CAREER: Designing Large-scale Ad Hoc Networking Systems: Models, Analysis, and Protocols

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Designing large-scale ad hoc networking systems capable of supporting heterogeneous traffic types involves a large number of factors (e.g., protocols, parameters, network size, traffic characteristics) that interact in a very complex manner, making system optimization a non-trivial problem. The principle goal of this project is to develop a deeper understanding of the fundamental performance, scaling properties, and tradeoffs and includes two main research thrusts. The first is focused on constructing analytical and empirical models that accurately characterize the functional relationship between performance metrics (e.g., end-to-end delay) and significant factors. Analytical end-to-end delay and packet discard models are being developed that account for interactions among the traffic arrival process, wireless channels, error control mechanisms, and mobility-induced path failures. The empirical models are based on two modeling approaches: (1) response surface methodology and regression analysis and (2) the class of Levenberg-Marquardt multilayer perceptron neural networks. In the second research thrust, we are using the above models to explore several scaling and performance properties, including which system configuration(s) lead to optimal, robust, scalable, or satisfiable performance response(s) over specified regions of interests. Using the predictive empirical models, adaptive cross-layer feedback-based mechanisms are being designed for transport and QoS-sensitive routing strategies. The success of the proposed project will produce solid models, principles, and protocols on which to build large-scale ad hoc networks. An educational component will enhance education by integrating statistical experimental design and modeling research into wireless networking courses and will enhance national research initiatives by establishing research partnerships with non-Ph.D. granting universities.