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A cost minimization algorithm for mobile data gathering in wireless sensor networks

机译:无线传感器网络中用于移动数据收集的成本最小化算法

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Recent studies have shown that significant benefit can be achieved in wireless sensor networks (WSNs) by employing mobile collectors for data gathering via short-range communications. A typical scenario for such a scheme is that a mobile collector roams over the sensing field and pauses at some anchor points on its moving tour such that it can traverse the transmission range of all the sensors in the field and directly collect data from each sensor. In this paper, we study the performance optimization of such mobile data gathering by formulating it into a cost minimization problem constrained by the channel capacity, the minimum amount of data gathered from each sensor and the bound of total sojourn time at all anchor points. We assume that the cost of a sensor for a particular anchor point is a function of the data amount a sensor uploads to the mobile collector during its sojourn time at this anchor point. In order to provide an efficient and distributed algorithm, we decompose this global optimization problem into two subproblems to be solved by each sensor and the mobile collector, respectively. We show that such decomposition can be characterized as a pricing mechanism, in which each sensor independently adjusts its payment for the data uploading opportunity to the mobile collector based on the shadow prices of different anchor points. Correspondingly, we give an efficient algorithm to jointly solve the two subproblems. Our theoretical analysis demonstrates that the proposed algorithm can achieve the optimal data control for each sensor and the optimal sojourn time allocation for the mobile collector, which minimizes the overall network cost. Finally, extensive simulation results further validate that our algorithm achieves lower cost than the compared data gathering strategy.
机译:最近的研究表明,通过使用移动收集器通过短距离通信收集数据,可以在无线传感器网络(WSN)中获得显着的收益。这种方案的典型场景是,移动收集器在感测场上漫游,并在其移动行程中停在某些锚点上,这样它就可以遍历该场中所有传感器的传输范围,并直接从每个传感器收集数据。在本文中,我们通过将这种移动数据收集公式化为成本最小化问题来研究其性能优化,该问题受信道容量,从每个传感器收集的最小数据量以及所有锚点的总停留时间的限制所约束。我们假设特定锚点的传感器成本是传感器在此锚点停留期间向移动收集器上载的数据量的函数。为了提供有效的分布式算法,我们将此全局优化问题分解为两个子问题,分别由每个传感器和移动收集器解决。我们表明,这种分解可以描述为一种定价机制,其中每个传感器根据不同锚点的影子价格独立调整其对向移动收集器上传数据的机会的付款。相应地,我们给出了一种有效的算法来共同解决这两个子问题。我们的理论分析表明,提出的算法可以为每个传感器实现最佳的数据控制,并为移动采集器实现最佳的驻留时间分配,从而最大程度地降低了总体网络成本。最后,大量的仿真结果进一步验证了我们的算法比比较的数据收集策略具有更低的成本。

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