Efficient Enhanced Sleep Awake Scheduling Using Fuzzy Logic and Neural Networks : A Review

Abstract

WSN is a distributed network that consists of great amount of sensor nodes and has the capacity of sensing, processing and transmits the partially processed and required data only. Sensor nodes have a tiny size, low cost but along with it the constraints of sensor node is they have limited memory, power source which is irreplaceable so power conservation should primarily focused by sensor network protocols. The proposed model was 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. Cloud computing help to overcome the limitation of WSN such as limited storage, processing, power life processing. The resource allocation problem is the major problem for a group of cloud user requests. The scheduling algorithms are termed as NP completeness problems in which FIFO scheduling is used by the master node to distribute resources to the waiting tasks. The problem like fragmentation of resources, low utilization of the resources such as CPU utilization, network throughput, disk I/O rate. In this paper different papers are reviewed and further it is implemented in research paper.