Satyajayant Misra, Ph.D. - US grants

This CREATIV award is partially funded by the Networking Technologies and Systems (NeTS) program in the Division of Computer Networks and Systems in the Directorate of Computer & Information Science & Engineering, the Animal Behavior program through the the Divisions of Integrative Organismal Systems and Emerging Frontiers in the Directorate of Biological Sciences, the Experimental Program to Stimulate Competitive Research (EPSCoR), the Office of the Division Director in CISE/CNS and the Office of the Assistant Director in CISE. This project aims to address the major barriers to adoption of wireless sensor networks (WSNs) in multiple cross-disciplinary domains, particularly high cost, low customizability, lack of rugged designs and complex programming models. The project team aims to surmount these barriers to provide a potentially transformative wireless sensor network design framework that can be used by anyone with minimal technical skills, and yet achieve the benefits of pervasive monitoring and sensing through large-scale ubiquitous wireless sensor networks. The PIs will leverage their multi-disciplinary and cross-domain expertise to address these challenges using experimental biology research as their platform.

The goals of this project are to provide and/or enable: 1) a hardware framework for low-cost, rugged, and customizable sensor nodes, in a wide range of form factors, 2) autonomous manipulation and monitoring of electro-physiological parameters of electro-motor circuits in vivo and in vitro using WSNs, 3) novel network protocols and algorithms for monitoring aquatic animals in the field, and 4) a software framework that makes programming WSNs easy and intuitive for users with minimal programming experience. By removing the barriers to adoption through plug-and-play, and easy customization and programming, this proposed research hopes to make WSNs ubiquitous in our daily life in general and in biology research in particular.

In the short term, this project will enable experimental researchers in labs and in the field to stimulate and monitor animals/specimen in real-time and without human intervention, which will significantly improve understanding of animal responses to diverse stimuli. In the long term, the outcomes of this research will help WSNs become ubiquitous in our daily life and as easy to use as computers today. The project will provide undergraduate and graduate students including women and minorities in the classes and labs of the PIs the benefit of an unique interdisciplinary learning and research environment. It will leverage NSF GK-12 DISSECT, BPC, and YWiC initiatives in the computer science department of New Mexico State University to expose middle and high school students in the city of Las Cruces to STEM research and teach them computational thinking.

With National Science Foundation support, New Mexico State University will establish the interdisciplinary Center of Research Excellence in Design of Intelligent Technologies for Smartgrids (iCREDITS). The vision of iCREDITS is to obtain sustainable generation capacity by shifting the paradigm from power delivery to energy delivery, using smartgrid concepts. In an energy delivery system, energy is viewed as a commodity, which can be produced, stored, and exchanged. This paradigm will lead to better economic sustainability due to more efficient generation, transmission and usage. This vision accommodates the creation of small microgrids, larger customer-driven microgrids in a distribution feeder and, ultimately, the smartgrid,which includes the generation, transmission, and distribution of the entire power system. The research focus of iCREDITS is to develop the fundamental science and engineering necessary for the energy delivery paradigm. The realization of the smartgrid vision requires addressing a second fundamental problem: the dramatic shortage of smartgrids workforce, exacerbated by the lack of diversity.

Intellectual Merit:

The proposed research will articulate four research strands, addressing the core components of a modern smartgrid architecture; iCREDITS will strive to combine the innovations within the research strands to advance the broad science and engineering of smartgrids. The challenge addressed by iCREDITS is to investigate the fundamental science in power systems, communication systems, disturbance modeling, and agent-based coordination mechanisms and their interactions to enable the energy-delivery paradigm. The iCREDITS educational initiatives effort will provide comprehensive pathways, starting in the K-12 system and continuing to the doctoral level. The center's educational models are interdisciplinary and designed to serve a student population that is diverse in academic and cultural backgrounds.

Broader Impacts:

The research agenda is transformative and focused on making deep contributions to the general field of smartgrids - a field that has profound impact on the U.S. economy and the sustainability of the nation's energy infrastructure. Project activities are designed with
strong components of outreach and education, to enhance the participation of women and other underrepresented groups in smartgrids. iCREDITS will address the issues of underrepresentation by expanding the research and training pipeline and introducing specialized mentoring and retention mechanisms. iCREDITS will infuse smartgrids expertise in a range of academic programs, enhancing the competency of New Mexico State University.

NON-TECHNICAL SUMMARY
This Research Experience for Undergraduate (REU) site will support NSF's mission to promote progress of science by introducing big data analytics in Cyber-physical Systems (CPS) to undergraduate students, helping advance the state of art, and preparing them for the future scientific workforce. The site's objectives include (i) motivating and solidifying students' interest in Computer Science (CS) in general, and big data analytics in particular; (ii) providing students with problem solving skills for conducting research in big data analytics and for presenting scientific findings verbally and in writing; (iii) equipping students with working knowledge of applying data management and data analytics techniques, by involving students in research projects related to different aspects of CPS; (iv) enhancing self-confidence and self-efficacy of participants, by creating a sense of belonging to a diverse community; and (v) broadening participation in computing, and contributing to diversify the computing workforce. The research outcome will advance the state of the art of big data analytics and push the research agenda of utilizing big data techniques for CPS. The REU site will reach undergraduate students beyond the New Mexico State University (NMSU) campus and train workforce for big data analytics in CPS. Special emphasis will be placed on recruiting underrepresented students nationwide. The participating students will be mentored by the site researchers to disseminate their research projects' findings via professional conferences and through the REU site website.

TECHNICAL SUMMARY:
The goal of this REU site initiative is to inspire and prepare undergraduate students to pursue careers in STEM with a focus on big data analytics for Cyber-physical Systems (CPS). PI's propose research projects to explore big data analytics for CPS in three intertwined layers: (L1) systems and architecture, (L2) models and algorithms, and (L3) visualization, spanning across four CPS application areas including smart grids, wireless sensor networks, smart homes for elderly and disabled, and disaster response. The planned student activities include: (i) team-based research activities on focused research projects, (ii) creation of cohorts, which will engage in training workshops, to develop research skills and to prepare for graduate schools, (iii) field trips to companies, and local and national labs to broaden students' research horizon, (iv) workshop and conference participation to present research findings, and (v) mentoring by faculty members and interaction with other student researchers. The proposed research outcome has the potential to advance the operation, protection, and utility of CPS. The research activities in the projects will equip student participants with skills and knowledge related to both big data analytics and CPS. The training workshops will help students develop research skills and their career paths. The field trips will broaden participants' understanding about data analytics research for CPS.

The Cyber Infrastructure Training and Mentoring (CI-TraM) project serves the national interest by developing and increasing the cyberinfrastructure (CI) literacy of undergraduates who are interested in STEM careers. It does this through technical training and career mentoring focused around building knowledge in CI. CI-TraM provides direct mentoring of new undergraduates by active STEM researchers and IT professionals. The training will be provided by a diverse group of researchers in CI-intensive domains and CI professionals. Topics will include network and data security, high performance computing, computer architecture, and data analytics tools to provide the background to explore computing in a) cybersecurity, b) patterns discovery in biological data, c) computational physics, d) neuroscience, e) game design and human-computer interaction, etc. This will help address the challenge of creating a future STEM workforce that has the technical and professional skills needed to promote the progress of science; to advance the national health, prosperity and welfare; or to secure the national defense. The CI-TraM program, developed in a Hispanic Serving Institution (NMSU), cultivates untapped talent within a growing, yet underrepresented, population in STEM careers. The model used for community engagement and student recruitment addresses the transitions between secondary education, post-secondary education, and individual career planning and management.  The CI-TraM model will be designed to become institutionalized with the ability to be replicated in other communities.

The main goals of the CI-TraM program are: 1) To develop a program that exposed and retains students in CI-STEM fields while teaching them valuable technical and life skills needed for successfully pursing, attaining, and maintaining careers, and 2) To develop a program that is sustainable and scalable to other institutions so that other student populations may benefit from the program. The program utilizes common job site internship procedures in area high schools that provide dual/concurrent college credit. The CI-TraM program will create a cohort of students interns each academic semester and summer (50/yr) that have demonstrated interest/ability in STEM career pathways. To achieve Goal 1, technical training and career planning modules developed and taught by working STEM researchers and IT professionals will be completed by each student intern. At the start and finish of the program a general assessment of a student's knowledge will be performed, and each module would have a tangible deliverable to evaluate student understanding and progress throughout the program. The program itself will be assessed by a longitudinal follow up that will track students into their futures. Assessment results will be used by the program coordinators in a continual improvement process. To achieve Goal 2, the modules will be generated using a standard Learning Management System allowing them to be transferable to other universities. External consultant-created rubrics will be used to evaluate the modules and their efficacy as well as the efficacy of the modules together as the body of the CI-TraM program and available for others to use.

Technological advances have moved society into an exciting era of mobile computing. Our daily lives can be further enriched by a new generation of mobile applications, such as augmented reality (AR) which broadens one's real-world perception by harmonizing sound, image, video, and sensors from multiple sources to aid comprehension and navigation. However, today's Internet operates with the address-based TCP/IP protocol architecture developed 40 years ago, which greatly limits the full promises of these new applications. Thus, current AR implementations face challenges in performance, scalability and availability upon disasters. This proposed research project (ICE-AR) aims to develop a new wireless network architecture to address these limitations and provide pervasive support for these emerging applications.

The ICE-AR project team will apply and extend six years of research efforts on Named Data Networking (NDN), a realization of the Information Centric Networking (ICN) vision, to create this new architecture. The design emphasizes application-level data naming, data-centric security and computing, asynchronous publishing and consumption, and efficient use of local and proximate resources. The architecture will unify latest advances in wireless communication with domain-specific computing technologies to accelerate AR at the wireless edge and deliver robust performance, with or without the pre-deployed infrastructure support.

The Centers of Research Excellence in Science and Technology program provides support to enhance the research capabilities of minority-serving institutions through the establishment of centers that effectively integrate education and research. With National Science Foundation support, New Mexico State University will build on the accomplishments of their Phase I Center by engaging in research focused on scalable approaches to the realization of microgrids and networks of microgrids, that meet criteria of security, reliability, and resilience. Phase II Center investigators will conduct collaborative research to explore transformations of existing electricity distribution infrastructures into interconnected intelligent microgrids.

The Phase II Center addresses design, operational, and security challenges of next generation electric power production and delivery, providing sustainability, reliability, and resilience against low-probability, high-impact events. The Center articulates three research strands, and a fourth integration effort. The Modeling, Operation and Integration strand addresses the lack of standardized physical design and operation approaches for customer-centric distribution microgrid architectures and creates designs that balance sustainability, economy, and reliability. The Security and Resilience Frameworks strand defines the architectural frameworks necessary to realize security and resilience, providing constraints on the models and algorithms from the other research strands. The Data-Driven Decision-Making strand implements the data-information-knowledge-decision flow to support operation and control of the customer-centric distribution microgrid, optimizing for resilience and enabling user-centered and transactive behavior. All research strands converge to investigate interactions and to validate the software and hardware implementations developed.

The Center at New Mexico State University will strive to become a leader in the creation of sustainable, integrated and comprehensive learning pathways in customer-centric distribution microgrid and critical cyberphysical systems. The Phase II Center addresses underrepresentation by expanding the research and training pipeline and introducing specialized mentoring and retention mechanisms. New Mexico State University will also enhance competency by infusing smartgrids expertise in a range of academic programs.

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.

Diverse, novel applications, such as autonomous driving, Industrial Internet of Things (IIoT), Augmented and Virtual Reality (AR/VR), tele-medicine, and distributed machine learning are driving the rapid growth in research and development in edge computing deployed in the last mile of the network where dynamic and resource constrained wireless communications dominate. These applications require computation to happen close to the data source and be coordinated across nearby devices, base stations, or access points as well as with data services such as stored media download at the edge. They may also require computation offloading to a data center located near the edge or somewhere on the Internet for processes such as image annotation and machine learning. Furthermore, these applications rely on ultra-low latency communications, reliable computations, and security and privacy at the network edge. This project aims to investigate the vision of a secure Pervasive Edge Computing (PEC) environment where the abundant edge computing resources (e.g. city infrastructure, individuals? devices, and future wireless devices), can be easily and securely marshaled, in a trusted manner, to make the participation of any device in edge computing feasible. The particular research problem addressed in this project is access control and authorization of devices and services at the edge?essential for the broad adoption of PEC to meet the needs of future applications in healthcare, transportation, smart cities, and the smart grid.

This project focuses on investigating the access control and authorization mechanisms in an information-centric PEC network. The researchers will investigate mechanisms for delegating access control-as-a-service (ACaaS) to the network edge; efficient revocation of access credentials to data and services in a dynamic manner; and secure accounting of the access control operations to verify access control claims of the service and also to assess users? usage. They will contrast their designs with competing designs in the IP network to provide comprehensive comparative assessments of the efficacy of proposed approaches. The results from this project will help increase the security, adoptability, and trust in edge computing and speed up its adoption by enabling more of the edge devices to become part of edge computing.

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.