An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud
In recent days, resource allocation is considered to be a complex task in cloud systems. The heuristics models will allocate the resources efficiently in different machines. Then, the fitness function estimation plays a vital role in cloud load balancing, which is mainly used to minimize power consu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-03-01
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| Series: | Cybernetics and Information Technologies |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/cait-2023-0009 |
| _version_ | 1797815462103351296 |
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| author | Ilankumaran Arivumathi Narayanan Swathi Jamjala |
| author_facet | Ilankumaran Arivumathi Narayanan Swathi Jamjala |
| author_sort | Ilankumaran Arivumathi |
| collection | DOAJ |
| description | In recent days, resource allocation is considered to be a complex task in cloud systems. The heuristics models will allocate the resources efficiently in different machines. Then, the fitness function estimation plays a vital role in cloud load balancing, which is mainly used to minimize power consumption. The optimization technique is one of the most suitable options for solving load-balancing problems. This work mainly focuses on analyzing the impacts of using the Genetic Algorithm and Ant Colony Optimization (GAACO) technique for obtaining the optimal solution to efficiently balance the loads across the cloud systems. In addition to that, the GA and ACO are the kinds of object heuristic algorithms being proposed in the work to increase the number of servers that are operated with better energy efficiency. In this work, the main contribution of the GAACO algorithm is to reduce energy consumption, makespan time, response time, and degree of imbalance. |
| first_indexed | 2024-03-13T08:23:03Z |
| format | Article |
| id | doaj.art-c54b4420e67841e9a6d14710f15184a5 |
| institution | Directory Open Access Journal |
| issn | 1314-4081 |
| language | English |
| last_indexed | 2024-03-13T08:23:03Z |
| publishDate | 2023-03-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Cybernetics and Information Technologies |
| spelling | doaj.art-c54b4420e67841e9a6d14710f15184a52023-05-31T06:59:54ZengSciendoCybernetics and Information Technologies1314-40812023-03-0123116117710.2478/cait-2023-0009An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for CloudIlankumaran Arivumathi0Narayanan Swathi Jamjala11School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India1School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, IndiaIn recent days, resource allocation is considered to be a complex task in cloud systems. The heuristics models will allocate the resources efficiently in different machines. Then, the fitness function estimation plays a vital role in cloud load balancing, which is mainly used to minimize power consumption. The optimization technique is one of the most suitable options for solving load-balancing problems. This work mainly focuses on analyzing the impacts of using the Genetic Algorithm and Ant Colony Optimization (GAACO) technique for obtaining the optimal solution to efficiently balance the loads across the cloud systems. In addition to that, the GA and ACO are the kinds of object heuristic algorithms being proposed in the work to increase the number of servers that are operated with better energy efficiency. In this work, the main contribution of the GAACO algorithm is to reduce energy consumption, makespan time, response time, and degree of imbalance.https://doi.org/10.2478/cait-2023-0009load balancingenergy consumptiongenetic algorithmant colony optimization algorithmcloud computing |
| spellingShingle | Ilankumaran Arivumathi Narayanan Swathi Jamjala An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud Cybernetics and Information Technologies load balancing energy consumption genetic algorithm ant colony optimization algorithm cloud computing |
| title | An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud |
| title_full | An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud |
| title_fullStr | An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud |
| title_full_unstemmed | An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud |
| title_short | An Energy-Aware QoS Load Balance Scheduling Using Hybrid GAACO Algorithm for Cloud |
| title_sort | energy aware qos load balance scheduling using hybrid gaaco algorithm for cloud |
| topic | load balancing energy consumption genetic algorithm ant colony optimization algorithm cloud computing |
| url | https://doi.org/10.2478/cait-2023-0009 |
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