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提出一种理论优化路由树的启发式算法,实现地理信息辅助的传感器网络服务质量数据收集架构。算法采用群智能蚁群优化机理进行设计:首先通过构造基于流量的能量有效性权将网络划分为不同的功能区域,使得路由的选择过程能够低延时地自适应网内不均衡性的能耗状况;然后,设计了新颖的启发式因子和信息素更新规则,赋予人工蚂蚁代理感知网络局域能量状况和逼近理论优化树的能力,从而提高路由构建的自适应性和能量有效性。仿真实验结果表明,本文提出的路由机制能够在数据收集的应用背景下,有效提高收集质量和降低传输时延,并在健壮性和节能效果方面优于许多经典的传感器网络路由算法。
A heuristic algorithm is proposed to optimize the routing tree to achieve the geographic information aided sensor network QoS data collection architecture. The algorithm uses the swarm intelligence ant colony optimization mechanism to design: First, the network is divided into different functional areas by constructing the traffic-based energy-efficient right, which makes the routing selection process adaptive to the unbalanced energy consumption in the network with low delay Then, we designed novel heuristic factors and pheromone updating rules, which gave the artificial ant agent the ability to perceive the local energy status of the network and approximate the theoretical optimization tree, so as to improve the adaptability and energy efficiency of routing construction. The simulation results show that the routing mechanism proposed in this paper can effectively improve the collection quality and reduce the transmission delay under the application background of data collection, and outperform many classic sensor network routing algorithms in terms of robustness and energy saving effect.