NeTS: EAGER: A Cross-layer End-to-End Performance Modeling Approach for Large-Scale Random Wireless Networks with Node Cooperative Behavior

University Of Massachusetts, Dartmouth, North Dartmouth MA

Investigators

Abstract

This project provides theoretical framework analyses, engineering design rules, and guidelines for large-scale cooperative implementation and deployment of Random Wireless Networks (RWN). The research advances the understanding of emerging wireless networks and contributes to the RWN research community by meeting the future data capacity demand and the goals of quality of service, and has the potential to transform the findings to a broad range of complex network applications spanning transportation, disaster recovering, healthcare, and other sectors. In addition, an important education objective tightly coupled with the proposed research is to recruit and educate the next generation of network engineers. The findings from this project are disseminated via various public and academic venues. Specifically, this project conducts end-to-end performance analysis of large scale RWN in the presence of node cooperation. It aims at estimating and optimizing the performance of multi-layer-designed RWN to meet the required quality of service prior to network deployment. The project addresses new challenges in modeling multi-hop cooperative RWN through three tasks: 1) integration of Markov Chain with point process for cross-layer modeling; 2) identification of the optimal condition of RWN based on its randomness, dynamics and network cooperative characteristics; and 3) model validation and a case study in mesh networks. Unlike previous studies where cooperative wireless networks or random networks are modeled separately, this project integrates Markov chain and point process for modeling large scale cooperative RWN. This is challenging due to the complexity of cooperative behavior of multiple layers, network randomization and scalability. This modeling approach is crucial for self-organized RWN, because many network applications favor this cooperation in order to improve their quality of service and reliability, reduce their power consumption and interference, and increase their spatial or frequency reuse. The success of this project can significantly advance RWN design and deployment, improve quality of service, capacity, and coverage of the next generation wireless networks.