Suyoung Yoon
Abstract
Time synchronization is a fundamental middleware service for any distributed system. Wireless sensor networks make extensive use of synchronized time in many contexts (e.g., data fusion, TDMA schedules, synchronized sleep periods, etc.). We propose a time synchronization method relevant for wireless sensor networks. The solution features minimal complexity in network bandwidth, storage as well as processing, and can achieve good accuracy. Especially relevant for sensor networks, it also provides tight, deterministic bounds on offset and clock drift. A method for synchronizing the entire network is presented. The performance of the algorithm is analyzed theoretically and validated on a realistic testbed. The results show that the proposed algorithm outperforms existing algorithms in terms of precision and resource requirements.
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Index Terms
- Tiny-sync: Tight time synchronization for wireless sensor networks
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Reviews
William W. Oblitey
Wireless sensor networks (WSNs) require time synchronization to provide accurate estimations of the times that the base stations sense data. This paper presents two closely related algorithms for pairwise time synchronization of WSN applications. In the algorithms, one node determines the tight bounds of the relative offset and the drift of its clock, with respect to that of the other node. The paper discusses the development and performance evaluation of the two algorithms, which deliver accurate offset and drift information with tight bounds on them. The authors present and discuss the salient points of their experimental environment, used to measure the performance of their time synchronization protocol. They then discuss the expected performances of the two algorithms, and provide proofs of the theorem on which the algorithms are based. A scheme that builds on the algorithms and is capable of synchronizing the clocks of an entire sensor field is also presented. The paper is well presented, with a careful discussion of the authors' results. The authors discuss the performance of their algorithms based on the assumptions that they made. They then remove the claims of the assumptions in order to show the robustness of the algorithms. Online Computing Reviews Service
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