Resource scheduling algorithm with load balancing for cloud service provisioning

Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, Scalable traffic management has been developed in cloud data center...

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Main Authors: Priya, V., Sathiya Kumar, C., Kannan, R.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.22121 /
Published: 2019
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059462538&doi=10.1016%2fj.asoc.2018.12.021&partnerID=40&md5=fc57bfedf7dab7c8601b5e5f758c8d8e
http://eprints.utp.edu.my/22121/
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spelling utp-eprints.221212019-02-28T08:00:17Z Resource scheduling algorithm with load balancing for cloud service provisioning Priya, V. Sathiya Kumar, C. Kannan, R. Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, Scalable traffic management has been developed in cloud data centers for traffic load balancing and quality of service provisioning. However, latency reducing during multidimensional resource allocation still remains a challenge. Hence, there necessitates efficient resource scheduling for ensuring load optimization in cloud. The objective of this work is to introduce an integrated resource scheduling and load balancing algorithm for efficient cloud service provisioning. The method constructs a Fuzzy-based Multidimensional Resource Scheduling model to obtain resource scheduling efficiency in cloud infrastructure. Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. A load balancing algorithm is then implemented to avoid underutilization and overutilization of resources, improving latency time for each class of request. Simulations were conducted to evaluate the effectiveness using Cloudsim simulator in cloud data centers and results shows that the proposed method achieves better performance in terms of average success rate, resource scheduling efficiency and response time. Simulation analysis shows that the method improves the resource scheduling efficiency by 7 and also reduces the response time by 35.5 when compared to the state-of-the-art works. © 2018 Elsevier B.V. 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059462538&doi=10.1016%2fj.asoc.2018.12.021&partnerID=40&md5=fc57bfedf7dab7c8601b5e5f758c8d8e Priya, V. and Sathiya Kumar, C. and Kannan, R. (2019) Resource scheduling algorithm with load balancing for cloud service provisioning. Applied Soft Computing Journal, 76 . pp. 416-424. http://eprints.utp.edu.my/22121/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, Scalable traffic management has been developed in cloud data centers for traffic load balancing and quality of service provisioning. However, latency reducing during multidimensional resource allocation still remains a challenge. Hence, there necessitates efficient resource scheduling for ensuring load optimization in cloud. The objective of this work is to introduce an integrated resource scheduling and load balancing algorithm for efficient cloud service provisioning. The method constructs a Fuzzy-based Multidimensional Resource Scheduling model to obtain resource scheduling efficiency in cloud infrastructure. Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. A load balancing algorithm is then implemented to avoid underutilization and overutilization of resources, improving latency time for each class of request. Simulations were conducted to evaluate the effectiveness using Cloudsim simulator in cloud data centers and results shows that the proposed method achieves better performance in terms of average success rate, resource scheduling efficiency and response time. Simulation analysis shows that the method improves the resource scheduling efficiency by 7 and also reduces the response time by 35.5 when compared to the state-of-the-art works. © 2018 Elsevier B.V.
format Article
author Priya, V.
Sathiya Kumar, C.
Kannan, R.
spellingShingle Priya, V.
Sathiya Kumar, C.
Kannan, R.
Resource scheduling algorithm with load balancing for cloud service provisioning
author_sort Priya, V.
title Resource scheduling algorithm with load balancing for cloud service provisioning
title_short Resource scheduling algorithm with load balancing for cloud service provisioning
title_full Resource scheduling algorithm with load balancing for cloud service provisioning
title_fullStr Resource scheduling algorithm with load balancing for cloud service provisioning
title_full_unstemmed Resource scheduling algorithm with load balancing for cloud service provisioning
title_sort resource scheduling algorithm with load balancing for cloud service provisioning
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059462538&doi=10.1016%2fj.asoc.2018.12.021&partnerID=40&md5=fc57bfedf7dab7c8601b5e5f758c8d8e
http://eprints.utp.edu.my/22121/
_version_ 1741196571527086080
score 11.62408

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