Minimising k-dominating set in arbitrary network graphs

Wang, Guangyuan and Wang, Hua and Tao, Xiaohui and Zhang, Ji and Zhang, Jinhua (2013) Minimising k-dominating set in arbitrary network graphs. In: 9th International Conference on Advanced Data Mining and Applications (ADMA 2013), 14-16 Dec 2013, Hangzhou, China.

Abstract

A self-stabilizing algorithm, after transient faults hit the system and place it in some arbitrary global state, recovers in finite time without external (e.g., human) intervention. A k-dominating set in a distributed system is a set of processors such that each processor outside the set has at least k neighbors in the set. In the past, a few self-stabilizing algorithms for minimal k-dominating set (MKDS) have been obtained. However, the presented self-stabilizing algorithms for MKDS work for either trees or a minimal 2-dominating set. Recently a self-stabilizing algorithm for MKDS in arbitrary graphs under a central daemon has been investigated. But so far, there is no algorithm for the MKDS problem in arbitrary graphs that works under a distributed daemon. In this paper, we propose a self-stabilizing algorithm for finding a MKDS under a distributed daemon model when operating in any general network graph. We further verify the correctness of the proposed algorithm (Algorithm MKDS) and prove that the worst case convergence time of the algorithm from any arbitrary initial state is O(n 2) steps where n is the number of nodes in the network.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2013 Springer-Verlag. Series: Lecture Notes in Computer Science, v8347 pt2. Permanent restricted access to Accepted version due to publisher copyright policy.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 27 May 2014 06:09
Last Modified: 29 Sep 2017 01:51
Uncontrolled Keywords: self-stabilizing algorithm; minimal k-dominating set; distributed daemon model; arbitrary network; convergence
Fields of Research : 10 Technology > 1005 Communications Technologies > 100503 Computer Communications Networks
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1007/978-3-642-53917-6_11
URI: http://eprints.usq.edu.au/id/eprint/25192

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