Energy efficient multiple base stations deployment in wireless sensor networks

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Copyright: Mahmud, Sabbir
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Abstract
Wireless sensor network (WSN) is widely used in various applications ranging from area monitoring, health care monitoring, bush _re detection, to environmental monitoring, agricultural and structural monitoring. In WSNs, sensor nodes, typically battery powered, communicate with each other using radio signals and send the sensed data to a designated base station. In some applications of WSN, several thousands of sensor nodes might be deployed over the monitored region spanning several kilometres. Hence, it is very difficult to replace the batteries of the sensor nodes which are deployed over a large, remote and hostile area. As a result, it is important to save the energy of each sensor node to increase the lifetime of a WSN. In a WSN, each sensor node spends most of its energy on relaying the data of other sensor nodes. Multiple base stations can be deployed to reduce the amount of data, a sensor node needs to relay, thus increase the net- work lifetime. Furthermore, multiple base stations can also reduce the latency of a packet delivery. This thesis studies multiple base stations deployment problems in WSNs, and presents a set of efficient techniques. Firstly, we present a quadratic-time algorithm to optimally place a base station in a WSN so that the total energy consumption of all the sensor nodes is minimized. Given a cluster of sensor node m, the time complexity of the algorithm is O(m2). We also propose a heuristic algorithm to evenly distribute energy consumptions of all the clusters of a WSN. Secondly, we propose a 2-approximation algorithm for minimizing the shortest hop distance from all the sensor nodes to the designated base stations in order to deploy k base stations in a WSN. For a single base station, we present an optimal algorithm for finding the optimal location of the base station. We also propose a modified version of our previous heuristics for balancing clusters of sensors and show the simulation results of 2-approximation algorithm and the heuristics on 171 instances of different distributions. The simulation results show that the cluster balancing heuristics performs significantly better than the 2- approximation algorithm. Lastly, we present two polynomial time heuristics for multiple base station deployment problems. In case of a single base station, we propose the first polynomial time algorithm for optimally placing a static base station in a cluster of sensor node to maximize the cluster's lifetime, and a heuristic for deploying a mobile base station in a cluster of sensor node to increase the cluster's lifetime.
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Author(s)
Mahmud, Sabbir
Supervisor(s)
Wu, Hui
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Publication Year
2015
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
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