Self-optimized collaborative data communication in wireless sensor networks

OC '11 Pub Date : 2011-06-18 DOI:10.1145/1998642.1998648
B. Banitalebi, Takashi Miyaki, H. Schmidtke, M. Beigl
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引用次数: 5

Abstract

Collaborative data communication is one of the efficient approaches in wireless sensor networks (WSN) in terms of life-time, reliability and quality of service (QoS) enhancement. In this paper, we propose a new self-optimized collaborative algorithm which minimizes the energy consumption by decreasing the number of collaborative nodes and at the same time guarantees the demanded quality. To do this, we focus on the fact that during the collaboration, a receiver node aggregates the signals of the collaborative nodes separately. The major task of this node is the time adjustment of the collaborative nodes to receive their signals synchroneously. The proposed algorithm performs an extra process to sort the aggregated signals based on their bit error rate (BER) as the quality and select the minimum number of the nodes with higher rank for collaboration. It is because the low quality signals have negative effect on the collaboration performance, as confirmed experimentally. The new algorithm gains higher level of energy storage balance without increasing of the inter-node communications or computational load by modification of the node selection metric. It also guarantees the demanded QoS through modification of the collaboration based on the signal quality at the destination which results in higher reliability. Based on the proposed algorithm, sensor nodes can gain the optimum efficiency during collaborative data communication without external management resources. The algorithm is applicable in various scenarios and network structures.
无线传感器网络中的自优化协同数据通信
协作数据通信是提高无线传感器网络寿命、可靠性和服务质量的有效途径之一。在本文中,我们提出了一种新的自优化协同算法,该算法通过减少协作节点的数量来最小化能耗,同时保证所需的质量。为此,我们关注这样一个事实,即在协作过程中,接收节点分别聚合协作节点的信号。该节点的主要任务是调整协作节点的时间,使其同步接收信号。该算法以误码率(BER)为质量对聚合信号进行排序,并选择最小数量的高秩节点进行协作。实验证实,低质量的信号会对协作性能产生负面影响。该算法通过修改节点选择度量,在不增加节点间通信和计算负荷的前提下,获得了更高水平的储能平衡。它还根据目的地的信号质量对协作进行修改,从而保证了所需的QoS,从而提高了可靠性。基于该算法,传感器节点在不需要外部管理资源的情况下,可以获得最佳的协同数据通信效率。该算法适用于各种场景和网络结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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