A Comparative Study on GA-based Scheduling on Cloud Computing

Lamisha Rawshan; Tasnim Rahman; Afsana Begum; Syeda Sumbul Hossain; Touhid Bhuiyan

doi:10.1145/3372422.3372425

A Comparative Study on GA-based Scheduling on Cloud Computing

Lamisha Rawshan, Tasnim Rahman, Afsana Begum, Syeda Sumbul Hossain, Touhid Bhuiyan

Research output: Contribution to conference › Conference paper

Abstract

Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.

Original language	English
Pages	74-78
Number of pages	5
DOIs	https://doi.org/10.1145/3372422.3372425
Publication status	Published - 23 Nov 2019
Externally published	Yes
Event	ACM International Conference Proceeding Series - Duration: 9 Dec 2019 → …

Conference

Conference	ACM International Conference Proceeding Series
Period	9/12/19 → …

Keywords

GA
Makespan
Meta-heuristics
Scheduling
VM

Access to Document

10.1145/3372422.3372425

Cite this

@conference{5987264c67f94a9b82ac712fef3f7fec,

title = "A Comparative Study on GA-based Scheduling on Cloud Computing",

abstract = "Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.",

keywords = "GA, Makespan, Meta-heuristics, Scheduling, VM",

author = "Lamisha Rawshan and Tasnim Rahman and Afsana Begum and Hossain, {Syeda Sumbul} and Touhid Bhuiyan",

year = "2019",

month = nov,

day = "23",

doi = "10.1145/3372422.3372425",

language = "English",

pages = "74--78",

note = "ACM International Conference Proceeding Series ; Conference date: 09-12-2019",

}

TY - CONF

T1 - A Comparative Study on GA-based Scheduling on Cloud Computing

AU - Rawshan, Lamisha

AU - Rahman, Tasnim

AU - Begum, Afsana

AU - Hossain, Syeda Sumbul

AU - Bhuiyan, Touhid

PY - 2019/11/23

Y1 - 2019/11/23

N2 - Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.

AB - Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.

KW - GA

KW - Makespan

KW - Meta-heuristics

KW - Scheduling

KW - VM

U2 - 10.1145/3372422.3372425

DO - 10.1145/3372422.3372425

M3 - Conference paper

SP - 74

EP - 78

T2 - ACM International Conference Proceeding Series

Y2 - 9 December 2019

ER -

A Comparative Study on GA-based Scheduling on Cloud Computing

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this