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A Dynamic Task Scheduling Algorithm Improved by Load Balancing in Cloud Computing

Fatemeh Ebadifard, Seyed Morteza Babamir, Sedighe Barani

202051 citationsDOI

Abstract

Task scheduling is the main challenge for the service provider in cloud Computing. One of the most critical objective in the scheduling is to assign tasks to virtual machines so that some machines do not overload or under load. To do this, load balancing plays a crucial role in the scheduling problem. Using an appropriate load balancing method can reduce response time and increase resource utilization. In this paper, we present a dynamic method for scheduling a task to virtual machines to increase load balancing and reliability in cloud computing. The proposed method reduces the makespan, increases the degree of load balancing, and improves the system's reliability. The proposed method, in contrast to previous work, has been able to increase the reliability of the task scheduling based on previous experience of the virtual machines in addition to the fair distribution of workload among the virtual machines. We have compared the proposed algorithm with other task scheduling algorithms such as the honeybee load balancing and dynamic scheduling without load balancing. Simulation results show that the proposed method improves the reliability and degree of imbalance.

Topics & Concepts

Computer scienceLoad balancing (electrical power)Distributed computingDynamic priority schedulingFair-share schedulingCloud computingWorkloadVirtual machineRate-monotonic schedulingScheduling (production processes)Two-level schedulingRound-robin schedulingEarliest deadline first schedulingJob shop schedulingReal-time computingQuality of serviceComputer networkMathematical optimizationScheduleOperating systemGeometryMathematicsGridCloud Computing and Resource ManagementIoT and Edge/Fog ComputingDistributed and Parallel Computing Systems
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