Task processing optimization using cuckoo particle swarm (CPS) algorithm in cloud computing infrastructure
Recently, cloud computing infrastructure (CCI) models have received much attention for their exceptional scalability, dependability, Data Information Sharing (DIS), and low cost rate. There are many hardware and software elements that are accessed over the internet by cloud data centers. Modern data...
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| Published in | Cluster computing Vol. 26; no. 1; pp. 745 - 769 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.02.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1386-7857 1573-7543 |
| DOI | 10.1007/s10586-022-03796-9 |
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| Abstract | Recently, cloud computing infrastructure (CCI) models have received much attention for their exceptional scalability, dependability, Data Information Sharing (DIS), and low cost rate. There are many hardware and software elements that are accessed over the internet by cloud data centers. Modern data centers utilize Virtualization Techniques (VT) to offer a dispersed CI that employs Virtual Machines (VM) based on Physical Hosts (PH). With the increasing number of centers, optimizing energy consumption has become vital to saving costs due to DCC's high energy consumption. In our CPS algorithm, we combine the Cuckoo algorithm and the particle swarm optimization (PSO). It is determined which virtual machine can be assigned to each host, thus choosing the best virtual machine. As a result, if the selected host is overloaded, it is determined which virtual machines are generating high loads and migrated to another host, which is determined based on the cuckoo algorithm and PSO. In testing each algorithm separately, the combination method proved to consume less energy and execute faster than the other methods in the CloudSim simulation environment. Fault tolerance for our network and evaluation of VMs have also been emphasized in vSphereTM. |
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| AbstractList | Recently, cloud computing infrastructure (CCI) models have received much attention for their exceptional scalability, dependability, Data Information Sharing (DIS), and low cost rate. There are many hardware and software elements that are accessed over the internet by cloud data centers. Modern data centers utilize Virtualization Techniques (VT) to offer a dispersed CI that employs Virtual Machines (VM) based on Physical Hosts (PH). With the increasing number of centers, optimizing energy consumption has become vital to saving costs due to DCC's high energy consumption. In our CPS algorithm, we combine the Cuckoo algorithm and the particle swarm optimization (PSO). It is determined which virtual machine can be assigned to each host, thus choosing the best virtual machine. As a result, if the selected host is overloaded, it is determined which virtual machines are generating high loads and migrated to another host, which is determined based on the cuckoo algorithm and PSO. In testing each algorithm separately, the combination method proved to consume less energy and execute faster than the other methods in the CloudSim simulation environment. Fault tolerance for our network and evaluation of VMs have also been emphasized in vSphereTM. |
| Author | Li, Yuan Rostami, Ali Shokouhi Javadpour, Amir Nasseri, Seyed Hadi Ja’fari, Forough Zavieh, Hadi |
| Author_xml | – sequence: 1 givenname: Hadi surname: Zavieh fullname: Zavieh, Hadi organization: School of Economics and Statistics, Guangzhou University – sequence: 2 givenname: Amir surname: Javadpour fullname: Javadpour, Amir email: a_javadpour@e.gzhu.edu.cn organization: Department of Computer Science and Technology (Cyberspace Security), Harbin Institute of Technology, ADiT-Lab, Electrotechnics and Telecommunications Department, Instituto Politécnico de Viana do Castelo – sequence: 3 givenname: Yuan surname: Li fullname: Li, Yuan email: mathly@gzhu.edu.cn organization: School of Economics and Statistics, Guangzhou University – sequence: 4 givenname: Forough surname: Ja’fari fullname: Ja’fari, Forough organization: Department of Computer Engineering, Sharif University of Technology – sequence: 5 givenname: Seyed Hadi surname: Nasseri fullname: Nasseri, Seyed Hadi organization: Department of Mathematics, University of Mazandaran, Foshan University, Sharif University of Technology – sequence: 6 givenname: Ali Shokouhi surname: Rostami fullname: Rostami, Ali Shokouhi organization: Department of Communication Engineering, University of Sistan and Baluchestan |
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| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Cloud computing Fault tolerance Virtual machine migration Task processing Cuckoo algorithm PSO |
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