Reliability guaranteed efficient data gathering in wireless sensor networks
Reliability guaranteed efficient data gathering in wireless sensor networks
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DOI：
10.1109/access.2015.2426794
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发表时间：
2015-04
期刊：
影响因子：
3.9
通讯作者：
J. Long;M. Dong;K. Ota;Anfeng Liu;S. Hai
中科院分区：
文献类型：
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作者：
J. Long;M. Dong;K. Ota;Anfeng Liu;S. Hai
无线传感器网络（WSNs）广泛应用于各种工业应用中。在本文中，我们提出了一个有效的数据收集方案，保证服务质量和优化以下网络性能指标，以及在无线传感器网络的端到端的可靠性：（1）最小的总能耗;（2）最小的单位数据传输能耗;（3）最大的利用效率定义为网络寿命每单位部署。我们首先将性能优化问题转化为优化以下参数的问题：（1）部署节点数N*;（2）节点布局d*;以及（3）节点传输结构p*。然后，我们证明了优化问题是数学上可解的。根据我们的观察，靠近sink趋势的传感器节点很早就失败了，因为它们消耗了更多的能量，而去往sink的中继流量更大，这严重影响了网络性能。这种优化的关键是对靠近sink的节点采用较低的可靠性要求和较短的传输距离。因此，这减少了热点区域中的节点的能量消耗。同时，对远离sink的节点采用更高的可靠性要求和更远的传输距离，充分利用节点剩余能量，在不损害网络可靠性的前提下优化网络性能。数值仿真结果表明，该方法在保证网络可靠性的前提下，使网络寿命提高了18%-48%，网络效用提高了17%。
Wireless sensor networks (WSNs) are widely applied in various industrial applications. In this paper, we present an efficient data gathering scheme that guarantees the Quality of Service and optimizes the following network performance metrics as well as the end-to-end reliability in WSNs: (1) minimum total energy consumption; (2) minimum unit data transmitting energy consumption; and (3) maximum utilization efficiency defined as network lifetime per unit deployment. We first transform the performance optimization problem into a problem to optimize the following parameters: (1) deployed nodal number N*; (2) nodal placement d*; and (3) nodal transmission structure p*. Then, we prove that the optimization problem is solvable mathematically. For our observation, the sensor nodes close to the sink trend failed early since they consumed more energy with heavier relay traffic destined for the sink, which seriously affects the network performance. The key point of this optimization is adopting lower reliability requirements and shorter transmission distance for nodes near the sink. Consequently, this reduces the energy consumption of the nodes in the hotspot area. Meanwhile, it adopts higher reliability requirements and farther transmission distance for nodes far from the sink to make full use of the node residual energy, so as to optimize the network performance without harming network reliability. Numerical simulation results demonstrate that our optimal approach improves the network lifetime by 18%-48% and network utility by 17%, and guarantees desire reliability level.