RSSI and LQI Data Clustering Techniques to Determine the Number of Nodes in Wireless Sensor Networks. (13th May 2014)

• Record Type: Journal Article
• Authors: Wang, Yanwen; Guardiola, Ivan G.; Wu, Xiaoling
• Is Part Of: International journal of distributed sensor networks. Volume 10:Number 5(2014)
• Publication Date: 2014-05-13
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2014/380526
• Languages: English
• ISSNs: 1550-1329

Abstract

With the rapid proliferation of wireless sensor networks, different network topologies are likely to exist in the same geographical region, each of which is able to perform its own functions individually. However, these networks are prone to cause interference to neighbor networks, such as data duplication or interception. How to detect, determine, and locate the unknown wireless topologies in a given geographical area has become a significant issue in the wireless industry. This problem is especially acute in military use, such as spy-nodes detection and communication orientation systems. In this paper, three different clustering methods are applied to classify the RSSI and LQI data recorded from the unknown wireless topology into a certain number of groups in order to determine the number of active sensor nodes in the unknown wireless topology. The results show that RSSI and LQI data are capable of determining the number of active communication nodes in wireless topologies.