A framework for Resource-Aware Data Accumulation in sparse wireless sensor networks

被引:23
|
作者
Shah, Kunal [1 ]
Di Francesco, Mario [1 ]
Anastasi, Giuseppe [2 ]
Kumar, Mohan [1 ]
机构
[1] Univ Texas Arlington, Box 19015, Arlington, TX 76015 USA
[2] Univ Pisa, I-56122 Pisa, Italy
基金
美国国家科学基金会;
关键词
Sparse wireless sensor networks; Mobile data collectors; Reinforcement learning; Resource allocation; Adaptive algorithms;
D O I
10.1016/j.comcom.2011.06.010
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wireless sensor networks (WSNs) have become an enabling technology for a wide range of applications. In contrast with traditional scenarios where static sensor nodes are densely deployed, a sparse WSN architecture can also be used in many cases. In a sparse WSN, special mobile data collectors (MDCs) are used to gather data from ordinary sensor nodes. In general, sensor nodes do not know when they will be in contact with the MDC, hence they need to discover its presence in their communication range. To this end, discovery mechanisms based on periodic listening and a duty-cycle have shown to be effective in reducing the energy consumption of sensor nodes. However, if not properly tuned, such mechanisms can hinder the data collection process. In this paper, we introduce a Resource-Aware Data Accumulation (RADA), a novel and lightweight framework which allows nodes to learn the MDC arrival pattern, and tune the discovery duty-cycle accordingly. Furthermore, RADA is able to adapt to changes in the operating conditions, and is capable of effectively supporting a number of different MDC mobility patterns. Simulation results show that our solution obtains a higher discovery efficiency and a lower energy consumption than comparable schemes. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:2094 / 2103
页数:10
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