Seung-Jong Park, Ph.D. - US grants

In this proposal, we propose to develop a Cyberinfrastructure for Reconfigurable Optical Networks (CRON). With supercomputing facilities and storage resources geographically dispersed across the US and around the globe, the success of scientific applications and collaborations relies increasingly on high-speed optical networks. The development and deployment of national and international optical networks and regional networks make it possible for more scientists, research and educational institutes to connect and collaborate at previously unachievable levels.

However, there is a critical gap between the research projects and the deployed high speed networks, caused by the following problems: (1) Limited physical resource ? e.g., the expensive resource of the LONI network has limitations on the number of simultaneous users, and there are many research and/or educational institutions in Louisiana that cannot access the networks due to the last mile problem.; (2) Unmodifiable environment - because the currently deployed networks are used for production as well as research, individual users cannot impose on other users by modifying environmental parameters, such as network protocol stacks and operating systems; and (3) Partial environment ? applications or protocols developed for one specific high speed network should work correctly over all kinds of different networks, irrespective of different network bandwidths and delays. However, each deployed physical network has one physical characteristic, such as bandwidth and delay.

The goal of this project is to bridge the gap between physical networks and research by developing a virtual networking and computing cyberinfrastructure, CRON, that provides integrated and automated access to diverse networking environments. To provide the virtual environments, CRON consists of two components: hardwares including a switch, optical fibers, network emulators and softwares automatically reconfiguring the hardwares based on users? demands. CRON resolves the critical issues by achieving three key objectives: (i) Unlimited virtual networking resource CRON will enable researchers to explore new network technologies and rapidly assess their impact on applications irrespective of physical limitation and allow educators to introduce the state-of-art networking environment to students who cannot access those physical networks. (ii) Reconfigurability CRON will allow researchers and educators to modify the virtual environments without interfering with others who share CRON. (iii) Complete environment CRON will provide all kinds of networking environments, including regional networks and global transoceanic optical networks.

This CC-NIE Integration project performed at the Louisiana State University is developing a cyber-infrastructure integrating six different large scale scientific research groups with high performance computing (HPC) clusters at LSU using software defined network technology and Hadoop and MPI (Message Passing Interface) based parallel frameworks.

The project consists of three objectives: (i) Building 10Gbps software-defined network (SDN) with OpenFlow switches and controllers to provide multiple virtual network slices to each group; (ii) Transferring Big Data with automatically tuned operation through multiple optical paths over the SDN network achieving at most 20Gbps of aggregated disk-to-disk transfer rate; and (iii) Analyzing Big Data by developing data-intensive distributed computing frameworks with Hadoop and MPI technologies parallelizing large number of jobs over HPC clusters.

Those three components are integrated with a web portal service and a GENI-enabled network management system. To achieve high disk-to-disk transfer rate at 20Gbps, the project has an industrial partnership with Samsung Electronics that contributes 70TB Solid State Drive (SSD) storage and optimizes the I/O bandwidth.

The cyber-infrastructure accelerates the current Big Data research projects spanning a wide range of research areas including gene sequencing research at Biology and Vet School, computational chemistry, big data mining at Computer Science, coastal hazard simulation research at civil and environmental engineering. In the end, the project will establish a methodology to build integrated cyber-infrastructures consisting of high speed networks, high performance computing, and high speed storage for the Big Data Science and Engineering.

This is an award to acquire a compute cluster at LSU. The computer is a heterogeneous HPC cluster named SuperMIC containing both Intel Xeon Phi and NVIDIA Kepler K20X GPU (graphics processing unit) accelerators. The intent is to conduct research on programming such clusters while advancing projects that are dependent on HPC. The efforts range from modeling conditions which threaten coastal environments and test mitigation techniques; to simulating the motions of tumors/organs in cancer patients due to respiratory actions to aid radiotherapy planning and management. The burden of learning highly complex hybrid programming models presents an enormous software development crisis and demands a better solution. SuperMIC will serve as the development platform to extend current programming frameworks, such as Cactus, by incorporating GPU and Xeon Phi methods. Such frameworks allow users to move seamlessly from serial to multi-core to distributed parallel platforms without changing their applications, and yet achieve high performance. The SuperMIC project will include training and education at all levels, from a Beowulf boot camp for high school students to more than 20 annual LSU workshops and computational sciences distance learning courses for students at LONI (Louisiana Optical Network Initiative) and LA-SiGMA (Louisiana Alliance for Simulation-Guided Materials Applications) member institutions. These include Southern University, Xavier University, and Grambling State University - all historically black colleges and universities (HBCU) which have large underrepresented minority enrollments. The SuperMIC cluster will be used in the LSU and LA-SiGMA REU and RET programs. It will impact the national HPC community through resources committed to the NSF XSEDE program and the Southeastern Universities Research Association SURAgrid. The SuperMIC will commit 40% of the usage of the machine to the XSEDE XRAC allocation committee.

This interdisciplinary research project will examine whether social and geographical disparities exist during the four phrases of emergency management (mitigation, preparedness, response, and recovery). The investigators will use multiple perspectives and scales to address the research questions, including analysis at the community, individual, and organizational scales. Findings from this project will provide valuable insights into the interplay among regional disparities, individual social networks and behavior, and governmental/organizational policies. This project will expand knowledge of whether social media use may serve to overcome or further deepen the social and geographical disparities in each phase of emergency management. The project will enhance understanding of how to conduct efficient mining of social media data in order to produce useful and valid scientific information, thereby advancing both social science and information science research by developing and testing algorithms that can be used to mine noisy and imperfect data from sources like Twitter. The knowledge gained from this project will help develop strategies to reduce disparities, create effective social media campaigns and emergency management outreach, and promote resilience to disasters. The methods used in this project will be applicable to study other disasters in other regions.

Understanding the sources, patterns, and consequences of social and geographical disparities in disaster resilience is critical to building long-term resilient, healthy, and sustainable communities. Traditional resilience analysis has been confined mostly to the use of static data collected at scheduled intervals. With the advent of the "Big Data" era, real-time human response data extracted from social media could provide new opportunities for studying disparities in disaster resilience. The investigators will compare Twitter data from two events, Hurricane Isaac and Hurricane Sandy, both of which occurred in 2012. They will pursue four interrelated research components: (1) development of data-mining algorithms for the evaluation and visualization of Twitter data; (2) analysis of social media and resilience disparities at the community (zip-code) level across the emergency management cycle; (3) an online survey of Twitter and non-Twitter users to understand effects of social media use on individual resilience, social networks, social support, and social disparities; and (4) analysis of bi-directional communication among residents and governmental and non-governmental organizations throughout each event cycle. Through an investigation of the Twitter data before, during, and after the hurricanes coupled with analysis of online surveys, the researchers will be able to address a set of core research questions: (1) Are there distinct geographical and social disparities in the use of social media in disaster resilience? (2) What are the sources and consequences of such disparities? (3) How do these disparities vary across the four phases of the disaster cycle? (4) How do these disparities affect resilience? (5) How can social media data be used to improve resilience? This project is supported through the NSF Interdisciplinary Behavioral and Social Sciences Research (IBSS) competition.

The U.S. Economic Development Administration, through its Investing in Manufacturing Communities Partnership (IMCP) initiative, recently named the entire east-west, 200-mile span of South Louisiana centered around Baton Rouge (BR) as one of the nation's strategic manufacturing regions. This "chemical corridor" is the home of hundreds of chemical manufacturing facilities and refineries worth billions of dollars. Despite the major economic significance of this region, the BR area suffers from critical problems including i) crippling transportation issues, and (ii) high levels of crime. Heavy traffic congestion is one of the main reasons why manufacturing industry in BR is reluctant to build new plants and hire more people in this region; it is also a key factor in making the region unattractive for new investments from elsewhere in the U.S. The violent crime rate is substantially higher than that of similarly- sized regions, further affecting economic development in this important region. The goal of this S&CC planning proposal is to build a partnership between community stakeholders and a multidisciplinary team of academic researchers. By considering economic and social issues in a holistic manner, this partnership will develop research concepts that will promote and employ S&CC technologies to help stakeholders tackle the major factors affecting the region's economic progress. Through multidisciplinary team- building and strong community engagement, a proposed integrative S&CC research concept will have significant impacts on various disciplines and communities for planning and developing smarter cities. In particular, the research concept will be directly aligned with the strategic plans determined by the city's Smart City Committee and Subcommittees. Through the proposed Web portal, PIs will share the developed outcomes and information collected from the project with researchers from other higher education including Southern University , a local HBCU. The most significant impact will be seen through quality of life measures pre- and post-project implementations. Building community-wide tools to help stakeholders of all missions addressing crime- and traffic-related challenges for all citizens in the region has real impact on quality of life and economic health, making the region more attractive for growth.


From a technical perspective, this project proposes to build a multidisciplinary research team by integrating different research groups with significant research strength in the areas of High Performance Computing (LSU CCT), Big Data Analysis and Cybersecurity (Computer Science), Sensors (Electrical Engineering), Violence Prevention (Social Work and Sociology), and Transportation (Civil Engineering). The intellectual goal is to define challenging problems and develop research concepts via offline workshops, tutorials, and an online Web portal, which allows an easy access to integrative cyberinfrastructure for computing, storage, and software tools. The software tools we plan to develop will enable predictive analyses on heterogeneous data collected from city infrastructure, public open data from the city of Baton Rouge, and relevant social network data. The developed research concepts will increase the research capacity of every individual research group, enhance the understanding of cross-disciplinary demands, and advance state-of-art technologies for the design of smart and connected communities.