Energy Efficient Data Collection Classifier in Wireless Sensor Network
Wireless sensor network (WSN) comprises of nodes that are spatially distributed to monitor the environments
and detect the data accordingly. Energy Efficient Communication Scheme (EECS) in wireless sensor network used Adaptive
and Distributed Routing (ADR) algorithm for correlated data gathering in order to minimize the total energy consumption.
Though energy consumption was reduced in the network, energy delay tradeoff occurred while securing data in sensor
network was high. Optimal Selective Forwarding for Energy Saving (OSFES) scheme provided a secured data aggregation
technique using an aggregation tree which provided privacy but the energy consumption was high during event detection.
Privacy-Preserving Location Monitoring System (PPLMS) for Data Integrity recovered all sensing data events even when
the data were aggregated, by reducing the transmission overhead but with higher energy ratio. To develop an energy efficient
Data Collection Classifier in wireless sensor network, a predetermined Energy Efficient Data Collection Classifier (EEDCC)
is proposed in this paper. The EEDCC initially identifies the weight of the data events for effective classification using SVM
with minimal energy consumption. EEDCC uses Doppler Effecting method for recovering all sensing data events with
minimal energy. The task of Doppler Effecting method in EEDCC is to collect the periodic events of moving objects (i.e.,)
sensor nodes to reduce the classification time of sensor datas. With the minimal time on classification, the energy delay
tradeoff is overcome in EEDCC. Furthermore, with the application of an event section key generation in EEDCC, reduces
the energy consumption during the generating of section key and broadcast the notification to the sensor nodes within the
section. EEDCC with event section key generation improves the security level on object collection. Experimental work is
carried out on the factors such as classifier rate, security level, and energy consumption rate.
Keywords— Data Classifier, Data Collection, Wireless Sensor Network, Doppler Effecting, Key Management, Weight.