Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks

  • Authors:

  • Kai Lin;Chin-Feng Lai;Xingang Liu;Xin Guan

  • Affiliations:

  • School of Computer Science and Engineering, Dalian University of Technology, Liaoning, China;Department of Applied Geoinformatics, Chia Nan University of Pharmacy and Science, Taiwan, China;School of Electrical and Electronic Engineering, Yonsei University of South Korea, Yonsei, Korea;Graduate School of Science and Technology, Keio University, Keio, Japan

  • Venue:
  • Mobile Networks and Applications
  • Year:
  • 2012

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Abstract

For the energy limited wireless sensor networks, the critical problem is how to achieve the energy efficiency. Many attackers can consume the limited network energy, by the method of capturing some legal nodes then control them to start DoS and flooding attack, which is difficult to be detected by only the classic cryptography based techniques with common routing protocols in wireless sensor networks (WSNs). We argue that under the condition of attacking, existing routing schemes are low energy-efficient and vulnerable to inside attack due to their deterministic nature. To avoid the energy consumption caused by the inside attack initiated by the malicious nodes, this paper proposes a novel energy efficiency routing with node compromised resistance (EENC) based on Ant Colony Optimization. Under our design, each node computes the trust value of its 1-hop neighbors based on their multiple behavior attributes evaluation and builds a trust management by the trust value. By this way, sensor nodes act as router to achieve dynamic and adaptive routing, where the node can select much energy efficiency and faithful forwarding node from its neighbors according to their remaining energy and trust values in the next process of data collection. Simulation results indicate that the established routing can bypass most compromised nodes in the transmission path and EENC has high performance in energy efficiency, which can prolong the network lifetime.