Cooperative and Forwarding Hybrid Routing Algorithm for Network Lifetime Maximization in Wireless Sensor Network
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    Abstract:

    Periodic monitoring and many-to-one data transmission is one of the representative scenarios in wireless sensor networks where inherent uneven energy consumption problem exists, that is nodes with different distances away from sink have different energy consumptions and it seriously reduces network lifetime. A routing algorithm is proposed based on cooperative and forwarding hybrid transmission modes, which utilizes the complementary characteristic in energy consumption of cooperative and forwarding transmission over long and short distance, and balances nodes' energy consumption through tuning the traffic ratio transmit by non-cooperative mode (referred to as relay ratio). Network lifetime maximization (NLM) is modeled as optimization of relay ratio vector, which is a high order non-linear optimization problem of multiple variables. To solve this problem, theoretical analysis is carried out on node energy consumption when network lifetime is maximized and an important conclusion is reached: if bit-energy-consumption of forwarding mode is lower than that of cooperative mode of sink's one-hop neighbor, all nodes have equal energy consumption when network lifetime is maximized; otherwise, only nodes whose bit-energy-consumption of cooperative mode is higher than that of forwarding mode have equal energy consumptions. As a result, NLM, a high order non-linear optimization problem, is simplified into an optimization about single variable. A distributed optimal relay ratio based routing algorithm (DORRCR) is designed based on the theoretical analysis. Simulation shows that, DORRCR prolongs network lifetime greatly compared with pure cooperative and non-cooperative energy balance routing protocols and evidently balances energy balance over the whole network.

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张霞,周刚,于宏毅.一种协作和中继混合的传感网寿命最大化路由算法.软件学报,2013,24(12):2859-2870

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History
  • Received:February 06,2012
  • Revised:September 12,2012
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  • Online: December 04,2013
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