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Optimal Selective Transmission under Energy Constraints in Sensor Networks

机译:传感器网络中能量约束下的最优选择性传输

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An optimum selective transmission scheme for energy-limited sensor networks, where sensors send or forward messages of different importance (priority), is developed. Considering the energy costs, the available battery, the message importances and their statistical distribution, sensors decide whether to transmit or discard a message so that the importance sum of the effectively transmitted messages is maximized. It turns out that the optimal decision is made comparing the message importance with a time-variant threshold. Moreover, the gain of the selective transmission scheme, compared to a nonselective one, critically depends on the energy expenses, among other factors. Albeit suboptimal, practical schemes that operate under less demanding conditions than those for the optimal one are developed. Effort is placed into three directions: 1) the analysis of the optimal transmission policy for several stationary importance distributions; 2) the design of a transmission policy with invariant threshold that entails asymptotic optimality; and 3) the design of an adaptive algorithm that estimates the importance distribution from the actual received (or sensed) messages. Numerical results corroborating our theoretical claims and quantifying the gains of implementing the selective scheme close this paper.
机译:针对能量受限的传感器网络,开发了一种最佳的选择性传输方案,在该网络中,传感器发送或转发不同重要性(优先级)的消息。考虑到能源成本,可用电池,消息的重要性及其统计分布,传感器决定是发送还是丢弃消息,以使有效传输的消息的重要性之和最大化。事实证明,通过将消息重要性与时变阈值进行比较,可以做出最佳决策。此外,与非选择性传输方案相比,选择性传输方案的增益主要取决于能量消耗以及其他因素。尽管次优,但已开发出在比最佳方案要求条件低的条件下运行的实用方案。努力分为三个方向:1)对几种固定重要性分布的最优传输策略进行分析; 2)设计具有不变阈值并具有渐近最优性的传输策略; 3)一种自适应算法的设计,该算法从实际接收(或感知)的消息中估计重要性分布。数值结果证实了我们的理论主张并量化了实施选择性方案的收益。

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