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Issue No. 01 - June (2013 vol. 1)
ISSN: 2168-6750
pp: 98-110
Xi Deng , Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
Yuanyuan Yang , Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA
A reliable, scalable, and low-delay information collection network is an essential component in cyber-physical systems (CPS). Cluster-based sensor network is a good candidate because of its advantage in increasing scalability, improving energy efficiency, and providing QoS guarantees. However, in such networks, frequent interactions between the intra-cluster communication and the inter-cluster communication are inevitable, which may severely downgrade the communication efficiency and hence the network performance if not handled properly. Proper synchronization among these two types of communications is required. In this paper, we propose two approaches to schedule the communications in clustered wireless sensor networks aiming at delay-sensitive applications. In the first approach, an efficient cycle-based synchronous scheduling is proposed to achieve low average packet delay and high throughput by optimizing the cycle length and transmission order. In the second approach, a novel clustering structure is introduced to eliminate the necessity of communication synchronization so that packets are transmitted with no synchronization delay, yielding very low end-to-end packet delay. Our extensive experimental results demonstrate the superior performance of both the approaches. These two approaches are then integrated as a hybrid scheme that allows smooth switching between them. The hybrid scheme takes advantage of both the approaches and enables cluster-based sensor networks to serve as the fundamental network infrastructure for information collection in CPS.
Communication networks, Wireless sensor networks, Synchronization, Scheduling, Optimal scheduling, Time division multiple access

X. Deng and Y. Yang, "Communication Synchronization in Cluster-Based Sensor Networks for Cyber-Physical Systems," in IEEE Transactions on Emerging Topics in Computing, vol. 1, no. 1, pp. 98-110, 2013.
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