Data acquisition and delay optimization in WSN using knapsack algorithm in presence of transfaulty nodes

T. P. Shamna, P. Praveen
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引用次数: 2

Abstract

The wireless sensors has wide range of applications. The sensor network consist of many tiny sensors and each sensor is assigned to perform specific mission that is some node are transmitting node some are receiving and others are intermediate sensing nodes. Once sensor nodes are deployed, thereafter no additional actions are performed. In typical WSNs, the sensor nodes collect the information from the environment and the collection of the data is done in the intermediate nodes. The collected data is the send to the base station. Reliable communication, power efficiency and network survivability issues are critical concerns, because all the operation is done in sensor nodes. Energy consumption and end to end delay is a major issue in WSNs [8]. In this work we propose a scheme named data acquisition along with knapsack algorithm for reliable and efficient data transmission and delay optimization in the presence of transfaulty nodes. To prevent information loss in WSN due to transfaulty behavior of sensor nodes, in the proposed scheme we construct the network using sensor nodes having dual mode of communication — RF, acoustic and also we use knapsack algorithm for reliable data transmission. Knapsack algorithm is to increase the in-order packets and decrease the out-of-order packets simultaneously, which helps for delay optimization. This scheme has better energy efficiency and reduced delay.
基于背包算法的WSN跨故障节点数据采集与时延优化
无线传感器具有广泛的应用前景。传感器网络由许多微小的传感器组成,每个传感器被分配执行特定的任务,即一些节点是发送节点,一些节点是接收节点,其他节点是中间感知节点。一旦部署了传感器节点,就不会再执行其他操作。在典型的wsn中,传感器节点从环境中收集信息,数据的收集在中间节点完成。采集到的数据被发送到基站。由于所有操作都在传感器节点中完成,因此可靠的通信、功率效率和网络生存性问题是关键问题。能量消耗和端到端延迟是无线传感器网络的主要问题[8]。在这项工作中,我们提出了一种名为数据采集和背包算法的方案,用于在跨故障节点存在的情况下可靠高效的数据传输和延迟优化。为了防止由于传感器节点的故障行为而造成的信息丢失,在该方案中,我们使用具有射频和声学双重通信模式的传感器节点构建网络,并使用背包算法进行可靠的数据传输。背包算法是在增加有序数据包的同时减少无序数据包,有利于时延优化。该方案具有较好的能效和较低的时延。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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