Kruekaew, Boonhatai
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Kruekaew, Boonhatai
Alternative Name
Kruekaew, B.
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Email
boonhatai.kr@kmitl.ac.th
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Item type:Publication, Heuristic Task Scheduling with Artificial Bee Colony Algorithm for Virtual Machines(2016-12-28); Cloud computing is one of the Information Technology services which are provided from IT infrastructures to application services. It is the combination of Distributed computing and virtualization technology using virtual machines, an essential component in Cloud computing. Therefore, task scheduling is an important matter to consider for virtual machines to balance load of each machine and to efficiently use the resources in Cloud computing. This paper proposes the use of Heuristic task scheduling with Artificial Bee Colony algorithm for virtual machines in heterogeneous Cloud computing, called HABC. The research aim is to introduce HABC, which is a new task scheduling and load balancing algorithm, for virtual machines in heterogeneous environments to reduce the makespan in the system. In the experiments, CloudSim was simulated to compare various types of the optimization task scheduling in using the virtual machines. The experimental results indicated that using the proposed Artificial Bee Colony algorithm when large job was considered first (HABC-LJF) in virtual machine scheduling, improved the efficiency in task scheduling and load balancing of virtual machines in Cloud computing. In addition, the proposed algorithm can minimize the makespan even if the tasks are increased and the different types of data are distributed. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Virtual machine scheduling management on Cloud computing using Artificial Bee Colony(2014-01-01); Resource scheduling management design on Cloud computing is an important problem. Scheduling model, cost, quality of service, time, and conditions of the request for access to services are factors to be focused. A good task scheduler should adapt its scheduling strategy to the changing environment and load balancing Cloud task scheduling policy. Therefore, in this paper, Artificial Bee Colony (ABC) is applied to optimize the scheduling of Virtual Machine (VM) on Cloud computing. The main contribution of work is to analyze the difference of VM load balancing algorithm and to reduce the makespan of data processing time. The scheduling strategy was simulated using CloudSim tools. Experimental results indicated that the combination of the proposed ABC algorithm, scheduling based on the size of tasks, and the Longest Job First (LJF) scheduling algorithm performed a good performance scheduling strategy in changing environment and balancing work load which can reduce the makespan of data processing time.