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An Energy-Efficient Routing Mechanism Based On Genetic Ant Colony Algorithm for Wireless Body Area Networks

机译:一个基于节能的路由机制遗传蚁群算法的无线的身体区域网络

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As an important branch of Wireless Sensor Network (WSN), Wireless Body Area Network (WBAN) has received extensive attention of various fields as it is portable and removeable. However, energy consumption is highlighting increasingly as nodes are hard to be recharged or replaced. Up to now, many energy efficient routing algorithms or protocols have been proposed with techniques like clustering, data aggregation and location tracking etc. However, many of them aim to minimize parameters like total energy consumption, latency etc. In order to optimize network routing and prolong the life of network, this paper proposes an energy-efficient routing algorithm in WBAN which is based on Genetic Ant Colony Algorithm (GACA). GACA makes full use of Genetic Agorithm (GA) and Ant Colony Algorithm (ACA). Choosing the optimal routing is to take advantages of both GA and ACA. At the early stage of algorithm, it uses GA to generate the initial pheromone distribution quickly and comprehensively, and then converts the evolved pheromones distribution into pheromones that can be used by ACA and finally uses the positive feedback and parallelism of ACA to find out the optimal solution. It is the fusion of the two algorithms, gaining an improvement of both time and quality. Then it reduces and balances energy consumption for all sensor nodes through a Distance-based Energy Aware Routing (DEAR) algorithm in order to prolong the lifetime of network.
机译:作为无线传感器网络的一个重要分支(网络、无线区域网络(WBAN)受到各领域的广泛关注它是便携式和removeable。消费逐渐突出作为节点很难充电或更换。许多节能路由算法与技术协议提出了聚类、数据聚合和位置跟踪等。最小化总能量等参数消费、延迟等。网络路由和延长网络的寿命,本文提出了一种节能的路由算法在WBAN基于遗传蚁蚁群算法(GACA)。遗传Agorithm (GA)和蚁群算法(ACA)。GA和ACA的优点。的算法,它使用遗传算法生成初始信息素分布快速、全面,然后将进化而来的信息素分配到信息素使用ACA最后使用积极的一面反馈和ACA找出的并行性最优的解决方案。算法,获得了一种改进的时间和质量。所有传感器节点通过消费基于距离的能量感知路由(亲爱的)算法以延长的寿命网络。

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