Minimum-delay energy-efficient source to multisink routing in wireless sensor networks

  • Authors:

  • Shun-Yu Chuang;Chien Chen;Chang-Jie Jiang

  • Affiliations:

  • Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan;Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu 300, Taiwan

  • Venue:
  • Signal Processing
  • Year:
  • 2007

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Abstract

This paper proposes a simple and scalable approach to multisink routing scheme in wireless sensor networks. Wireless sensor network is a rapidly growing discipline, with new technologies emerging and new applications under development. In addition to providing light and temperature measurements, wireless sensor nodes have applications such as security surveillance, environmental monitoring, and wildlife watching. One potential problem in a sensor network is how to transmit packets efficiently from single-source to multi-sinks, i.e., to gather data from a single sensor node and deliver it to multiple clients who are interested in the data. The difficulty of such a scenario is finding the minimum-cost multiple transmission paths. Many routing algorithms have been proposed to solve this problem. Most current algorithms address the reduction of power consumption, and potentially introduce a large delay. This paper proposes a novel multi-path routing algorithm, called hop count based routing (HCR) algorithm, which considers energy cost and transmission delay simultaneously. A hop count vector (HCV) is introduced to support routing decision. Moreover, an additional pruning vector (PV) can further enhance routing performance. The proposed algorithm also provides a maintenance mechanism to handle the consequence of faulty nodes. A failure of a node leads to an inaccurate HCV. Therefore, an efficient correction algorithm is necessary. An Aid-TREE (A-TREE) is applied to facilitate restricted flooding. This correction mechanism is more efficient than full-scale flooding for correcting the limited inaccurate HCVs. Finally, the impact of failed nodes is studied, and an algorithm, called Lazy-Grouping, is proposed to enhance the robustness of HCR.