GSAGA: A hybrid algorithm for task scheduling in cloud infrastructure

Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for bet...

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Published in:	The Journal of supercomputing Vol. 78; no. 15; pp. 17423 - 17449
Main Authors:	Pirozmand, Poria, Javadpour, Amir, Nazarian, Hamideh, Pinto, Pedro, Mirkamali, Seyedsaeid, Ja’fari, Forough
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.10.2022 Springer Nature B.V
Subjects:	Algorithms Cloud computing Compilers Computer networks Computer Science Distributed processing Genetic algorithms Internet resources Interpreters Processor Architectures Programming Languages Random search method Search algorithms Task scheduling Traveling salesman problem Cloud computing Gravitational search Epigenomics NP-hard problem GSA Genetic algorithm SLA Scheduling Resources
ISSN:	0920-8542, 1573-0484
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Abstract	Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for better performance. Task scheduling is one of the most important aspects of cloud computing. In order to achieve high performance from cloud computing systems, tasks need to be scheduled for processing by appropriate computing resources. The large search space of this issue makes it an NP-hard problem, and more random search methods are required to solve this problem. Multiple solutions have been proposed with several algorithms to solve this problem until now. This paper presents a hybrid algorithm called GSAGA to solve the Task Scheduling Problem (TSP) in cloud computing. Although it has a high ability to search the problem space, the Genetic Algorithm (GA) performs poorly in terms of stability and local search. It is therefore possible to create a stable algorithm by combining the general search capacities of the GA with the Gravitational Search Algorithm (GSA). Our experimental results indicate that the proposed algorithm can solve the problem with higher efficiency compared with the state-of-the-art.
AbstractList	Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an overview of many available resources. Cloud providers want to get the most out of their resources, and users are inclined to pay less for better performance. Task scheduling is one of the most important aspects of cloud computing. In order to achieve high performance from cloud computing systems, tasks need to be scheduled for processing by appropriate computing resources. The large search space of this issue makes it an NP-hard problem, and more random search methods are required to solve this problem. Multiple solutions have been proposed with several algorithms to solve this problem until now. This paper presents a hybrid algorithm called GSAGA to solve the Task Scheduling Problem (TSP) in cloud computing. Although it has a high ability to search the problem space, the Genetic Algorithm (GA) performs poorly in terms of stability and local search. It is therefore possible to create a stable algorithm by combining the general search capacities of the GA with the Gravitational Search Algorithm (GSA). Our experimental results indicate that the proposed algorithm can solve the problem with higher efficiency compared with the state-of-the-art.
Author	Pinto, Pedro Javadpour, Amir Mirkamali, Seyedsaeid Pirozmand, Poria Nazarian, Hamideh Ja’fari, Forough
Author_xml	– sequence: 1 givenname: Poria surname: Pirozmand fullname: Pirozmand, Poria organization: School of Computer and Software, Dalian Neusoft University of Information – sequence: 2 givenname: Amir surname: Javadpour fullname: Javadpour, Amir email: a.javadpour87@gmail.com, a_javadpour@e.gzhu.edu.cn organization: ADiT-Lab, Electrotechnics and Telecommunications Department, Instituto Politécnico de Viana do Castelo, Department of Computer Science and Technology, Harbin Institute of Technology – sequence: 3 givenname: Hamideh surname: Nazarian fullname: Nazarian, Hamideh organization: Department of Management, Alzahra University – sequence: 4 givenname: Pedro surname: Pinto fullname: Pinto, Pedro organization: ADiT-Lab, Electrotechnics and Telecommunications Department, Instituto Politécnico de Viana do Castelo – sequence: 5 givenname: Seyedsaeid surname: Mirkamali fullname: Mirkamali, Seyedsaeid organization: Department of Computer Engineering and IT, Payame Noor University (PNU) – sequence: 6 givenname: Forough surname: Ja’fari fullname: Ja’fari, Forough organization: Department of Computer Engineering, Sharif University of Technology
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Snippet	Cloud computing is becoming a very popular form of distributed computing, in which digital resources are shared via the Internet. The user is provided with an...
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SubjectTerms	Algorithms Cloud computing Compilers Computer networks Computer Science Distributed processing Genetic algorithms Internet resources Interpreters Processor Architectures Programming Languages Random search method Search algorithms Task scheduling Traveling salesman problem
Title	GSAGA: A hybrid algorithm for task scheduling in cloud infrastructure
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