无线传感器网络中基于程序长度的最小信息损失估计事实汇编

K. Lalitha, V. M. Barkavi, R. Thangarajan, K. S. Preethi
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引用次数: 0

摘要

在无线传感器网络(WSN)中,如何收集大量的数据并减小数据量是一个亟待解决的问题。现有的方法主要是基于阈值限制的数据相似度。这些方法可能会减少无线通信的数量,但可能无法保证带宽要求。为了保证通信和带宽的要求,集群是基于数据关系框架的,信息收集是在全局级的汇聚节点上完成的。采用基于树的路由拓扑(称为convergecast)在传感器之间传输收集到的信息。在单个频率信道上进行时间调度的主要目的是尽量减少完成汇聚所需的时隙数量(调度长度)。为了减少干扰的影响,实现了多频传输调度。结果预测,由于这种全球数据收集方法,在不影响带宽需求的情况下,大大减少了通信和信息收集。
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Program length based estimated facts assembly with minimal information loss in Wireless sensor networks
In Wireless sensor networks (WSN), how to collect the major amount of data and reduce the data size is a delinquent issue. The existing methods concentrated on the data similarities based on the threshold limit. Those approaches may reduce the number of wireless communications but may not guarantee the bandwidth requirements. To ensure the communication and bandwidth requirements, clusters are framed based on the relationship of data and information gathering is done at the global level, in the sink node. A tree based routing topology known as convergecast is applied to transfer the collected information among sensors. The main aim of the time scheduling on a single frequency channel is to minimize the number of time slots required (schedule length) to complete convergecast. To reduce the effect of interference, multiple frequency transmission scheduling is implemented. The results predict that the communication and information gathering is greatly reduced without compromising the bandwidth requirements due to this global data collection approach.
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