Xuxun Liu, Xinyuan Zeng, Junyu Ren, Song Yin, Huan Zhou
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引用次数: 0
Abstract
Connectivity restoration is essential for ensuring continuous operation in wireless sensor networks (WSNs). However, existing works lack enough network robustness when suffering from the secondary external damages. In this paper, we propose a novel connectivity restoration scheme to address this problem. This scheme comprises three connectivity mechanisms regarding relay segment selection in different regions. The first one is a data traffic decentralization mechanism, which establishes more transmission paths near the sink for reliability improvement and traffic load balancing. The second one is a segment shape selection mechanism, in which the segments with high-reliability preferably become the relay segments for greater network robustness. The third one is a traffic load transfer mechanism, in which data traffic is transferred from a high-load segment to a low-load segment for balancing energy depletion of the network. The distinctive characteristics of this work are twofold: different regions perform diverse connectivity restoration approaches according to the demand diversity of different regions, and traffic load can be balanced from upstream regions rather than only from downstream regions. Extensive simulation experiments validate the effectiveness and advantages of our proposed scheme in terms of connection cost, network robustness, load balance degree, and network longevity.
期刊介绍:
ACM Transactions on Sensor Networks (TOSN) is a central publication by the ACM in the interdisciplinary area of sensor networks spanning a broad discipline from signal processing, networking and protocols, embedded systems, information management, to distributed algorithms. It covers research contributions that introduce new concepts, techniques, analyses, or architectures, as well as applied contributions that report on development of new tools and systems or experiences and experiments with high-impact, innovative applications. The Transactions places special attention on contributions to systemic approaches to sensor networks as well as fundamental contributions.