Affiliation:
1. University of California, San Diego, La Jolla, CA
Abstract
Unlike traditional multihop forwarding among stationary sensor nodes, use of mobile devices for data collection in wireless sensor networks has recently been gathering more attention. The use of mobility significantly reduces the energy consumption at sensor nodes, elongating the functional lifetime of the network. However, a drawback is an increased data delivery latency. Reducing the latency through optimizing the motion of data mules is critical for this approach to thrive. In this article, we focus on the problem of motion planning, specifically, determination of the speed of the data mule and the scheduling of the communication tasks with the sensors. We consider three models of mobility capability of the data mule to accommodate different types of vehicles. Under each mobility model, we design optimal and heuristic algorithms for different problems: single data mule case, single data mule with periodic data generation case, and multiple data mules case. We compare the performance of the heuristic algorithm with a naive algorithm and also with the multihop forwarding approach by numerical experiments. We also compare one of the optimal algorithms with a previously proposed method to see how our algorithm improves the performance and is also useful in practice. As far as we know, this study is the first of a kind that provides a systematic understanding of the motion planning problem of data mules.
Funder
Division of Computing and Communication Foundations
DMEA
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
Cited by
34 articles.
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