource monitoring and proactive networking, whereby the optimal service quality can be delivered to users based on the network and end device resources; and (iii) the development of automatic detection and provisioning of services, such that mobile users can discover and utilize services near their current location, as well as offer services to other mobile users. This work will result in the development of techniques for supporting collaboration services within mobile networks. Numerous applications, such as disaster control, administration, education, and public safety are likely to benefit. An immediate impact of this work is the education of undergraduate and graduate students through participation in this research.

Abstract

Program: NSF 04-588 CISE Computing Research Infrastructure
Title: CRI: Collaborative Research: WORKIT: A Universal Wireless Open Research KIT

Lead Proposal: CNS 0454288
PI: Henning Schulzrinne
Institution: Columbia University

Proposal CNS 0453830
PI: Thomas LaPorta
Institution: Pennsylvania State Univ University Park

Proposal CNS 0454329
PI: Elizabeth M. Belding-Royer
Institution: University of California-Santa Barbara

Proposal CNS 0454174
PI: Scott C. MIller
Institution: Lucent Technologies, Bell Labs


This project addresses the need for wireless network tools and platforms as recommended in the 2003 NSF Wireless Network Workshop report. The project will build on the IOTA (Integration of Two Access Technologies) project at Bell Labs. The PI's will enhance and develop IOTA for a software and systems package in a distributable form called the Wireless Open Research Kit (WORKIT). WORKIT will include source code and documentation and also be embodied in low-cost off the shelf hardware. WORKIT will be an enabler for research in mobility management, interlayer awareness, software algorithms for optimal network selection, reconfiguration, security, accounting, authentication, policy download and enforcement, and hybrid wireless networking. Broader impacts of this project include use of WORKIT in education and enabling stronger university/industry collaborations in this area of emerging importance.
at colleges and universities.

Recent Internet expansion, at least in terms of geographical coverage, has largely occurred using wireless technology. The goal of this research grant is to enable the deployment of service-capable and responsive wireless-based networks through real-time network diagnosis and dynamic adaptation.

Only through an integration of real-time measurement and analysis (localized, autonomous adaptation by network devices, and management though visualization and interactive analysis) can wireless networks achieve long-term utility and stability while also providing support for increasingly complex services.

The research in this project is divided into five areas: dynamic monitoring, which includes work to improve the accuracy of monitored data as well as the real-time capability to perform targeted high-fidelity monitoring; network health diagnosis, which attempts to determine the real-time operational status of a variety of metrics; dynamic provisioning, which uses status information to adjust network operation and protocol parameters in order to improve performance; interactive visualization, which attempts to aid network understanding through interactive and scalable display techniques; and finally, management and planning, which takes a longer-term view of wireless network operations and focuses on capabilities like additional resource placement. These projects provide intellectual merit through new designs for wireless networks, work to develop a clear set of design solutions, investigation of possible alternatives within each set, and evaluation of proposed solutions.

The research will have a broad impact on research, industry, society, and education. It will offer new directions in research, impact wireless network design and deployment, and improve the robustness of wireless network deployments.

The large amount of unlicensed and semi-unlicensed bandwidth available for millimeter (mm) wave communication enable multi-Gigabit wireless networking that can potentially transform the telecommunications landscape.

Intellectual Merit: This research investigates the use of the unlicensed 60 GHz ``oxygen absorption'' band for providing a quickly deployable broadband infrastructure based on multi-Gigabit outdoor mesh networking. Millimeter wave links are inherently directional: the directionality is required to overcome the increased path loss at higher frequencies, and is feasible for nodes with compact form factors using antenna arrays realized as patterns of metal on circuit board. This project addresses the cross-layer design of mesh networks with such highly directional links, in which implicit coordination using carrier sense mechanisms cannot be relied on, and there is no omni-directional mode for explicit coordination. In addition, the research will investigate new design principles for directional medium access control, with the challenge being to coordinate nodes despite the deafness induced by directionality, while taking advantage of the drastically reduced spatial interference. The project will also study methods for network discovery and topology updates, the interactions between scheduling and routing; and the impact of oxygen absorption on network capacity and protocol design/performance.

Broader Impact: The principal investigators will develop publicly available mm wave network simulation tool, intended to engage a larger research community in this emerging field. The investigators will also explore other mechanisms for broader impact including technology transfer, undergraduate research, and curriculum updates featuring mm wave communication.

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

Accurate wireless measurements are critical to the sustained growth of deployed wireless networks, as well as the successful development of wireless innovations. Because of the significant effort required to deploy wireless networks and obtain reliable measurements, current wireless traces are lacking both in breadth of environments and consistency of methodology. The AirLab project seeks to facilitate meaningful analysis of wireless networks by deploying a distributed wireless measurement infrastructure that produces consistent and comparable wireless traces over different deployment environments. AirLab provides core periodic measurements as well as user-driven experiments, and a centralized repository for storing, accessing, and statistically analyzing wireless traces. The richness of these measurement datasets allows researchers to detect and confirm hidden trends, and derive statistically meaningful conclusions based on real-world observations. All AirLab measurements are public and accessible by the research community, thereby lowering the barrier to entry for research and enabling researchers to innovate without the upfront expenses of deploying local wireless testbeds. The project integrates its research outcomes into the undergraduate and graduate education programs. It also proactively seeks to increase the number of women and underrepresented groups in the field.

The newly ratified IEEE 802.11n standard brings a number of new possibilities in the quest for attaining wire-like transmission speeds. The number of subchannels, the option for channel bonding, and the use of multiple antennas and MIMO technologies result in a vast variety of potential transmission strategies. Because of the number of variables, selecting the 'right combination' given the offered load, interference patterns and environmental noise is a complex undertaking. A naïve channel assignment strategy will result in sub-optimal performance due to unnecessary channel contention. This work addresses a number of open questions in the quest to develop a channel assignment strategy for 802.11n that maximizes spatial reuse. In particular, the work seeks to answer to the following questions: (i) how should MIMO transmission schemes, channel bonding, and DFS considerations best be integrated into a channel management solution to maximize performance?; (ii) how can the gains achieved by MIMO systems best be utilized to influence the channel management system?; and (iii) how should metrics that influence these decisions be obtained and redefined for 802.11n systems?

The project will be facilitated through a partnership between UC Santa Barbara and HP Laboratories. Outcomes of the work will include a set of solutions for dynamically monitoring current channel state, and an integrated channel management solution that utilizes monitoring output to achieve high-speed, long transmission range communication in 802.11n systems.

Access to communication plays a pivotal role in the socio-economic development of any nation. While the Internet has revolutionized the development of economic, social, financial and educational sectors of the industrialized world, it has also created a 'digital divide' that separates the affluent and developed nations from the developing and under-developed regions of the world. Significant progress has been made in bridging this digital divide by bringing Internet connectivity to rural regions through Internet kiosks and cafes whereby citizens travel, often by foot, to these central areas in order to access the Internet. While clearly Internet access through this model is much better than no access at all, these public terminals are not a satisfactory end solution due to long travel distances from homes, limited hours of availability, high usage costs, and long wait times.

The goal of this research is to extend Internet connectivity from the point where it is brought into the community by a long distance link (i.e., satellite, long range WiFi, etc.), to provide coverage throughout the village such that residents have Internet access in their homes, offices, schools and public buildings. The research consists of an ambitious, integrated set of research projects that provides Internet connectivity throughout a village in a developing region. The work differs from, and is complementary to, prior work on rural wireless networks in that the focus is, not on the long-distance links that connect the local network to the Internet, but on the development of solutions that provide widespread, local coverage across a geographically dispersed community for currently available end devices. Working in partnership with rural Zambians, a network architecture will be developed that greatly enhances Internet access in rural Africa and elsewhere. This work makes several key contributions:

- To provide widespread connectivity across a geographically dispersed rural community, a customized cross-layer protocol stack for the white spaces spectrum will be developed. This stack includes an integrated PHY/MAC layer, called a transmission layer, that jointly considers interference properties, energy constraints and application requirements to select transmission parameters and channel access strategies to most efficiently utilize available spectrum.

- To minimize impact on already congested Internet gateway links, a novel network architecture and supporting application, called VillageShare, will be designed to isolate local network traffic: traffic that originates and ends within the local community network completely avoids the gateway link. As discovered in preliminary work, unnecessary transmissions on the gateway link constitute a catastrophic problem for rural communities and lead to aborted sessions, dropped connections, and poor end user experience.
- To decrease connectivity cost and provide Internet access to users without home computers, this work will develop VillageCell, a low-cost femtocell-inspired system that provides off-the-shelf cellular phones with free local Internet, voice and chat access utilizing the white spaces network as a backbone.
- To evaluate the efficacy of the work and influence the solution design, a qualitative ethnographic study of ICT in the community of Macha, Zambia, will be conducted through cooperation with partner institutions. The study will explore the social, cultural and economic impacts of developed solutions, and ensure solutions are designed in partnership with rural Zambians.

- To demonstrate the benefits of our integrated system, we develop RemoteMath, an SMS/voice-based mathematics tutoring system through which students can obtain after school assistance on math homework.

Broader Impact. The work from this award will have far-reaching impact by expanding the utility of Internet access in developing regions. Prior research clearly indicates the vast economic, social and educational benefits of Internet connectivity in a rural community. Through the principal investigators' (PIs) partnership with two African organizations, the work will directly impact local Africans through the development and deployment of technology that solves complex technological problems while enabling practical, deployable solutions. Locally, the immediate impact of this work is the education of undergraduate and graduate students about the vast potential for societal impact of computer science research. The PIs will leverage their participation in the UCSB Center for Information Technology and Society (CITS) to create an interdisciplinary course on technology for developing regions. In a time when CS enrollments are shrinking, the PIs will use the societal impact of this work to increase student enthusiasm, enrollment, and diversity.

IEEE 802.11 is an evolving standard used throughout the Internet. Recent advances in wireless communication have been incorporated into IEEE 802.11-based standards. IEEE 802.11n and 802.11ac, for example, offer new mechanisms that enable a multifold increase in transmission speeds relative to 802.11a/b/g. Newly available features make configuring a network, and the devices which use it, a critical challenge. The performance of even the most sophisticated networks suffer debilitating degradation if the network is improperly configured. This project is focused on the following questions: 1) What gains can be achieved by closed-loop 802.11n/ac rate adaptation solutions? 2) How can IEEE 802.11 features better be utilized in a rate adaptation solution? 3) How responsive and adaptive should a real-time channel monitoring solution be? and 4) How can the cost of expensive Channel State Information be minimized? By designing new network configuration mechanisms and observing the performance of these mechanisms in a wide variety of real-world deployment scenarios, wireless network performance and robustness are being improved.

As the scale of wireless network deployments grows, the need for effective network configuration mechanisms is critical. The work in this project is developing highly flexible protocol enhancements that are adding significant new performance and robustness capabilities to wireless networks running the newest IEEE 802.11 standards. Through scientific publications, conference presentations, and industrial collaborations, the outcomes of this project will be made available to wireless equipment vendors, thereby achieving tangible improvements in Internet performance.

Tribal communities represent the final frontiers of Internet access in the U.S., with fast (broadband) Internet access available to fewer than 10% of Native Americans on tribal reservation lands. The lack of broadband access is caused by a collection of challenges, including remote terrain, inadequate funding, and complex telecommunication policies. Yet Native Americans need reliable avenues for participation and contribution to Internet content to strengthen their communities. This project investigates technologies that will increase Internet availability on reservation lands. Further, it will develop new methodologies of disseminating Internet content to reservation residents, prioritizing content by relevance during periods of limited connectivity. Ethnographic methods and interviews of Native Americans residing on the reservations will be incorporated to ensure usability and utility of the proposed solutions. Through the trial of the solutions within Southern California tribal communities, the work has the potential to reach over 2,700 homes and 60 community anchor institutions. Within the three participating institutions, the PIs will include in courses results from the research that demonstrate the positive humanitarian impact of computer science in order to increase the appeal of computer science to female and minority groups.

The goal of the research is to make critical inroads to addressing the lack of Internet access on tribal reservations, to increase the number of Native American reservation residents who are able to engage with, create, and disseminate Internet and on-line social network content. This project will achieve this goal through four related elements: (1) develop an architecture suitable for a multi-network setting comprised of cellular, wireless ISP and whitespace networks, where coverage, cost and network speed varies; (2) develop a tribal content distribution network, consisting of computation and storage at cellular, wireless ISP and white space towers across the reservation, that delivers content to and receives content from end users; (3) conduct a limited empirical study of Internet use and organizational network technology use capacity within the TDV community using ethnographic methods to inform the content prioritization and distribution mechanisms. Interviews will also be conducted and engaged in prototyping activities as needed to ensure that the system interfaces support use and administration by members of the community; (4) collect and analyze multiple years' worth of traffic from the TDV network to develop models of content relevance and consumption to prioritize content distribution in the network.

Tribal communities represent the final frontiers of Internet access in the U.S., with fast (broadband) Internet access available to fewer than 10% of Native Americans on tribal reservation lands. The lack of broadband access is caused by a collection of challenges, including remote terrain, inadequate funding, and complex telecommunication policies. Yet Native Americans need reliable avenues for participation and contribution to Internet content to strengthen their communities. The work investigates technologies that will increase Internet availability on reservation lands using capacity that has been allocated to TV stations but is unused, so called ?white spaces?. Through the trial of our solutions within Southern California tribal communities, the work has the potential to reach over 2,700 homes and 60 community anchor institutions. While the immediate goal of the project is to benefit Native Americans throughout the U.S., the work has broad applicability beyond this context. Other indigenous groups, as well as low-income rural communities in the U.S. and elsewhere, face similar problems. Course material will be integrated from this project demonstrating the positive humanitarian impact of computer science in order to increase the appeal of computer science to female and minority groups.

The goal of the research is to develop technologies to support Native American community building through broadening Internet accessibility and supporting social media content production and dissemination across the reservation. The work outlined in this proposal will make critical inroads to addressing the lack of Internet access on tribal reservations, to increase the number of Native American reservation residents who are able to engage with, create, and disseminate Internet and on-line social network content. The goal will be achieve through three related elements: (1) Development of an architecture suitable for a multi-network setting comprised of cellular, wireless ISP and whitespace networks, where coverage, cost and network speed varies. (2) Partnering with the community to pilot a next generation whitespace network on reservation lands, demonstrating geographic reach beyond current pilots and supporting quantitative measurements of changes in network use before and after deployment. (3) Using the initial lessons learned from the pilot to develop approaches to network management that span the socio-technical including, as appropriate, spectrum management, access management, caching policies and scheduled and on-demand content.

This award will support students at U.S. institutions to attend the Workshop on Mobile Computing Systems and Applications (ACM HotMobile 2017). HotMobile, sponsored by ACM SIGMOBILE, will be held in February, 2017 in Sonoma, CA. HotMobile 2017 is an important workshop targeting mobile computing and system integration fields and attending this event will benefit the scientific progress of the student's research. The exposure to the technical content of HotMobile 2017 will inspire students to address the tough problems in their respective fields, with a long-term benefit of scientific advances in these types of networks.

Priority will be given to students who will benefit from attending this workshop, but are unlikely to attend due to the unavailability of travel funding. In addition, applications from female and underrepresented groups in networking research will be strongly encouraged. Up to fourteen students will receive travel grants from this award to attend HotMobile 2017.

Our research addresses the dual goals of improving Internet access in economically marginalized communities while also building local capacity towards regular digital content creation. We focus on Native American reservation communities, which have among the lowest Internet availability rates in the nation. Our work will develop new network technologies to enable reservation residents to meaningfully participate in the Internet, as both consumers and producers of Internet content, in order to create new opportunities for economic development. To ensure the success of our technical work, we will engage community members in the planning, implementation, and dissemination of our research. Our team is partnered with non-profit, Native-serving, and community organizations that are actively working to solve digital inequities.

To create a more usable Internet, we comprehensively rethink middle- and last-mile network technologies to offer adaptive, smart connectivity. Our fundamental contributions include: the disaggregation of control and data planes and a new content upload and download platform that bridges the gap between the network core and end system devices via a smart middle mile; Television (TV) spectrum white space pilot link deployments and network management solution and to study usability in rural regions; and collaboration with community partners through a participatory action research protocol to identify digital information needs and develop a framework for Web-design training to increase the Internet presence of Native-owned organizations. Because Native American reservations share many geographical and population density characteristics with other rural regions, many aspects of our work will be applicable to extending the reach and usability of the Internet to other, non-Native communities within the U.S.

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.

The proliferation of Internet-connected devices and applications, which are heavily reliant on high-speed, robust networks, have made the management of networks difficult and complicated. While the incorporation of programmable switches and machine-learning tools in data-centers and wide-area networks has contributed to improvements in Quality of Experience (QoE), access networks, which heavily rely on human operators for most network management tasks, remain the final frontier for providing a high quality of experience to end-users. The goal of this project is to design, implement, and evaluate RELIEF, a REinforcement-LearnIng (RL)-based sElF-driving wireless network-management system that can dynamically update network configurations to detect, diagnose, and resolve network events that contribute to QoE degradation.

This project will develop new data-collection tools to capture fine-grained network data, new metrics to quantify QoE for the network, a scalable and explainable RL-based learning model to dynamically configure the underlying network and data-processing pipelines for QoE optimization. This project pursues fundamental contributions to the reinforcement learning area by developing novel solutions to inherent statistical and computational challenges. Finally, this project will design new programming abstractions and data structures to build an end-to-end system that optimizes the use of limited network resources to execute the trained RL models at scale.

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.

The U.S. has long suffered from digital inequities in multiple dimensions: rural and tribal regions are far less likely than urban cities to have high speed Internet access. Internet availability and quality within communities can often be predicted based on demographic and socioeconomic factors. The COVID-19 pandemic has brought to the forefront these inequalities; due to shelter-in-place orders, the lack of high quality Internet access has had dramatic impacts, including on the ability to participate in remote learning, remote work, and telehealth. While new government programs have been created to try to broaden access, a fundamental problem persists: no one accurately knows who does and does not have high quality access. There are many datasets of Internet measurements, but each on its own represents too incomplete a picture to provide the fine-grained information needed to discern which communities, or, ideally, neighborhoods lack quality Internet access. However, these datasets, when combined, is expected to provide a rich and geographically broad data source through which it may be possible to accurately assess Internet connectivity and performance. Furthermore, this study can let one learn trends from these datasets to predict Internet accessibility in regions for which no measurement data is currently available.

The goal of this project is threefold: (i) to aggregate data from public and private sources to produce the most fine-grained analysis and detailed maps, to date, within states, at the community and, ideally, neighborhood level, of where fixed and mobile Internet access exists, where it does not, and where it is of too poor quality to be usable; (ii) to build statistical models that use demographic and other social variables to understand variation in Internet availability and quality; and (iii) to use what is learned to build predictive models of Internet service in areas for which there exist insufficient measurement data from available sources.

This work will have broad impacts, including the informing of local, state and federal governments about where investments must be made to ensure all Americans have access to high quality mobile and/or fixed Internet. The project website, digitalaccess.cs.ucsb.edu, will contain information about research methodology and outcomes, including a report on what is learned about the state of California, the first state of focus for this award. Prediction models will also be made available.

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.

The emerging area of self-driving networks provides network administrators at campus networks to automate most network-management tasks. Such an automation ensures that the network remains performant and reliable amidst various disruptions, while requiring minimal interventions from the network administrators. However, making significant contributions to self-driving network research requires developing artificial intelligence (AI) and machine learning (ML)-based tools and demonstrating that they work in practice. Unfortunately, in stark contrast to their counterparts in industry, most academic researchers have neither access to the proper data for developing learning-based tools nor have properly instrumented testbeds for road-testing the resulting tools in realistic settings.

This collaborative project brings together investigators from the University of California-Santa Barbara, University of Chicago, and NIKSUN Inc., to investigate how to use campus networks to overcome barriers to self-driving network research. First, it will deploy packet-processing pipelines at two campus networks to collect the proper network data at scale without compromising user privacy. It will then strategically place programmable network devices at campus networks to safely road-test newly developed learning models in production settings. Finally, it will illustrate the capabilities enabled by these newly-instrumented campus networks for developing, evaluating, and road-testing new learning models with different use cases.

This project is intended to seed a community effort that uses campus networks as vehicles for democratizing self-driving networks research, improving its transparency through reproducibility, and ensuring its success in practice by establishing trust. As such, it promises to be transformative not only for the network community as a whole but also for different campus network stakeholders (e.g., campus IT). Fully leveraging these campus networks' dual role as data source and testbed and seamlessly integrating it into the university's engineering curriculum suggests radically new approaches to teaching, training, and educating engineering students in the era of AI and ML.

The project information will be maintained at: https://democratize-netai.cs.ucsb.edu/.

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.

The U.S. suffers from digital inequality that stretches in multiple dimensions. Several demographic and socioeconomic factors, such as race, ethnicity, and income, as well as population density, are often indicators of Internet availability and quality. To fully bridge the Internet access divide and best allocate available funding, policymakers need to understand the state of Internet accessibility and quality at fine-grained geographical granularity. The goal of this project is to make the best use of crowdsourced Internet measurement data to estimate the distribution of fixed Internet quality at different levels of geospatial granularity with as high accuracy as possible.<br/><br/>To do so, the projects plans to make the following contributions: (i) to develop a Broadband Offerings Tool that aggregates ISP broadband plan offerings and links that data with crowdsourced measurements and socioeconomic data to predict user subscription plans, (ii) to develop new methodologies and algorithms that can detect noisy data points, such as speed test measurements that report bottlenecks in WiFi access or remote peering links, which bias the understanding of Internet quality, (iii) to propose new statistical techniques that use the resulting dataset to output a debiased dataset that removes the spatial, temporal, and demographic biases inherent in crowdsourced Internet measurement data.<br/><br/>Digital inequality continues to persist in the U.S., deepened by the work-from-home and remote schooling resulting from the COVID-19 pandemic. The outputs of this work will be used to report the distribution of Internet quality in a region and predict that of regions for which less data is available. This work will also reveal demographic variables that most influence the U.S. digital divide. The outcomes of this project can be used to inform local, state and federal governments about where investments must be made to ensure all Americans have access to high quality Internet.<br/><br/>A project website will be established, which will contain information about research methodology, models and outcomes. The likely URL is broadband.cs.ucsb.edu. The website will be maintained for the duration of the project, and at least a year thereafter.<br/><br/>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.

About 85% of people in the United States own a smartphone and use it to access the Internet on a regular basis, checking e-mail, using video conferencing applications, communicating with a doctor’s office, or searching for an answer to an urgent question. Sometimes these applications work well, and other times they do not. When they do not work well, the problem is often with the mobile broadband cellular network in the place and at the time of use. Unfortunately no one knows completely and accurately where high quality access exists, nor where regions of limited or no access are present. Accurate maps of coverage quality would enable resources to be directed to areas of greatest need, allow long term tracking of progress on the digital divide, and form a building block for new applications that can adapt to network quality. This project aims to create accurate and complete maps of cellular coverage quality by bringing together multiple measurement datasets and creating guidance for new measurements.<br/> <br/>This collaborative project brings together experts in statistical modeling, machine learning, and mobile networking from Georgia Institute of Technology and University of California, Santa Barbara. The project has two thrusts. The first focuses on creating mathematical models to predict cellular network quality using latent Gaussian processes in novel ways to combine measurement datasets collected with different methodologies. One set of models will consider how coverage quality varies over geographic space; the other will consider how it varies over time. The second thrust focuses on using the predicted coverage quality maps in two key ways, to use the models to create a Quality of Coverage metric that provides useful information to network users, and to use the models to guide in future measurement campaigns so that regions that are not well understood get prioritized.<br/> <br/>The United States Federal Government and other government and non-government organizations have allocated funding to broaden Internet access. However, because no one accurately knows where high quality access exists (or does not), it is difficult to target investments to communities of highest need. If successful, this work will be able to inform local, state, and federal governments about where investment should be made to ensure all Americans have access to high quality mobile Internet. As a result, residents of these communities will benefit from the educational, economic, and medical benefits that Internet access enables. <br/> <br/>https://sites.gatech.edu/mapping-broadband/ - this site will contain products of the project, including datasets, models, algorithms, and publications resulting from the work. The website and repository will be maintained for at least five years, from 2022 to 2027.<br/><br/>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.