Selective Sleep- awake Scheduling in WSN -Cloud Integration

Abstract

The integration of Wireless Sensor Network (WSN) with Cloud is becoming popular in most of the industry and academics. WSN is bringing attention from past few decades as it used in many geographical area and application. The usage of WSN have several benefits such as tiny size, low power, low cost and easy communication over small range. With these benefits it has certain drawbacks like low processing power, scarcity of storage and limited battery life. The biggest constraints of WSN is low battery powered and limited processing. The idea behind the integration of WSN and CC is to overcome the certain limitation of WSN and to exploit the cloud to share and process the sensory data such as temperature, pressure, light, movement etc. as collected by WSN anytime and anywhere. The proposed model deals with environmental application where detection of forest fire is analyzed by taking parameters such as temperature, humidity, wind speed and time using fuzzy logic as by detecting earlier of fire in forest it helps to prevent huge loss of living organism, infrastructure and property. After detection the proposed MSA (Modified Sleep Awake) model work in prolonging lifetime of WSN in forest fire application using selective sleep awake approach.