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Dynamic state-based routing for load balancing and efficient data gathering in wireless sensor networks

机译:基于动态状态的动态路由,可在无线传感器网络中实现负载平衡和高效的数据收集

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We consider the online data gathering problem in wireless sensor networks and examine the key issues of load balancing the nodes to achieve longer network lifetime, and that of load balancing the network links to achieve greater reliability in the network. We model the given network as a shortest-path DAG D, which defines a set of parent nodes for each node that determine the minimum-hops paths from the node to a sink. Data gathering in D is accomplished using a dynamic routing approach, where each node selects a parent using a parent selection function σ to forward the sensed data. We investigate a dynamic state-based routing approach where σ is defined using the current state of the network and propose two routing algorithms — MPE Routing and WPE Routing, that aim to load balance the nodes as well as the edges of D. Load balancing the nodes achieves longer network lifetime while load balancing the edges yields greater disjointness and thus greater reliability and trust in the network. Our simulation results show that our algorithms perform consistently better than our benchmark algorithms and other existing data gathering schemes with respect to our three goodness measures — network lifetime, nodal load balancing and disjointness.
机译:我们考虑了无线传感器网络中的在线数据收集问题,并研究了如何对节点进行负载平衡以实现更长的网络寿命,以及对网络链路进行负载平衡以实现更高的网络可靠性的关键问题。我们将给定网络建模为最短路径DAG D,该DAG D为每个节点定义了一组父节点,这些父节点确定了从节点到接收器的最小跳跃路径。 D中的数据收集是使用动态路由方法完成的,其中每个节点都使用父级选择函数σ选择一个父级,以转发感测到的数据。我们研究了一种动态的基于状态的路由方法,其中σ是使用网络的当前状态定义的,并提出了两种路由算法-MPE路由和WPE路由,旨在平衡节点和D的边缘。节点可实现更长的网络寿命,而边缘的负载平衡则会产生更大的不连贯性,从而提高网络的可靠性和信任度。我们的仿真结果表明,就网络寿命,节点负载平衡和不连续性这三个方面而言,我们的算法在性能上始终优于基准算法和其他现有数据收集方案。

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