An improved load balanced metaheuristic scheduling in cloud

Cloud computing refers to on-demand delivery of service over internet and has application in various domains like media, research, business, bigdata analysis etc. Task scheduling is one of the prime issues in this type of environment. Various metaheuristic algorithms and hard optimization problems h...

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Vydáno v:	Cluster computing Ročník 22; číslo Suppl 5; s. 10873 - 10881
Hlavní autoři:	Aruna, M., Bhanu, D., Karthik, S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.09.2019 Springer Nature B.V
Témata:	Algorithms Cloud computing Communication Computer Communication Networks Computer Science Efficiency Energy consumption Heuristic methods Infrastructure Load balancing Operating Systems Particle swarm optimization Polynomials Power Processor Architectures Response time Software Task scheduling Workloads Cloud computing Load balancing algorithm Scheduling Firefly algorithm (FA)
ISSN:	1386-7857, 1573-7543
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Abstract	Cloud computing refers to on-demand delivery of service over internet and has application in various domains like media, research, business, bigdata analysis etc. Task scheduling is one of the prime issues in this type of environment. Various metaheuristic algorithms and hard optimization problems have been proposed for solving cloud task scheduling which is a non-deterministic polynomial or an NP. Adaptation of the scheduling strategy to the changes taking place in the environment has to be done by a good scheduler. A proposal for cloud scheduling by means of a balanced load using both firefly algorithm (FA) and particle swarm optimization (PSO) heuristics has been made. The aim is to balance the load of the entire system while at the same time bring down the makespan of a set of tasks. This new strategy for scheduling has been simulated with CloudSim tool kit package. The results of this experiment proved that the proposed FA performed better than min–min scheduling, PSO, and also the first come first serve methods.
AbstractList	Cloud computing refers to on-demand delivery of service over internet and has application in various domains like media, research, business, bigdata analysis etc. Task scheduling is one of the prime issues in this type of environment. Various metaheuristic algorithms and hard optimization problems have been proposed for solving cloud task scheduling which is a non-deterministic polynomial or an NP. Adaptation of the scheduling strategy to the changes taking place in the environment has to be done by a good scheduler. A proposal for cloud scheduling by means of a balanced load using both firefly algorithm (FA) and particle swarm optimization (PSO) heuristics has been made. The aim is to balance the load of the entire system while at the same time bring down the makespan of a set of tasks. This new strategy for scheduling has been simulated with CloudSim tool kit package. The results of this experiment proved that the proposed FA performed better than min–min scheduling, PSO, and also the first come first serve methods.
Author	Bhanu, D. Karthik, S. Aruna, M.
Author_xml	– sequence: 1 givenname: M. surname: Aruna fullname: Aruna, M. email: aruna.cse.4388@gmail.com organization: Department of Computer Science and Engineering, Surya Engineering College – sequence: 2 givenname: D. surname: Bhanu fullname: Bhanu, D. organization: Department of Computer Science and Engineering, Karpagam Institute of Technology – sequence: 3 givenname: S. surname: Karthik fullname: Karthik, S. organization: Department of Computer Science and Engineering, SNS College of Technology
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Cites_doi	10.1504/IJBIC.2010.032124 10.3844/jcssp.2014.1156.1165 10.9790/0661-16442328 10.1007/s00521-014-1804-9 10.1109/TST.2013.6449405 10.14445/22312803/IJCTT-V9P169 10.1007/s13174-010-0007-6 10.14257/ijgdc.2015.8.2.02 10.19153/cleiej.17.1.2 10.1155/2015/780879 10.1109/ICHCI-IEEE.2013.6887799 10.1109/ICECCT.2015.7226080 10.1007/978-3-319-12286-1_6 10.5120/908-1286 10.5120/21729-4894 10.1109/C3IT.2015.7060176 10.1007/978-3-319-28031-8_6 10.1109/SPIN.2015.7095363
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References	CR2 Kaur, Kinger (CR18) 2014; 9 Pacini, Mateos, García Garino (CR19) 2014; 17 Xu, Pang, Fu (CR8) 2013; 18 CR7 CR16 CR14 CR13 CR12 CR23 CR11 CR10 CR21 Thakur, Kumar (CR9) 2015; 9 CR20 Haryani, Jagli (CR4) 2014; 16 Kaur, Kaur (CR3) 2015; 8 Priyadarsini, Arockiam (CR17) 2014; 99 Zhang, Cheng, Boutaba (CR1) 2010; 1 Kashyap, Viradiya (CR5) 2014; 3 Saranya, Maheswari (CR6) 2015; 5 Cho, Tsai, Tsai, Yang (CR15) 2015; 26 Yang (CR22) 2010; 2 Florence, Shanthi (CR24) 2014; 10 D Saranya (1213_CR6) 2015; 5 P Kaur (1213_CR3) 2015; 8 1213_CR7 R Kaur (1213_CR18) 2014; 9 1213_CR14 1213_CR12 1213_CR23 1213_CR13 1213_CR10 1213_CR21 XS Yang (1213_CR22) 2010; 2 N Haryani (1213_CR4) 2014; 16 1213_CR11 1213_CR2 1213_CR20 AP Florence (1213_CR24) 2014; 10 D Kashyap (1213_CR5) 2014; 3 KM Cho (1213_CR15) 2015; 26 E Pacini (1213_CR19) 2014; 17 G Xu (1213_CR8) 2013; 18 V Thakur (1213_CR9) 2015; 9 Q Zhang (1213_CR1) 2010; 1 1213_CR16 RJ Priyadarsini (1213_CR17) 2014; 99
References_xml	– volume: 9 start-page: 7 issue: 1 year: 2015 ident: CR9 article-title: A comparison of select load balancing algorithms in cloud computing publication-title: IUP J. Comput. Sci. – ident: CR21 – volume: 2 start-page: 78 issue: 2 year: 2010 end-page: 84 ident: CR22 article-title: Firefly algorithm, stochastic test functions and design optimisation publication-title: Int. J. Bio-Inspired Comput. doi: 10.1504/IJBIC.2010.032124 – volume: 10 start-page: 1156 issue: 7 year: 2014 ident: CR24 article-title: A load balancing model using firefly algorithm in cloud computing publication-title: J. Comput. Sci. doi: 10.3844/jcssp.2014.1156.1165 – volume: 16 start-page: 23 issue: 4 year: 2014 end-page: 28 ident: CR4 article-title: Dynamic method for load balancing in cloud computing publication-title: IOSR J. Comput. Eng. doi: 10.9790/0661-16442328 – ident: CR14 – volume: 26 start-page: 1297 issue: 6 year: 2015 end-page: 1309 ident: CR15 article-title: A hybrid meta-heuristic algorithm for VM scheduling with load balancing in cloud computing publication-title: Neural Comput. Appl. doi: 10.1007/s00521-014-1804-9 – ident: CR2 – volume: 5 start-page: 1107 issue: 7 year: 2015 end-page: 1111 ident: CR6 article-title: Load balancing algorithms in cloud computing: a review publication-title: Int. J. Adv. Res. Comput. Sci. Softw. Eng. – volume: 18 start-page: 34 issue: 1 year: 2013 end-page: 39 ident: CR8 article-title: A load balancing model based on cloud partitioning for the public cloud publication-title: Tsinghua Sci. Technol. doi: 10.1109/TST.2013.6449405 – ident: CR16 – volume: 9 start-page: 379 issue: 7 year: 2014 end-page: 386 ident: CR18 article-title: Analysis of job scheduling algorithms in cloud computing publication-title: Int. J. Comput. Trends Technol. doi: 10.14445/22312803/IJCTT-V9P169 – ident: CR12 – ident: CR13 – ident: CR10 – ident: CR11 – volume: 1 start-page: 7 issue: 1 year: 2010 end-page: 18 ident: CR1 article-title: Cloud computing: state-of-the-art and research challenges publication-title: J. Internet Serv. Appl. doi: 10.1007/s13174-010-0007-6 – volume: 99 start-page: 47 issue: 18 year: 2014 end-page: 54 ident: CR17 article-title: Performance evaluation of min-min and max-min algorithms for job scheduling in federated cloud publication-title: Int. J. Comput. Appl. (0975–8887) – ident: CR7 – volume: 8 start-page: 9 issue: 2 year: 2015 end-page: 14 ident: CR3 article-title: Efficient and enhanced load balancing algorithms in cloud computing publication-title: Int. J. Grid Distrib. Comput. doi: 10.14257/ijgdc.2015.8.2.02 – volume: 17 start-page: 3 issue: 1 year: 2014 end-page: 3 ident: CR19 article-title: Dynamic scheduling based on particle swarm optimization for cloud-based scientific experiments publication-title: CLEI Electron. J. doi: 10.19153/cleiej.17.1.2 – ident: CR23 – ident: CR20 – volume: 3 start-page: 115 issue: 11 year: 2014 end-page: 19 ident: CR5 article-title: A survey of various load balancing algorithms in cloud computing publication-title: Int. J. Sci. Technol. Res. – ident: 1213_CR23 doi: 10.1155/2015/780879 – volume: 16 start-page: 23 issue: 4 year: 2014 ident: 1213_CR4 publication-title: IOSR J. Comput. Eng. doi: 10.9790/0661-16442328 – ident: 1213_CR12 doi: 10.1109/ICHCI-IEEE.2013.6887799 – ident: 1213_CR10 doi: 10.1109/ICECCT.2015.7226080 – volume: 2 start-page: 78 issue: 2 year: 2010 ident: 1213_CR22 publication-title: Int. J. Bio-Inspired Comput. doi: 10.1504/IJBIC.2010.032124 – volume: 9 start-page: 7 issue: 1 year: 2015 ident: 1213_CR9 publication-title: IUP J. Comput. Sci. – volume: 3 start-page: 115 issue: 11 year: 2014 ident: 1213_CR5 publication-title: Int. J. Sci. Technol. Res. – volume: 99 start-page: 47 issue: 18 year: 2014 ident: 1213_CR17 publication-title: Int. J. Comput. Appl. (0975–8887) – ident: 1213_CR11 doi: 10.1007/978-3-319-12286-1_6 – ident: 1213_CR21 doi: 10.5120/908-1286 – volume: 8 start-page: 9 issue: 2 year: 2015 ident: 1213_CR3 publication-title: Int. J. Grid Distrib. Comput. doi: 10.14257/ijgdc.2015.8.2.02 – volume: 17 start-page: 3 issue: 1 year: 2014 ident: 1213_CR19 publication-title: CLEI Electron. J. doi: 10.19153/cleiej.17.1.2 – volume: 5 start-page: 1107 issue: 7 year: 2015 ident: 1213_CR6 publication-title: Int. J. Adv. Res. Comput. Sci. Softw. Eng. – volume: 9 start-page: 379 issue: 7 year: 2014 ident: 1213_CR18 publication-title: Int. J. Comput. Trends Technol. doi: 10.14445/22312803/IJCTT-V9P169 – ident: 1213_CR14 doi: 10.5120/21729-4894 – ident: 1213_CR16 doi: 10.1109/C3IT.2015.7060176 – volume: 18 start-page: 34 issue: 1 year: 2013 ident: 1213_CR8 publication-title: Tsinghua Sci. Technol. doi: 10.1109/TST.2013.6449405 – ident: 1213_CR13 doi: 10.1007/978-3-319-28031-8_6 – volume: 1 start-page: 7 issue: 1 year: 2010 ident: 1213_CR1 publication-title: J. Internet Serv. Appl. doi: 10.1007/s13174-010-0007-6 – volume: 10 start-page: 1156 issue: 7 year: 2014 ident: 1213_CR24 publication-title: J. Comput. Sci. doi: 10.3844/jcssp.2014.1156.1165 – ident: 1213_CR20 – ident: 1213_CR2 – ident: 1213_CR7 doi: 10.1109/SPIN.2015.7095363 – volume: 26 start-page: 1297 issue: 6 year: 2015 ident: 1213_CR15 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-014-1804-9
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SubjectTerms	Algorithms Cloud computing Communication Computer Communication Networks Computer Science Efficiency Energy consumption Heuristic methods Infrastructure Load balancing Operating Systems Particle swarm optimization Polynomials Power Processor Architectures Response time Software Task scheduling Workloads
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