Binary Consensus-Based Decentralized Algorithm for Event Detection in Large Scale Monitoring Systems
نویسندگان
چکیده
Decentralized sensor fusion plays a particularly important role in event occurrence detection when it comes to large scale monitoring systems. Regarding WSNs, a decentralized sensor fusion mechanism provides efficient information extraction and data reduction by means of reducing the energy and communication constraints of the embedded sensing nodes. In large scale monitoring systems event occurrence detection can be achieved by different methods based on decentralized detection. In some cases such as earthquake detection, a binary sensing approach is proper. This mainly concerns to binary consensus algorithms intended to allow efficient in-network data processing. The paper discusses a binary consensus mechanism for use in wireless sensor networks in large scale monitoring systems for event occurrence detection. We focus more on real hardware and software implementation instead of theoretical work. Experimental results such as convergence time are provided stemming from a flexible testbed based on Contiki-Cooja WSN simulator. Moreover, we are able to perform energy consumption estimation for each sensing node by means of convergence steps and power trace. Experimental results showed that time convergence can vary in a rather unexpected way for different number of sensor nodes, while number of convergence steps and power consumption are linear dependent to the number of sensor nodes. A network architecture based on clusters of nodes should be considered for wireless sensor networks consisting of large number of sensor nodes. Key-Words: wireless sensor networks; decentralized sensor fusion; binary consensus; Contiki Cooja
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تاریخ انتشار 2015