A distributed rate allocation algorithm for Slepian-Wolf coding based data aggregation in wireless sensor networks

Jun Zheng, Zhenzhong Huang, Qihuang Shu, N. Mitton
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Abstract

This paper considers the Slepian-Wolf coding based energy-minimization rate allocation problem in a wireless sensor network (WSN) and propose a distributed rate allocation algorithm to solve the problem. The proposed distributed algorithm is based on an existing centralized rate allocation algorithm which has a high computational complexity. To reduce the computational complexity of the centralized algorithm and make the rate allocation performable in a distributed manner, we make necessary modifications to the centralized algorithm by reducing the number of sets in calculating the average energy consumption cost and limiting the number of conditional nodes that a set can use. Simulation results show that the proposed distributed algorithm can significantly reduce the computational time when compared with the existing centralized algorithm at the cost of the overall energy consumption for data transmission and the total amount of data transmitted in the network.
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基于睡眠狼编码的无线传感器网络数据聚合的分布式速率分配算法
研究了无线传感器网络中基于睡眠狼编码的能量最小速率分配问题,提出了一种分布式速率分配算法来解决该问题。该分布式算法是在现有的集中式速率分配算法的基础上提出的,该算法的计算复杂度较高。为了降低集中式算法的计算复杂度,使速率分配能够以分布式的方式执行,我们对集中式算法进行了必要的修改,减少了计算平均能耗成本的集合数,限制了一个集合可以使用的条件节点数。仿真结果表明,与现有的集中式算法相比,本文提出的分布式算法可以显著减少计算时间,但代价是数据传输的总体能耗和网络中传输的数据总量。
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