Abstract

Mobile sensor networks (MSNs) are widely used in various domains to monitor, record, compute, and interact the information within an environment. To prolong the life time of each node in MSNs, energy model and conservation should be considered carefully when designing the data communication mechanism in the network. The limited battery volume and high workload on channels worsen the life times of the busy nodes. In this paper, we propose a new energy evaluating methodology of packet transmissions in MSNs, which is based on redividing network layers and describing the synchronous data flow with matrix form. We first introduce the cache coherence layer to the protocol stack of MSNs. Then, we use a set of energy probability matrices to describe and calculate the energy consumption of each state in the protocol. After that, based on our energy model, we will give out an energy evaluating method of the MSNs design, which is suitable for measuring and comparing the energy consumption from different implements of hardware/software. Our experimental results show that our approach achieves a precision with less than 2% error and provides a credible quantitative criterion for energy optimization of data communication in MSNs.

Document Type

Article

Publication Date

4-1-2013

Notes/Citation Information

Published in International Journal of Distributed Sensor Networks, v. 2013, article ID 362649, p. 1-10.

Copyright © 2013 Jihe Wang et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Digital Object Identifier (DOI)

https://doi.org/10.1155/2013/362649

Funding Information

Jihe Wang and Bing Guo are supported in part by the National Natural Science Foundation of China under Grant nos. 61272104 and 61073045; Sichuan Science Fund for Distinguished Young Scholars under Grant no. 2010JQ0011; the Fund from State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences under Grant no. ICT-ARCH201003. Meikang Qiu is supported by NSF CNS-1249223 and NSFC 61071061.

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