无线传感器网络能量有效监测的Set K覆盖算法
Set K-Cover Algorithms for Energy Efficient Monitoring in Wireless Sensor Networks
摘要：
无线传感器网络（WSNs）是环境监测的有效手段。本文研究了一种在无线传感器网络的能源有效的监测策略，划分成覆盖的传感器，然后激活覆盖迭代循环的方式。这种方法利用了当许多传感器监视单个区域时产生的重叠。我们的工作建立在Slijepcevic和Potterak的“无线传感器网络的功率高效组织”中的先前工作的基础上，该模型首次制定。我们已经设计了三个近似算法的一个变化的设置K-覆盖问题，其目标是分区的传感器到覆盖，使覆盖的数量，包括一个区域，在所有领域的总和，是最大化的。第一种算法是随机化的，并将传感器分区，预期在最佳值的分数1 - 1/e（~.63）内。我们提出了另外两个确定性的近似算法。一种是近似比为1/2的分布式贪心算法，另一种是近似比为1 - 1/e的集中式贪心算法。我们表明，它是NP-完全的，以保证优于15/16的最佳覆盖率，这表明所有三种算法的最佳近似算法的性能。模拟表明，在实践中，确定性算法执行远高于其最坏情况下的界限，始终覆盖超过72%的最佳解决方案所覆盖的。模拟还表明，寿命的增加与传感器之间的重叠量成比例。该算法速度快，易于使用，并根据模拟，显着增加传感器网络的寿命。特别是随机算法似乎相当实用。
英文摘要：
Wireless sensor networks (WSNs) are emerging as an effective means for environment monitoring. This paper investigates a strategy for energy efficient monitoring in WSNs that partitions the sensors into covers, and then activates the covers iteratively in a round-robin fashion. This approach takes advantage of the overlap created when many sensors monitor a single area. Our work builds upon previous work in "Power Efficient Organization of Wireless Sensor Networks" by Slijepcevic and Potkonjak, where the model is first formulated. We have designed three approximation algorithms for a variation of the SET K-COVER problem, where the objective is to partition the sensors into covers such that the number of covers that include an area, summed over all areas, is maximized. The first algorithm is randomized and partitions the sensors, in expectation, within a fraction 1 - 1/e (~.63) of the optimum. We present two other deterministic approximation algorithms. One is a distributed greedy algorithm with a 1/2 approximation ratio and the other is a centralized greedy algorithm with a 1 - 1/e approximation ratio. We show that it is NP-Complete to guarantee better than 15/16 of the optimal coverage, indicating that all three algorithms perform well with respect to the best approximation algorithm possible. Simulations indicate that in practice, the deterministic algorithms perform far above their worst case bounds, consistently covering more than 72% of what is covered by an optimum solution. Simulations also indicate that the increase in longevity is proportional to the amount of overlap amongst the sensors. The algorithms are fast, easy to use, and according to simulations, significantly increase the longevity of sensor networks. The randomized algorithm in particular seems quite practical.
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