Optimal scheduling of computational task in cloud using Virtual Machine Tree

Achar, Raghavendra; Thilagam, P. Santhi; Shwetha, D.; H, Pooja; Roshni,; Andrea, Andrea

doi:10.1109/eait.2012.6407881

Cited by 24 publications

(7 citation statements)

References 5 publications

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“…At runtime broker decides mapping of task to a VM. Sometimes single tasks with multiple users [3] are mapped to VM and sometimes from a group of task a particular task is picked up for the allocation of VM depending upon the execution time and arrival time [6,7,9,12,16]. The tasks in the group is selected sequentially and submitted to the Virtual Machine.…”

Section: Related Workmentioning

confidence: 99%

Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization

Lakra

Yadav

2015

Procedia Computer Science

136

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In cloud computing datacentersexert server unification to enhance the efficiency of resources. Many Vms (virtual machine) are running on each datacenter to utilize the resources efficiently. Most of the time cloud resources are underutilized due to poor scheduling of task (or application) in datacenter. In this paper, we propose a multi-objective task scheduling algorithm formappingtasks to a Vms in order to improve the throughput of the datacenter and reduce the cost without violating the SLA (Service Level Agreement) for an application in cloud SaaS environment. The proposed algorithm provides an optimal scheduling method. Most of the algorithms schedule tasks based on single criteria (i.e execution time). But in cloud environment it is required to consider various criteria like execution time, cost, bandwidth of user etc. This algorithm is simulated using CloudSim simulator and the result shows better performance and improved throughput.

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Section: Related Workmentioning

confidence: 99%

Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization

Lakra

Yadav

2015

Procedia Computer Science

136

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“…The end goal of the VM scheduling is always be the maximum utilization of VMs resources with minimum incurred cost. Hence, efficient VM scheduling is always remains the key concern of cloud providers, and considered to be a primary feature of cloud computing [8,9].…”

Section: Virtual Machine Scheduling Problemmentioning

confidence: 99%

“…Where (7) the cost divisor ծ (Si) to reach load balancing S'I is expressed as (8) IV. METAHEURISTIC APPROACH FOR VM SCHEDULING PROBLEM Considering the system variation and historical data as a significant aspect of load balancing within the dynamic cloud environment, the authors in [12] develop an innovative technique by improving genetic algorithm for solving scheduling problem.…”

Section: ) Mathematical Modelmentioning

confidence: 99%

A Cloud-based Conceptual Framework for Multi-Objective Virtual Machine Scheduling using Whale Optimization Algorithm

2018

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Virtual machine scheduling in the cloud is considered one of the major issue to solve optimal resource allocation problem on the heterogeneous datacenters. With respect to that, the key concern is to map the virtual machines (VMs) with physical machines (PMs) in a way that maximum resource utilization can be achieved with minimum cost. Due to the fact that scheduling is an NP-hard problem, a metaheuristic approach is proven to achieve a better optimal solution to solve this problem. In a rapid changing heterogeneous environment, where millions of resources can be allocated and deallocate in a fraction of the time, modern metaheuristic algorithms perform well due to its immense power to solve the multidimensional problem with fast convergence speed. This paper presents a conceptual framework for solving multi-objective VM scheduling problem using novel metaheuristic Whale optimization algorithm (WOA). Further, we present the problem formulation for the framework to achieve multi-objective functions.

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“…Similar work is done in [17,18,19] where scheduling is done in order to reduce execution time and arrival time. Authors in [20] proposed a Dynamic task scheduling scheme DGS which allocates computing tasks to the virtual machines using greedy strategy and the scheme results in reduction in the completion time and improvement in the resource utilization.…”

Section: Related Workmentioning

confidence: 99%

Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing

Monika¹,

Jindal²

2016

MATEC Web of Conferences

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Abstract. Cloud computing is an incipient innovation which broadly spreads among analysts. It furnishes clients with foundation, stage and programming as enhancement which is easily available by means of web. A cloud is a sort of parallel and conveyed framework comprising of a gathering of virtualized PCs that are utilized to execute various tasks to accomplish good execution time, accomplish due date and usage of its assets. The scheduling issue can be seen as the finding an ideal task of assignments over the accessible arrangement of assets with the goal that we can accomplish the wanted objectives for tasks. This paper presents an optimal algorithm for scheduling tasks to get their waiting time as a QoS parameter. The algorithm is simulated using Cloudsim simulator and experiments are carried out to help clients to make sense of the bottleneck of utilizing no. of virtual machine parallely.

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Optimal scheduling of computational task in cloud using Virtual Machine Tree

Cited by 24 publications

References 5 publications

Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization

Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization

A Cloud-based Conceptual Framework for Multi-Objective Virtual Machine Scheduling using Whale Optimization Algorithm

Optimization of Task Scheduling Algorithm through QoS Parameters for Cloud Computing

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