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Back-Off Time Calculation Algorithms in WSN

1
Department of Communication Engineering, University of Duisburg-Essen, Duisburg 47057, Germany
2
Department of Computer Science, German University of Technology in Oman, Muscat 111, Oman
3
Department of Computer Science, University of Koblenz, Koblenz 56070, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Antony Bryant
Informatics 2016, 3(2), 9; https://doi.org/10.3390/informatics3020009
Received: 4 March 2016 / Revised: 16 May 2016 / Accepted: 12 June 2016 / Published: 22 June 2016
In a Mobile Wireless Sensor Mesh Network (MWSMN), based on the IEEE 802.15.4 standard, low power consumption is vitally important since the network devices are mostly battery driven. This is especially true for devices dependent on small form factors, such as those used in wireless sensor network. This paper proposes four new approaches to reduce the Back-Off Time in ZigBee standard in order to minimize the collisions caused by transmission between neighbouring nodes within the mesh network. The four alternate algorithms for the Back-Off Time calculation are compared to the ZigBee standard Back-Off Time algorithm regarding their energy needs using the simulation suite OPNET Modeler. To study the behaviour of the parameters of all algorithms in all scenarios, the statistical Analysis of Variance (ANOVA) has been used and it shows that the null hypotheses are rejected except for one case. The results show that the two passive algorithms Tabu Search and Simulated Annealing search techniques are suitable for battery-driven, energy-sensible networks. The Ant Colony Optimization (ACO) approaches increase throughput and reduce the packet loss but cost more in terms of energy due to the implementation of additional control packets. To the best of the authors’ knowledge, this is the first approach for MWSMN that uses the Swarm Intelligence technique and the search solution algorithm for the Back-Off Time optimization. View Full-Text
Keywords: OPNET Modeler; Zigbee; 802.15.4; Tabu Search; Simulated Annealing; Ant Colony Optimization OPNET Modeler; Zigbee; 802.15.4; Tabu Search; Simulated Annealing; Ant Colony Optimization
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MDPI and ACS Style

Al-Humairi, A.; Probst, A. Back-Off Time Calculation Algorithms in WSN. Informatics 2016, 3, 9. https://doi.org/10.3390/informatics3020009

AMA Style

Al-Humairi A, Probst A. Back-Off Time Calculation Algorithms in WSN. Informatics. 2016; 3(2):9. https://doi.org/10.3390/informatics3020009

Chicago/Turabian Style

Al-Humairi, Ali, and Alexander Probst. 2016. "Back-Off Time Calculation Algorithms in WSN" Informatics 3, no. 2: 9. https://doi.org/10.3390/informatics3020009

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