Abstract: A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. Intelligent sensor networks have numerous applications for distributed information gathering and processing monitoring, supervision of hazardous environments, intrusion detection. The increasing use of sensing units asks for the development of specific data mining algorithms and architectures.
Wireless sensor networks: a survey
Survey: Discovery in Wireless Sensor Networks
Interactive Data Mining
What is Data Mining (Predictive Analytics, Big Data)
A Distributed Approach for Prediction in Sensor Networks
Using Reconfigurable Computing to Accelerate Data Mining
Abstract: Data mining algorithms have become vital to researchers in science, engineering, medicine, business, search and security domains. In recent years, there has been a tremendous increase in the size of the data being collected and analyzed. Data mining algorithms have been unable to scale up to these vast amounts of data, leading to significant performance degradation. Also, the enhancements in processor and system designs do not necessarily aid data mining workloads. Therefore, there is a need to specifically address the limitations of accelerating data mining workloads.
An Architecture for Efficient Hardware Data Mining using Reconfigurable Computing Systems
School of Engineering
University of Guelph
Canada N1G 2W1