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Understanding optimal data gathering in the energy and latency domains of a wireless sensor network

机译:了解无线传感器网络在能量和延迟范围内的最佳数据收集

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The problem of optimal data gathering in wireless sensor networks (WSNs) is addressed by means of optimization techniques. The goal of this work is to lay the foundations to develop algorithms and techniques that minimize the data gathering latency and at the same time balance the energy consumption among the nodes, so as to maximize the network lifetime. Following an incremental-complexity approach, several mathematical programming problems are proposed with focus on different network performance metrics. First, the static routing problem is formulated for large and dense WSNs. Optimal data-gathering trees are analyzed and the effects of several sensor capabilities and constraints are discussed, e.g., radio power constraints, energy consumption model, and data aggregation functionalities. Then, dynamic re-routing and scheduling are considered. An accurate network model is proposed that captures the tradeoff between the data gathering latency and the energy consumption, by modeling the interactions among the routing, medium access control and physical layers. For each problem, extensive simulation results are provided. The proposed models provide a deeper insight into the problem of timely and energy efficient data gathering. Useful guidelines for the design of efficient WSNs are derived and discussed.
机译:通过优化技术解决了无线传感器网络(WSN)中最佳数据收集的问题。这项工作的目的是为开发算法和技术打下基础,这些算法和技术可最大程度地减少数据收集延迟,同时平衡节点之间的能耗,从而最大程度地延长网络寿命。遵循增量复杂性方法,提出了几个数学编程问题,重点放在不同的网络性能指标上。首先,为大型和密集的WSN制定静态路由问题。分析了最佳的数据收集树,并讨论了几种传感器功能和约束的影响,例如,无线电功率约束,能耗模型和数据聚合功能。然后,考虑动态重路由和调度。提出了一种精确的网络模型,该模型通过对路由,介质访问控制和物理层之间的交互进行建模,来捕获数据收集延迟和能耗之间的折衷。对于每个问题,都提供了广泛的仿真结果。所提出的模型提供了对及时且节能的数据收集问题的更深入的了解。得出并讨论了用于设计高效WSN的有用指南。

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