EAGER: Distributed Models and Algorithms for Pervasive Systems

Development of pervasive computing infrastructure is crucial for enabling the next generation of applications wherein physical- and cyber-subsystems collaborate to achieve a common goal. In a pervasive distributed system (PDS), the cyber-infrastructure algorithms must contend with cyber and physical entities interacting directly with each other in multiple ways.

Such interactions pose several new challenges in designing the underlying infrastructure algorithms. A number of assumptions related to when, where and how entities interact which typically hold in traditional systems may not apply in a PDS. The goal of this project is to develop new models and techniques to design distributed algorithms and middleware that can accommodate both cyber and physical entities in a PDS application.

To develop models and distributed algorithms for pervasive systems this project will extend the traditional graph-based distributed computing models to create a unified model to capture interactions between the physical and cyber entities and the physical phenomena, develop algorithms for coordination and cooperation in PDS applications, and techniques to ensure that algorithms can perform reliably in environments where physical entities may behave unpredictably. This project will integrate the proposed model into existing simulation tools to enable evaluation of scenarios involving different types of physical entities and physical phenomena.

Leveraging the capabilities of pervasive systems will be critical in supporting the needs of businesses and organizations. This research will lead to better understanding of distributed algorithms, and increase the confidence of businesses and organizations in using capabilities of next generation systems. This project will include integration of research and education, and outreach activities such as engagement with high school students for summer internships.

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.