Online data gathering for maximizing network lifetime in sensor networks
Online data gathering for maximizing network lifetime in sensor networks
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DOI：
10.1109/tmc.2007.250667
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发表时间：
2007-01-01
影响因子：
7.9
通讯作者：
Liu, Yuzhen
中科院分区：
文献类型：
--
作者：
Liang, Weifa;Liu, Yuzhen
能量受限的传感器网络已被广泛部署用于监测和监视目的。在这种网络中收集数据通常是一种普遍的操作。由于传感器具有显著的功率限制（电池寿命），因此必须采用节能方法进行数据收集以延长网络寿命。我们考虑了传感器网络中的在线数据收集问题，其表述如下：假设有一个数据收集查询序列，这些查询一个接一个地到达。为了响应每个查询，系统会为它建立一个路由树，在树中，每个内部节点传输的数据量不仅取决于节点本身感测的数据量，还取决于从其子节点接收的数据量。我们的目标是最大限度地提高网络的生命周期，没有任何知识的未来查询到达和生成率。换句话说，目标是最大化回答的数据收集查询的数量，直到网络中的第一个节点出现故障。针对所关心的问题，本文首先提出了一个通用的数据收集查询的能量消耗模型，如果路由树用于查询评估。然后，我们证明了这个问题是NP-完全的，并提出了几个启发式算法。最后，我们进行了模拟实验，以评估所提出的算法的性能方面的网络生命周期交付。实验结果表明，在所提出的算法中，一个算法，同时考虑到剩余能量和数据量在每个传感器节点显着优于其他。
Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: Assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others.