Please use this identifier to cite or link to this item: https://doi.org/10.1109/MILCOM.2007.4455260
Title: Optimizing application performance through learning and cooperation in a wireless sensor network
Authors: Yeow, W.-L.
Thamt, C.-K. 
Wong, W.-C. 
Issue Date: 2007
Source: Yeow, W.-L.,Thamt, C.-K.,Wong, W.-C. (2007). Optimizing application performance through learning and cooperation in a wireless sensor network. Proceedings - IEEE Military Communications Conference MILCOM : -. ScholarBank@NUS Repository. https://doi.org/10.1109/MILCOM.2007.4455260
Abstract: A wireless sensor network performing surveillance in time-critical missions involving event or target tracking demands accurate ground information be delivered within a delay guarantee. Present methods solve this by using innetwork fusion across all packets to reduce network load in the hope of achieving the delay guarantee. In this paper, we aim to maximize data quality from sensor fusion, while still respecting delay guarantees. The proposed method makes admission control and routing decisions using a fully distributed algorithm based on constrained Markov Decision Processes (MDPs). Cooperation is enforced through welldefined rewards and leading nodes. Assessment of data quality is derived from likelihood ratio, which is a commonly used metric in sensor fusion. We study the performance of the proposed algorithm through extensive simulations, and show that it can achieve soft delay guarantees and good data quality compared to other schemes. © 2007 IEEE.
Source Title: Proceedings - IEEE Military Communications Conference MILCOM
URI: http://scholarbank.nus.edu.sg/handle/10635/71324
ISBN: 1424415136
DOI: 10.1109/MILCOM.2007.4455260
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