Deep Learning Based Security Model for Cloud based Task Scheduling

K Devi, D. Paulraj, B. Muthusenthil

2020KSII Transactions on Internet and Information Systems41 citationsDOI Open Access PDF

Abstract

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms

Topics & Concepts

Computer scienceCloud computingScheduling (production processes)Task (project management)Distributed computingArtificial intelligenceComputer securityOperating systemSystems engineeringMathematical optimizationMathematicsEngineeringCloud Computing and Resource ManagementIoT and Edge/Fog ComputingDistributed and Parallel Computing Systems