Review of the quality of service scheduling  mechanisms in cloud

RemeshBabu, K R; Samuel, Philip

doi:10.14419/ijet.v7i3.13016

Cited by 4 publications

(3 citation statements)

References 65 publications

(77 reference statements)

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“…Definition Minimum power usage (EC, ED) consists of power consumption and CPU running time, relying primarily on high power, that is, dynamic energy utilization. Equation () 28 shows the active power

{P}_d

of a process is typically proportionate to the processing frequency (

f

) 29

$$ {P}_d=c{f}^3.

…”

Section: Tasks and Vm Allocation Schedulingmentioning

confidence: 99%

Task scheduling to a virtual machine using a multi‐objective mayfly approach for a cloud environment

Durairaj

Ramaswamy

2022

Concurrency and Computation

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Summary Cloud computing has been progressively popular in the arenas of research and business in the recent years. Virtualization is a resource management approach used in today's cloud computing environment. Virtual Machine (VM) migration algorithms allow for more dynamic resource allocation, as well as improvement in computing power and communication capability in cloud data centers. This necessitates an intelligent optimization approach to VM allocation design for an improved performance of application. In this article, a multi‐objective optimal design approach is proposed to tackle the tasks of VM allocation. Multi‐Objective Optimization (MOO) is a strategy adopted by several methods to handle tasks and workflow scheduling issues that deal with numerous opposing goals. In the cloud computing context, effective task scheduling is critical for achieving cost effective implementation as well as resource utilization. To address the optimal solution, this article proposes an entropy‐based multi objective mayfly algorithm is assessed using a convergence pattern in MOO. The model is tested by implementing in a cloud simulator and results prove that the recommended model has an improved performance with regard to factors such as time and utilization rate.

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{P}_d

of a process is typically proportionate to the processing frequency (

f

) 29

$$ {P}_d=c{f}^3.

…”

Section: Tasks and Vm Allocation Schedulingmentioning

confidence: 99%

Task scheduling to a virtual machine using a multi‐objective mayfly approach for a cloud environment

Durairaj

Ramaswamy

2022

Concurrency and Computation

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“…Rodriguez and Buyya presented the taxonomy on scheduling algorithms for scientific workflows, which gives insight into the problems encountered while scheduling the computing resources. Remesh Babu and Samuel had given a detailed review on recently proposed papers on QoS scheduling and load balancing techniques in the cloud. This paper listed the highlights and limitations based on parameters such as time, cost, energy, etc.…”

Section: Related Workmentioning

confidence: 99%

Service‐level agreement–aware scheduling and load balancing of tasks in cloud

Babu¹,

Samuel

2019

Softw Pract Exp

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Summary Cloud computing is an innovative computing paradigm designed to provide a flexible and low‐cost way to deliver information technology services on demand over the Internet. Proper scheduling and load balancing of the resources are required for the efficient operations in the distributed cloud environment. Since cloud computing is growing rapidly and customers are demanding better performance and more services, scheduling and load balancing of the cloud resources have become very interesting and important area of research. As more and more consumers assign their tasks to cloud, service‐level agreements (SLAs) between consumers and providers are emerging as an important aspect. The proposed prediction model is based on the past usage pattern and aims to provide optimal resource management without the violations of the agreed service‐level conditions in cloud data centers. It considers SLA in both the initial scheduling stage and in the load balancing stage, and it looks into different objectives to achieve the minimum makespan, the minimum degree of imbalance, and the minimum number of SLA violations. The experimental results show the effectiveness of the proposed system compared with other state‐of‐the‐art algorithms.

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“…over the internet. Cloud computing is a very proficient paradigm due to its reliability, availability, on-demand, easy to maintain, pay per -use, and scalability [4] [5]. Quality of Service in cloud computing as an essential issue on which many researchers are working.…”

Section: Introductionmentioning

confidence: 99%

Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

Kumar¹,

Suman²

2019

IJRTE

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Cloud computing technology has gained the attention of researchers in recent years. Almost every application is using cloud computing in one way or another. Virtualization allows running many virtual machines on a single physical computer by sharing its resources. Users can store their data on datacenter and run their applications from anywhere using the internet and pay as per service level agreement documents accordingly. It leads to an increase in demand for cloud services and may decrease the quality of service. This paper presents a priority-based selection of virtual machines by cloud service provider. The virtual machines in the cloud datacenter are configured as Amazon EC2 and algorithm is simulated in cloud-sim simulator. The results justify that proposed priority-based virtual machine algorithm shortens the makespan, by 11.43 % and 5.81 %, average waiting time by 28.80 % and 24.50%, and cost of using the virtual machine by 21.24% and 11.54% as compared to FCFS and ACO respectively, hence improving quality of service.

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Review of the quality of service scheduling mechanisms in cloud

Cited by 4 publications

References 65 publications

Task scheduling to a virtual machine using a multi‐objective mayfly approach for a cloud environment

Task scheduling to a virtual machine using a multi‐objective mayfly approach for a cloud environment

Service‐level agreement–aware scheduling and load balancing of tasks in cloud

Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

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