Abstract—Cloud computing is a framework for enabling access to distributed computing resources. These resources may be extra storage, network bandwidth, memory space or processing power elements. The cloud user and service provider perceive the service in the cloud from different perspectives. The cloud user focuses on minimizing response time and cost of the service while the provider focuses on efficient utilization, of cloud resources, service reliability and minimization of maintenance costs. To satisfy both points of view, efficient methods to optimize cloudlets scheduling have to be provided. This paper proposes a scheduling method for cloud computing environment based on artificial neural networks (ANN) optimized with firefly algorithm to pic k out the most convenient scheduling algorithm.
Index Terms—Cloud computing, artificial neural network, task scheduling, firefly algorithm, cloudlet scheduling controller.
The authors are with the Computer Science Department, Faculty of Computers and Information, Helwan University, Cairo, Egypt (e-mail: noha7amdy@yahoo.com).
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Cite: Noha Hamdy, Amal Elsayed Aboutabl, Nahla ElHaggar, and Mostafa-Sami M. Mostafa, "Dynamic Task Scheduling Method in Cloud Computing Environment Using Optimized Neural Network," International Journal of Future Computer and Communication vol. 6, no. 4, pp. 143-147, 2017.
