Providing each node in a multihop wireless network with one or more multi-channel radios offers a promising avenue for improving the networking performance. Recently, the impact of multiple channels and radios on network throughput has been extensively studied. But little is known about their impact on communication latency, which is an important performance metric for a broad class of time-critical applications such as emergency response and disaster recovery. While it is of no doubt that multiple channels and radios hold potentials of reducing the communication latency, what really matters is how much benefit can be realized by specific algorithms. This research conducts comprehensive algorithmic studies of minimizing the communication latency by utilizing multiple channels and radios. The algorithms developed in this research can be applied directly to support real-time applications in multihop wireless networks. The theoretical analysis of the performance against the number of channels and/or the number of radios can also provide guidance to industries on cost-effective design of multihop wireless networks.
This research focuses on the communication schedules for four primitive communication tasks which are involved in almost all applications: broadcasting, aggregation, gathering, and beaconing. The problem of seeking a shortest communication schedule for each of these four tasks is NP-hard. The investigators develop constant-approximation algorithms for them and analyze the impact of the number of channels and the number of radios on the latencies of the constructed communication schedules. This research is of interest to a number of research communities, and may serve as a basis for interesting future projects on multi-channel multi-radio multihop wireless networks. Both student training and curriculum development are integrated into this research.
