Improved AOW clustering algorithms for wireless self-organized network and performance analysis

In wireless self-organized network (WSON), AOW clustering algorithms can achieve better performance and high adaptability, but having limitations in certain circumstances. In this paper, working procedure and shortcomings of AOW are introduced and analyzed firstly. Then, several modified algorithms based on AOW are designed according to system requirements. Simulation experiments are conducted to compare modified algorithms and original AOW algorithm and simulation results show modified algorithms can improve overall performance of clustering network further in specific scenarios.

[1]  Narottam Chand,et al.  A Distributed Weighted Cluster Based Routing Protocol for MANETs , 2011, Wirel. Sens. Netw..

[2]  Cheng Wei.  A Clustering Algorithm for Mobile Ad-Hoc Network , 2005 .

[3]  Mohammad Reza Meybodi,et al.  Clustering the wireless Ad Hoc networks: A distributed learning automata approach , 2010, J. Parallel Distributed Comput..

[4]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[5]  Peter Han Joo Chong,et al.  An efficient clustering scheme for large and dense mobile ad hoc networks (MANETs) , 2006, Comput. Commun..

[6]  Ameer Ahmed Abbasi,et al.  A survey on clustering algorithms for wireless sensor networks , 2007, Comput. Commun..

[7]  Ravi Prakash,et al.  Max-min d-cluster formation in wireless ad hoc networks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[8]  Anna Gorbenko,et al.  Clustering algorithm in mobile ad hoc networks , 2012 .

[9]  Makoto Takizawa,et al.  A Survey on Clustering Algorithms for Wireless Sensor Networks , 2010, 2010 13th International Conference on Network-Based Information Systems.