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Distributed Minimum-Cost Clustering for Underwater Sensor Networks

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Presentation on theme: "Distributed Minimum-Cost Clustering for Underwater Sensor Networks"— Presentation transcript:

1 Distributed Minimum-Cost Clustering for Underwater Sensor Networks
Pu Wang, Cheng Li, Jun Zheng, Distributed Minimum-Cost Clustering Protocol for UnderWater Sensor Networks (UWSNs), IEEE International Conference on Communications (ICC '07), pp , June 24-28, 2007. Presented By Donghyun Kim January 15, Mobile Computing and Wireless Networking Research Group at University of Texas at Dallas

2 Target Underwater Sensor Network (USN) Structure
A (normally 2D, static) USN normally consists of Underwater sensor nodes One or more UnderWater Sinks (UW-Sinks) One or more out-of-water sinks (Out-of-water sink or station) On-shore station Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

3 Architecture for 2D USNs
(Image Source: ) Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

4 Special Requirements for Minimum Cost Clustering in USNs
Every node is a cluster head candidate (like 1-tier clustering) Three cost metrics The total energy consumption of the cluster members for sending data to the cluster head The residual energy of the cluster head and its cluster members The relative location between the cluster head and the UW-Sink (2-tier clustering?) Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

5 Network Model and Assumptions
Homogeneous ocean bottom sensor nodes Each node can adjust its transmission range with transmission power control A UW-Sink is connecting sensor nodes to a out-of-water sink (an on-shore control center) This paper assumes only one fixed UW- Sink Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

6 Notations is the set of sensor nodes in a given USN.
is the set of node within ’s cluster diameter (1-hop neighbors) is the cardinality of ’s is the powerset of can form a potential cluster (1- hop) There can be potential clusters. is the cluster set which consists of all the potential clusters in the network Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

7 Minimum-Cost Node Clustering (MCNC) Problem
A Cluster-Centric Cost-based Formulation Objective: Improve the energy efficiency and prolong the lifetime of the network Select a set of potential clusters to cover the whole network so that the overall cost of all selected clusters is minimized, i.e where and Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

8 Cost Metric Cluster cost (cost for a potential cluster)
The total energy consumption of the cluster members for sending data to the cluster head The relative location between the cluster head and the (nearest) UW-Sink The residual energy of the cluster head and its cluster members Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

9 Cost Metric – cont’ Given a potential cluster ,where is a clusterhead candidate and is a cluster member set of , the cluster cost of cluster is defined as where is the total energy consumed by all sensor nodes in for sending one data packet to (also called intra-cluster cost) is the energy consumed by for sending one data packet to the uw-sink directly (Euc. distance / data aggregator). Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

10 Cost Metric – cont’ To more comprehensively reflect the dynamic energy status of the cluster, the residual energy of the cluster head and its cluster members should also be considered Idea Initially, the cost function is dominated by energy consumption When the residual energy of the clusterhead candidate becomes small, the residual energy tem dominates the cost function Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

11 Cost Metric – cont’ Final cost function
where (or ) is the residual energy of node (or ) normalized by the initial energy of the node and Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

12 Distributed Minimum-Cost Clustering Algorithm (MCCA)
MCNC is very similar to the Minimum Weight Set Cover (MWSC) problem In MWSC, a point can be covered multiple times, while in MCNC, it has to be covered by only one cluster Chvatal’s Algorithm for MWSC (in 1979) Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

13 Distributed Minimum-Cost Clustering Algorithm (MCCA) – cont’
Proposed Algorithm Presented by Donghyun Kim on January 15, Mobile Computing and Wireless Networking Research Group at The University of Texas at Dallas

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