Detection and Resolving WSN Issues with the use of Data Mining & Intelligent Algorithms

Abstract

In this digital age, development in the Wireless Sensor Network (WSN) has offered many dimensions for the researchers to work on. Knowledge extraction, effective communication, security and energy limitation are the major issues in any network to secure important data and computer systems. Development in the data mining technologies, is also a gateway to discover the knowledge from the previously stored hidden data through which intelligent decisions can be made regarding any issue. In this paper, we have a detailed review on the different aspects of issues in WSN with different applications and desired approaches. Data mining in WSN is applied to discover important information to improve network performance. It includes the study on online Mining for Energy Efficiency, Outlier Detection Techniques for Wireless Sensor Networks, Data Mining Techniques to Intrusion Detection in Wireless Sensor Networks, Mobile Agent and Distributed Data Mining, Local Outlier Detection for Data Streams in Sensor Networks, Analyzing Data Mining Techniques for Wireless Sensor Network Protocols, Distributed Event Detection in Wireless Sensor Networks for Disaster Management, Detecting and Resolving major issues and Soft Computing Techniques in Wireless Sensor Network by using Data Mining and WSN for monitoring and event reporting in underground mine environments. This paper provides a unified view of state of the art data mining techniques and algorithms to resolve WSN issues since 2007 to the date.