Back-Off Time Calculation Algorithms in WSN

Abstract

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.

Keywords

• OPNET Modeler
• Zigbee
• 802.15.4
• Tabu Search
• Simulated Annealing
• Ant Colony Optimization