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Lower bounds on data collection time in sensory networks

机译:感觉网络中数据收集时间的下限

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摘要

Data collection, i.e., the aggregation at the user location of information gathered by sensor nodes, is a fundamental function of sensory networks. Indeed, most sensor network applications rely on data collection capabilities, and consequently, an inefficient data collection process may adversely affect the performance of the network. In this paper, we study via simple discrete mathematical models, the time performance of the data collection and data distribution tasks in sensory networks. Specifically, we derive the minimum delay in collecting sensor data for networks of various topologies such as line, multiline, and tree and give corresponding optimal scheduling strategies. Furthermore, we bound the data collection time on general graph networks. Our analyses apply to networks equipped with directional or omnidirectional antennas and simple comparative results of the two systems are presented.
机译:数据收集,即由传感器节点收集的信息在用户位置的聚集,是传感网络的基本功能。实际上,大多数传感器网络应用程序都依赖于数据收集功能,因此,效率低下的数据收集过程可能会对网络的性能产生不利影响。在本文中,我们通过简单的离散数学模型研究了感官网络中数据收集和数据分发任务的时间性能。具体而言,我们推导了收集各种拓扑(如线,多线和树)网络的传感器数据的最小延迟,并给出了相应的最佳调度策略。此外,我们将数据收集时间限制在通用图网络上。我们的分析适用于配备有定向或全向天线的网络,并给出了两个系统的简单比较结果。

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