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Self-Stabilizing Global Optimization Algorithms for Large Network Graphs.
- Source :
-
International Journal of Distributed Sensor Networks . 2005, Vol. 1 Issue 3/4, p329-344. 16p. - Publication Year :
- 2005
-
Abstract
- The paradigm of self-stabilization provides a mechanism to design efficient localized distributed algorithms that are proving to be essential for modern day large networks of sensors. We provide self-stabilizing algorithms (in the shared-variable ID-based model) for three graph optimization problems: a minimal total dominating set (where every node must be adjacent to a node in the set) and its generalizations, a maximal k-packing (a set of nodes where every pair of nodes are more than distance k apart), and a maxima! strong matching (a collection of totally disjoint edges). [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15501329
- Volume :
- 1
- Issue :
- 3/4
- Database :
- Academic Search Index
- Journal :
- International Journal of Distributed Sensor Networks
- Publication Type :
- Academic Journal
- Accession number :
- 19457687
- Full Text :
- https://doi.org/10.1080/15501320500330745