Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment
Resource scheduling is a procedure for the distribution of resources over time to perform a required task and a decision making process in cloud computing. Optimal resource scheduling is a great challenge and considered to be an NP-hard problem due to the fluctuating demand of cloud users and dynami...
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my.utm.876032020-11-30T09:06:13Z http://eprints.utm.my/id/eprint/87603/ Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment Madni, Syed Hamid Hussain Abd. Latiff, Muhammad Shafie Abdulhamid, Shafi’i Muhammad Ali, Javed QA75 Electronic computers. Computer science Resource scheduling is a procedure for the distribution of resources over time to perform a required task and a decision making process in cloud computing. Optimal resource scheduling is a great challenge and considered to be an NP-hard problem due to the fluctuating demand of cloud users and dynamic nature of resources. In this paper, we formulate a new hybrid gradient descent cuckoo search (HGDCS) algorithm based on gradient descent (GD) approach and cuckoo search (CS) algorithm for optimizing and resolving the problems related to resource scheduling in Infrastructure as a Service (IaaS) cloud computing. This work compares the makespan, throughput, load balancing and performance improvement rate of existing meta-heuristic algorithms with proposed HGDCS algorithm applicable for cloud computing. In comparison with existing meta-heuristic algorithms, proposed HGDCS algorithm performs well for almost in both cases (Case-I and Case-II) with all selected datasets and workload archives. HGDCS algorithm is comparatively and statistically more effective than ACO, ABC, GA, LCA, PSO, SA and original CS algorithms in term of problem solving ability in accordance with results obtained from simulation and statistical analysis. Springer New York LLC 2019-03-15 Article PeerReviewed Madni, Syed Hamid Hussain and Abd. Latiff, Muhammad Shafie and Abdulhamid, Shafi’i Muhammad and Ali, Javed (2019) Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment. Cluster Computing, 22 (1). pp. 301-334. ISSN 1386-7857 http://dx.doi.org/10.1007/s10586-018-2856-x DOI:10.1007/s10586-018-2856-x |
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QA75 Electronic computers. Computer science Madni, Syed Hamid Hussain Abd. Latiff, Muhammad Shafie Abdulhamid, Shafi’i Muhammad Ali, Javed Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
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Resource scheduling is a procedure for the distribution of resources over time to perform a required task and a decision making process in cloud computing. Optimal resource scheduling is a great challenge and considered to be an NP-hard problem due to the fluctuating demand of cloud users and dynamic nature of resources. In this paper, we formulate a new hybrid gradient descent cuckoo search (HGDCS) algorithm based on gradient descent (GD) approach and cuckoo search (CS) algorithm for optimizing and resolving the problems related to resource scheduling in Infrastructure as a Service (IaaS) cloud computing. This work compares the makespan, throughput, load balancing and performance improvement rate of existing meta-heuristic algorithms with proposed HGDCS algorithm applicable for cloud computing. In comparison with existing meta-heuristic algorithms, proposed HGDCS algorithm performs well for almost in both cases (Case-I and Case-II) with all selected datasets and workload archives. HGDCS algorithm is comparatively and statistically more effective than ACO, ABC, GA, LCA, PSO, SA and original CS algorithms in term of problem solving ability in accordance with results obtained from simulation and statistical analysis. |
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Article |
author |
Madni, Syed Hamid Hussain Abd. Latiff, Muhammad Shafie Abdulhamid, Shafi’i Muhammad Ali, Javed |
author_facet |
Madni, Syed Hamid Hussain Abd. Latiff, Muhammad Shafie Abdulhamid, Shafi’i Muhammad Ali, Javed |
author_sort |
Madni, Syed Hamid Hussain |
title |
Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
title_short |
Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
title_full |
Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
title_fullStr |
Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
title_full_unstemmed |
Hybrid gradient descent cuckoo search (HGDCS) algorithm for resource scheduling in IaaS cloud computing environment |
title_sort |
hybrid gradient descent cuckoo search (hgdcs) algorithm for resource scheduling in iaas cloud computing environment |
publisher |
Springer New York LLC |
publishDate |
2019 |
url |
http://eprints.utm.my/id/eprint/87603/ http://dx.doi.org/10.1007/s10586-018-2856-x |
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13.18916 |