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Job Scheduling Using Fuzzy Neural Network Algorithm in Cloud Environment

DOI: 10.9756/bijmmi.1064

Keywords: Cloud Computing , Neural Network , Fuzzy Logic , Job Scheduling , Berger Model

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Abstract:

Cloud Computing is providing computing as a service rather than product such as shared resources, software information, etc...Cloud computing can be used for dispatching user tasks or jobs to the available system resource like storage and software. Scheduling algorithm is used for dispatching user tasks. In Job scheduling using fuzzy neural network algorithm, first user tasks are classified based on Quality of service parameters like bandwidth, memory, CPU utilization and size. The classified tasks are given to fuzzier where the input values are converted into the range between 0 and 1. Neural network contains input layer, hidden layer and output layer for adjusting the weight of user task and match with system resources. The function of de-fuzzier is to reverse the operation performed by fuzzier. The exemplar input is matched with the exemplar output label by adjusting weights. The algorithm is implemented with the help of simulation tool (CloudSim) and the result obtained reduces the total turnaround time and also increase the performance.

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