Energy-aware online routing with QoS constraints in multi-rate wireless ad hoc networks

  • Authors:

  • Wei Yang;Weifa Liang;Jun Luo;Wenhua Dou

  • Affiliations:

  • National University of Defense Technology, ChangSha, HuNan, China;The Australian National University, Canberra, Australia;National University of Defense Technology, ChangSha, HuNan, China;National University of Defense Technology, ChangSha, HuNan, China

  • Venue:
  • Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
  • Year:
  • 2010

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Abstract

Wireless ad hoc networks consist of hundreds to thousands of mobile nodes that are powered by batteries. To prolong the network operational time, energy conservation in such networks is of paramount importance. Energy optimization thus is one major objective in the design of routing protocols. However, in some stringent real-time applications including target tracking and bushfire surveillance, latency is an important concern, and little attention has been paid to it in the design of routing protocols for such applications to meet the specified Quality of Service (QoS) requirements like the end-to-end latency constraint. In this paper we focus on online energy-aware routing protocol design for routing requests to meet various end-to-end latency constraints under the multi-rate environment, we aim to maximize the network lifetime through striking the right balance among the node's transmission rate, the end-to-end latency, and energy consumption. Specifically, due to the NP-hardness of the problem of concern, we propose a joint optimization framework consisting of finding a routing path and assigning a specific transmission rate at each node in the path for each request such that the total energy consumption is minimized. We also devise novel heuristic algorithms for the problem, based on different energy cost metrics. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms in terms of network lifetime. The experimental results show that the proposed algorithm incorporating the energy utilization ratio of the residual energy of a node to its initial energy capacity into the cost metric outperforms the others significantly.