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Sensor and sink placement, scheduling and routing algorithms for connected coverage of wireless sensor networks

机译:用于无线传感器网络连接覆盖的传感器和接收器放置,调度和路由算法

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A sensor is a small electronic device which has the ability to sense, compute and communicate either with other sensors or directly with a base station (sink). In a wireless sensor network (WSN), the sensors monitor a region and transmit the collected data packets through routes to the sinks. In this study, we propose a mixed-integer linear programming (MILP) model to maximize the number of time periods that a WSN carries out the desired tasks with limited energy and budget. Our sink and sensor placement, scheduling, routing with connected coverage (SPSRC) model is the first in the literature that combines the decisions for the locations of sinks and sensors, activity schedules of the deployed sensors, and data flow routes from each active sensor to its assigned sink for connected coverage of the network over a finite planning horizon. The problem is NP-hard and difficult to solve even for small instances. Assuming that the sink locations are known, we develop heuristics which construct a feasible solution of the problem by gradually satisfying the constraints. Then, we introduce search heuristics to determine the locations of the sinks to maximize the network lifetime. Computational experiments reveal that our heuristic methods can find near optimal solutions in an acceptable amount of time compared to the commercial solver based Two Phase (TP) method. (C) 2018 Elsevier B.V. All rights reserved.
机译:传感器是一种小型电子设备,具有与其他传感器或直接与基站(接收器)进行感应,计算和通信的能力。在无线传感器网络(WSN)中,传感器监视区域并将收集的数据包通过路由传输到接收器。在这项研究中,我们提出了一种混合整数线性规划(MILP)模型,以最大化WSN在有限的能量和预算下执行所需任务的时间段。我们的接收器和传感器的放置,调度,带连接覆盖的路由(SPSRC)模型是文献中的第一篇,该模型结合了有关接收器和传感器的位置,已部署传感器的活动计划以及从每个活动传感器到其分配的接收器,以在有限的计划范围内连接网络。这个问题是NP难题,即使对于小型实例也很难解决。假设知道汇的位置,我们开发启发式方法,通过逐渐满足约束条件来构造问题的可行解决方案。然后,我们引入搜索启发式方法来确定接收器的位置,以最大化网络寿命。计算实验表明,与基于商业求解器的两相(TP)方法相比,我们的启发式方法可以在可接受的时间内找到最佳解决方案。 (C)2018 Elsevier B.V.保留所有权利。

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