Game balanced multi-factor multicast routing in sensor grid networks

Fan, Qingfeng, Xiong, Naixue, Zeitouni, Karine, Wu, Qiongli, Vasilakos, Athanasios, & Tian, Yu-Chu (2016) Game balanced multi-factor multicast routing in sensor grid networks. Information Sciences, 367-368, pp. 550-572.

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In increasingly important sensor grid networks, multicast routing is widely used in date aggregation and distributed query processing. It requires multicast trees for efficient data transmissions. However, sensor nodes in such networks typically have limited resources and computing power. Efforts have been made to consider the space, energy and data factors separately to optimize the network performance. Considering these factors simultaneously, this paper presents a game balance based multi-factor multicast routing approach for sensor grid networks. It integrates the three factors into a unified model through a linear combination. The model is standardized and then solved theoretically by using the concept of game balance from game theory. The solution gives Nash equilibrium, implying a well balanced result for all the three factors. The theoretic results are implemented in algorithms for cluster formation, cluster core selection, cluster tree construction, and multicast routing. Extensive simulation experiments show that the presented approach gives mostly better overall performance than benchmark methods.

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ID Code: 97818
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Game balance, multicast, query, semantic cache, sensor grid networks
DOI: 10.1016/j.ins.2016.06.049
ISSN: 0020-0255
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Distributed and Grid Systems (080501)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Networking and Communications (080503)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 Elsevier
Copyright Statement: Licensed under the Creative Commons Attribution; Non-Commercial; No-Derivatives 4.0 International. DOI: 10.1016/j.ins.2016.06.049
Deposited On: 01 Aug 2016 01:15
Last Modified: 07 Aug 2016 05:36

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