Electrical Engineering
Permanent URI for this collectionhttps://hdl.handle.net/10735.1/2573
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Browsing Electrical Engineering by Author "Basagni, Stefano, 1965-"
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Item Distributed and mobility-adaptive clustering for ad hoc networks(The University of Texas at Dallas, 2013-04-18) Basagni, Stefano, 1965-; Eric Jonsson School of Engineering and Computer ScienceA distributed algorithm is presented that partitions the nodes of a fully mobile network (ad hoc network) into clusters, thus giving the network a hierarchical organization. The algorithm is proven to be adaptive to changes in the network topology due to nodes' mobility and to nodes addition/removal. A new weight-based mechanism is introduced for the efficient cluster formation/maintenance that allows the cluster organization to be configured for specific applications and adaptive to changes in the network status, not available in previous solutions. Simulation results are provided that demonstrate up to an 85% reduction on the communication overhead associated with the cluster maintenance with respect to clustering algorithms previously proposed.Item On the complexity of clustering multi-hop wireless networks(The University of Texas at Dallas, 2013-04-18) Basagni, Stefano, 1965-; Eric Jonsson School of Engineering and Computer ScienceA Distributed Clustering Algorithm (DCA) is presented that partitions the nodes of a fully mobile network (multi-hop network) into clusters, thus giving the network a hierarchical organization. Nodes are grouped by following a new weight-based criterium that allows the choice of the nodes that coordinate the clustering process based on node mobility-related parameters. The DCA time complexity is proven to be bounded by a network parameter Db that depends on the possibly changing topology of the network rather than on its size, i.e., the invariant number of the network nodes. Simulation results are given which demonstrate that in a mobile scenario Db-and thus the DCA time complexity-is logarithmic in the size of the network. This result improves exponentially a previously known upper bound on the time complexity of distributed clustering for multi-hop wireless networks.