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Empirical study of clustering algorithms for wireless ad hoc networks

Tselikis, C., Mitropoulos, S., Douligeris, C. , Ladis, E., Georgouleas, K., Vangelatos, C. & Komninos, N. (2009). Empirical study of clustering algorithms for wireless ad hoc networks. In: 2009 16th International Conference on Systems, Signals and Image Processing, IWSSIP 2009. 16th International Conference on Systems, Signals and Image Processing (IWSSIP 2009), 18 - 20 June 2009, Chalkida, Greece.


In this study we evaluate with experiments three generic clustering algorithms, namely the Lowest-ID, the Highest Degree and the Extended Robust Re-clustering Algorithm which is the one proposed. The aim is to investigate which are the factors that have significant effect on the re-clustering performance. We isolate those performance factors as being network conditions that we simulate with a particular focus on the node deployment pattern, the mobility pattern, the radio transmission range and the energy of the ad hoc nodes. For the evaluation of the re-clustering efficiency and for the comparison of the three algorithms we examined conventional re-clustering performance metrics, such as the cluster head modification rate and the number of the generated clusters but also reliability metrics, such as the cluster head availability probability and the end to end message delivery ratio. We draw generic outcomes that hold for the three algorithms and we also discuss the behavior of the proposed algorithm.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. DOI: 10.1109/IWSSIP.2009.5367771
Subjects: Q Science > QA Mathematics > QA76 Computer software
Departments: School of Science & Technology > Computer Science > Software Reliability
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