Context aware routing in Distributed Sensor Networks for data gathering and dissemination

L. B. Bhajantri, N. Nalini, V. Patil
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引用次数: 2

Abstract

This paper proposes a context aware routing in distributed sensor network for data gathering and dissemination. A Distributed Sensor Network (DSN) is composed of intelligent sensors that are geographically dispersed in the region of interest and interconnected through a communication network. The (acoustic, seismic, and infrared) data by leaf sensor nodes are transmitted over the network and integrated at the processing element to derive appropriate interferences about the environment for different purposes, such as target tracking, location, surveillance and so on. Since a DSN is typically deployed for remote operations in unstructured area and the measurements are usually collected in a harsh, unreliable, and even adversarial environment, it is critical to provide extended networking capability to guarantee the performance of the entire system. In this work, we consider different contexts in distributed sensors network by considering the scenario of forest area such as: temperature context, air pressure context and object aware context. This work mainly focuses on routing the data from source to sink, and gathering and dissemination of related data. In this work, data aggregation is done in two phase: In first phase data is aggregated in Data Aggregator (DA) and in second phase data is aggregated in Master Aggregator (MA). If the context is in the emergency level then data is disseminated to target area. We simulated the context aware routing for data gathering and dissemination to test the operation scheme in terms of performance parameters.
分布式传感器网络中用于数据收集和传播的上下文感知路由
本文提出了一种分布式传感器网络中用于数据采集和分发的上下文感知路由。分布式传感器网络(DSN)由地理上分散在感兴趣区域的智能传感器组成,并通过通信网络相互连接。叶片传感器节点的(声、震、红外)数据通过网络传输,并在处理单元进行整合,得出对环境的适当干扰,用于不同目的,如目标跟踪、定位、监视等。由于DSN通常用于非结构化区域的远程操作,并且通常在恶劣、不可靠甚至敌对的环境中收集测量数据,因此提供扩展的网络功能以保证整个系统的性能至关重要。在这项工作中,我们通过考虑森林区域的场景来考虑分布式传感器网络中的不同环境,例如:温度环境、气压环境和物体感知环境。这项工作主要集中在数据从源到汇的路由,以及相关数据的收集和传播。在这项工作中,数据聚合分两个阶段完成:第一阶段数据在数据聚合器(data Aggregator, DA)中聚合,第二阶段数据在主聚合器(Master Aggregator, MA)中聚合。如果情况属于紧急级别,则将数据传播到目标地区。我们模拟了上下文感知路由的数据收集和分发,以测试操作方案在性能参数方面的性能。
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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