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|Title: ||Stability-aware multi-metric clustering in mobile ad hoc networks with group mobility|
|Authors: ||Cheng, H|
|Keywords: ||Mobile ad hoc networks|
|Publication Date: ||2009|
|Publisher: ||John Wiley & Sons|
|Citation: ||Wireless Communications and Mobile Computing, 9(6): 759 - 771, Jun 2009|
|Abstract: ||Clustering can help aggregate the topology information and reduce the size of routing tables in a mobile ad hoc network (MANET). The maintenance of the cluster structure should be as stable as possible to reduce overhead and make the network topology less dynamic. Hence, stability measures the goodness of clustering. However, for a complex system like MANET, one clustering metric is far from reflecting the network dynamics. Some prior works have considered multiple metrics by combining them into one weighted sum, which suffers from intrinsic drawbacks as a scalar objective function to provide solution for multi-objective optimization. In this paper, we propose a stability-aware multi-metric clustering algorithm, which can (1) achieve stable cluster structure by exploiting group mobility and (2) optimize multiple metrics with the help of a multi-objective evolutionary algorithm (MOEA). Performance evaluation shows that our algorithm can generate a stable clustered topology and also achieve optimal solutions in small-scale networks. For large-scale networks, it outperforms the well-known weighted clustering algorithm (WCA) that uses a weighted sum of multiple metrics.|
|Description: ||This article can be obtained from the link below - Copyright @ 2008 John Wiley & Sons, Ltd.|
|Sponsorship: ||This work was supported in part by the UGC of Hong Kong under the CERG grant PolyU5170/03E, by the Engineering and Physical Sciences Research Council (EPSRC) of U.K. under Grant EP/E060722/1, by the National High-Tech Research and Development Plan of China under Grant No. 2006AA01Z214; the National Natural Science Foundation of China under Grant No. 60673159 and 70671020.|
|Appears in Collections:||Publications|
Dept of Computer Science Research Papers
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