IHCS: A Stochastic Framework for Robust Wireless Networking

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The objective of this research is to stochastically model wireless networks and develop integrated optimal solutions that maximize social network utilities while guaranteeing survivability against disruptions caused by natural disasters or malicious attacks. The approach is rooted in convex and distributed optimization and entails modeling of possibly correlated failures and changes in traffic patterns, characterization of pertinent performance metrics, and development of protocols that are stable with respect to throughput and robust.With respect to intellectual merit, the project investigates a framework for joint scheduling, routing and control of information flows through wireless nodes while guaranteeing network survivability against large-scale service disruptions. The stochastic model matches the randomness of failures and lends itself to optimality criteria and computationally affordable protocols. Various applications and critical issues are studied, including quality of service, fairness, relaying, robustness, on-line, distributed implementation and sensitivity.With respect to broader impact, the theme is directly relevant to the evolution of the IEEE 802.11 family of wireless local area network standards and emerging initiatives in mobile ad hoc networks. Incorporation of robustness has important potential societal and economic impact in future wireless networks, especially in wireless sensor networks where survivability is critical. Through the development of experiments and trials, this research provides meaningful experiences to students and integration of the expertise gained to enhance the content of graduate classes. Outreach to government and industrial sectors is accomplished through short courses in laboratories, tutorials in workshops and conferences, and student-faculty-staff collaboration to develop field trials of the proposed protocols on the University of Minnesota campus.