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Sleep scheduling and lifetime maximization in sensor networks: fundamental limits and optimal solutions

机译:传感器网络中的睡眠调度和寿命最大化:基本限制和最佳解决方案

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Energy efficiency is a very critical consideration in the design of low cost sensor networks, which typically have fairly low node battery life. This raises the need for providing periodic sleep cycles for the radios in the sensor nodes. Keeping sensors in sleep state also implies that node to sink communication incurs certain delays and there exists a threshold on the duty cycling for the communication delay to be bounded, giving rise to an upperbound on the lifetime of the network i.e., the time until at least one node in the network is able to communicate its sensed data to the sink. This paper aims at establishing tight analytical bounds on the sleeping probabilities of nodes and on the achievable lifetime of wireless sensor networks in a very generic setting. Bounds on the sleeping probability need to be satisfied for proper network functionality. Further, an energy efficient deployment scheme is suggested wherein the battery power depletion is fairly uniformly deployed throughout the network. This scheme makes use of the availability of low power auxiliary channel listening radio. With this scheme, we shown that an improvement in lifetime by a factor of O(/spl radic/log n) over uniform distribution of nodes is achievable, where n is the number of nodes in the network. We also show that the throughput capacity of the network is also improved by the same factor. We show also that the maximum lifetime of the network is bounded above by O(n/sup 3/2///spl radic/log n). Further, the accuracy of our analysis is verified by the simulation results presented.
机译:在低成本传感器网络的设计中,能源效率是一个非常关键的考虑因素,低成本传感器网络的节点电池寿命通常很短。这就需要为传感器节点中的无线电提供定期的睡眠周期。将传感器保持在睡眠状态还意味着到节点进行通信的节点会产生某些延迟,并且占空比的阈值会限制通信延迟,从而导致网络生命周期的上限,即直到至少网络中的一个节点能够将其感测到的数据传递到接收器。本文旨在在非常通用的环境中为节点的休眠概率和无线传感器网络可达到的寿命建立严格的分析界限。为了适当的网络功能,需要满足睡眠概率的界限。此外,提出了一种节能部署方案,其中,在整个网络中相当均匀地部署了电池电量耗尽。该方案利用了低功率辅助信道收听无线电的可用性。通过这种方案,我们表明,在节点的均匀分布上,寿命可以提高O(/ spl radic / n / log n),其中n是网络中的节点数。我们还表明,网络的吞吐能力也提高了相同倍数。我们还表明,网络的最大寿命由O(n / sup 3/2 //// spl radic / log n)限定。此外,我们的分析的准确性已通过所提供的仿真结果进行了验证。

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