Performance of Wireless Sensor Networks for Different Mobile Event Path Scenarios

Performance of Wireless Sensor Networks for Different Mobile Event Path Scenarios

Tao Yang (Fukuoka Institute of Technology, Japan), Gjergji Mino (Fukuoka Institute of Technology, Japan), Leonard Barolli (Fukuoka Institute of Technology, Japan), Makoto Ikeda (Seikei University, Japan), Fatos Xhafa (Technical University of Catalonia, Spain) and Arjan Durresi (Indiana University-Purdue University Indianapolis (IUPUI), USA)
Copyright: © 2011 |Pages: 15
DOI: 10.4018/jdst.2011070104
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Abstract

In this paper, the authors investigate how the sensor network performs when the event moves with special movement path. Simulation results are compared with four scenarios: when the event is stationary, moving randomly, moving with simple 4 path, and boids path. The simulation results show that for the case when the event is moving randomly, the performance is the worst in the four scenarios. The characteristic of goodput decreases with the increase of number of sensor nodes. In the case of the boids model, the goodput is unstable when the is lower than 10 pps. The consumed energy characteristic increases with the increase of . Simulation results show that the consumed energy of random movement is the worst among the four scenarios. The consumed energy of boids model is the lowest in four cases. This shows that the event movement with boids model can decrease the consumed energy in large scale WSNs.
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Proposed Network Simulation Model

In our WSN, every node detects the physical phenomenon and sends back to the sink node the data packets. We suppose that the sink node is more powerful than sensor nodes. In our previous work, the event node was stationary. In this work, we consider that the event moves with special movement path. We analyze the performance of the network in a fixed time interval. This is the available time for the detection of the phenomenon and its value is application dependent. Proposed network simulation model is shown in Figure 1.

Figure 1.

Proposed network simulation model

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