Coverage by directional sensors in randomly deployed wireless sensor networks
Coverage by directional sensors in randomly deployed wireless sensor networks
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DOI：
10.1007/s10878-006-5975-x
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发表时间：
2006-02-01
影响因子：
1
通讯作者：
Abouzeid, AA
中科院分区：
文献类型：
--
作者：
Ai, J;Abouzeid, AA
研究了一组离散目标上具有可调方位的“定向传感器覆盖”问题。提出了一种最小传感器最大覆盖(MCMS)问题，在该问题中，覆盖的目标数目最大化，而激活的传感器数目最少。我们给出了它的精确整数线性规划(ILP)公式和一个近似(但计算效率高)的集中式贪婪算法(CGA)解。这些集中解决方案用作比较基准。然后给出了一种分布式贪婪算法(DGA)的解决方案。通过在DGA中加入传感器剩余能量的度量，我们进一步提出了一种在更大时间尺度上执行自适应调度的感知邻域协作休眠(SNCS)协议。最后，我们通过大量的模拟评估了所提出的解决方案和协议在提供覆盖和最大化网络寿命方面的性能。此外，对于圆形覆盖的情况，我们将其与现有最著名的覆盖算法进行了比较。
We study a novel "coverage by directional sensors" problem with tunable orientations on a set of discrete targets. We propose a Maximum Coverage with Minimum Sensors (MCMS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the number of sensors to be activated is minimized. We present its exact Integer Linear Programming (ILP) formulation and an approximate (but computationally efficient) centralized greedy algorithm (CGA) solution. These centralized solutions are used as baselines for comparison. Then we provide a distributed greedy algorithm (DGA) solution. By incorporating a measure of the sensors residual energy into DGA, we further develop a Sensing Neighborhood Cooperative Sleeping (SNCS) protocol which performs adaptive scheduling on a larger time scale. Finally, we evaluate the properties of the proposed solutions and protocols in terms of providing coverage and maximizing network lifetime through extensive simulations. Moreover, for the case of circular coverage, we compare against the best known existing coverage algorithm.