On the performance of sensor node repositioning under realistic terrain constraints

I. Senturk, K. Akkaya
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引用次数: 5

Abstract

Node mobility has been exploited in many context of Mobile Sensor Networks (MSNs) and Wireless Sensor and Actor Networks (WSANs) to improve network performance. In particular, network partitioning due to node failures has been addressed via repositioning of some of the mobile nodes. In all of these studies, the application terrain is assumed to be obstacle free and the movements are performed by following the direct path from the source to destination. However, in reality, this is not the case since the terrains would not be obstacle free and the nodes cannot move freely and smoothly to every requested location. The terrain type, elevation as well as the obstacles should be taken into account before the nodes start moving. In this paper, we claim that most of the existing approaches would either not work or produce wrong results if realistic assumptions regarding the terrain are not considered. To demonstrate our claims regarding the mobility issues, we consider two of the existing heuristics on the connectivity restoration problem in disjoint MSNs. Rather than following the direct path for movement as done in these works, we propose to use a path planning algorithm for determining the least-cost path in terms of energy consumption. In the experiments, we simulate several varieties of terrain types, obstacles and elevations in the region. Simulation results indicate that the movement cost is significantly higher and this should be taken into account to redesign the existing approaches.
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真实地形约束下传感器节点重定位性能研究
在移动传感器网络(msn)和无线传感器和行动者网络(wsan)的许多环境中,节点移动性被用来提高网络性能。特别是,通过重新定位一些移动节点,解决了节点故障导致的网络分区问题。在所有这些研究中,假设应用地形是无障碍物的,并且运动是沿着从源到目的地的直接路径进行的。然而,在现实中,情况并非如此,因为地形不是无障碍的,节点不能自由平稳地移动到每个请求的位置。在节点开始移动之前,地形类型、海拔以及障碍物都应该考虑进去。在本文中,我们声称,如果不考虑有关地形的现实假设,大多数现有方法要么不起作用,要么产生错误的结果。为了证明我们关于移动性问题的主张,我们考虑了两种现有的关于不连接的msn中连通性恢复问题的启发式方法。我们建议使用路径规划算法来确定能量消耗方面成本最低的路径,而不是像这些作品中那样遵循直接的移动路径。在实验中,我们模拟了该地区几种不同的地形类型、障碍物和海拔。仿真结果表明,移动成本明显较高,在对现有方法进行重新设计时应考虑到这一点。
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