A slot assignment algorithm based on nodes' residual energy

Authors:
Qianping Wang;Xiang Xu;Jin Liu;Liangyin Wang
Affiliations:
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China;School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China;School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China;School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China
Venue:
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
Year:
2012

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Abstract

Aiming to extend the network lifespan through balancing the energy consumption, an EDRAND (Enhanced DRAND) algorithm based on the node's residual energy is presented in this paper. The EDRAND can be considered as an improved DRAND in which slot sizes are determined by the residual energy of sensor nodes. By taking into account of the nodes' residual energy and the network traffic, an E-ZMAC (Energy-ZMAC) protocol which employs energy control and traffic adaptive mechanism in the Z-MAC protocol, is introduced. In the presented protocol, a node in the network will switch to sleep mode for a while within its slot to reduce power consumption and network traffic. The time span in the sleep mode of a node will be shortened with the growth of the network traffic. A node will switch to TDMA mode when the network traffic reaches a certain upper bound. By doing so, the channel access mode is enabled to transit smoothly from competition-based to scheduling-based. In the presented methodology, the contention window size will be increased with the growth of the network traffic, and the backoff span will be negatively related to the amount of residual energy. To validate the presented approach, a group of simulations are conducted in NS2 under different scenarios. The simulation results have demonstrated that the proposed E-ZMAC protocol outperforms Z-MAC protocol in terms of network lifespan, throughput and energy consumption.