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A General Approach for Minimizing the Maximum Interference of a Wireless Ad-Hoc Network in Plane

机译:最小化平面中无线Ad-Hoc网络最大干扰的通用方法

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The interference reduction is one of the most important problems in the field of wireless sensor networks. Wireless sensor network elements are small mobile receiver and transmitters. The energy of processor and other components of each device is supplied by a small battery with restricted energy. One of the meanings that play an important role in energy consumption is the interference of signals. The interference of messages through a wireless network, results in message failing and transmitter should resend its message, thus the interference directly affect on the energy consumption of transmitter. This paper presents an algorithm which suggests the best subgraph for the input distribution of the nodes in the plane how the maximum interference of the proposed graph has the minimum value. The input of the application is the complete network graph, which means we know the cost of each link in the network graph. Without any lose of generality the Euclidean distance could be used as the weight of each link. The links are arranged and ranked according to their weights, in an iterative process the link which imposition minimum increase on the network interference with some extra conditions which is proposed in future sections, is added to resulting topology and is eliminated from list until all nodes are connected together. Experimental results show the efficiency of proposed algorithm not only for one dimensional known distribution like exponential node chain, but also for two dimensional distributions like two Exponential node chains and alpha-Spiral node chains.
机译:减少干扰是无线传感器网络领域中最重要的问题之一。无线传感器网络元素是小型移动接收器和发射器。处理器和每个设备的其他组件的能量由能量受限的小型电池提供。在能耗中起重要作用的意义之一是信号的干扰。消息通过无线网络的干扰会导致消息失败,并且发送方应重新发送其消息,因此干扰直接影响发送方的能耗。本文提出了一种算法,该算法为平面中节点的输入分布建议了最佳子图,建议的图的最大干扰如何具有最小值。应用程序的输入是完整的网络图,这意味着我们知道网络图中每个链接的成本。不失一般性,欧几里德距离可以用作每个链接的权重。链接根据其权重进行排列和排序,在迭代过程中,将在将来的部分中提出的,对网络干扰施加最小增加并增加一些额外条件的链接添加到生成的拓扑中,并从列表中删除,直到所有节点都被删除为止。连接在一起。实验结果表明,该算法不仅对于一维已知分布(如指数节点链),而且对于二维分布(如两个指数节点链和α-螺旋节点链)的有效性。

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