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A Partition-based Energy-Efficient Strategy for Deadline-based Data Collection in Wireless Sensor Networks

[ Vol. 8 , Issue. 2 ]

Author(s):

Ravi Babu*, Udaya Kumar K. Shenoy and Kiran Kumari Patil   Pages 109 - 121 ( 13 )

Abstract:


Background & Objective: Several studies have revealed that mobile sinks help in extending the lifetime of Wireless Sensor Networks (WSNs) by minimizing multihop transmissions. However, prolonging lifetime of WSNs that require all sensed information to be collected within a time limit involves considerable challenges. A proposed framework to gather data in such WSNs is to combine multihop transmissions with a mobile sink that visits only a subset of sensor nodes, as opposed to all nodes. The ability of such an approach to improve network lifetime depends on the tour taken by the mobile sink. Thus, the problem essentially becomes identifying a sink tour no longer than a given constraint such that the tour visits only a subset of sensor nodes. Since the problem of computing the optimal tour is NP-hard, in this paper we propose a partition-based energy-efficient heuristic to address the problem.

Method: The proposed approach computes a subset of sensor nodes to be included in the tour based on their energy consumption rate and hop distance. It operates in an iterative manner, each time identifying the congested part of the network and selecting from that part a node that has the highest rate of energy consumption. The tour computation based on energy consumption rate combined with hop distance ensures a balanced distribution of sensors energy consumption in a WSN. We present an algorithm for the proposed approach, and evaluate the performance of the algorithm through simulations.

Conclusion: The simulations results reveal that the approach considerably improves network lifetime.

Keywords:

Data collection, energy-hole problem, lifetime maximization, mobile sink, multihop transmission, rendezvous point, sensor node, wireless sensor network.

Affiliation:

Department of Computer Science, REVA University, Bangalore, Department of Computer Science, NMAM Institute of Technology, Nitte University, Mangalore, School of Computing and IT, REVA University, Bangalore

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