Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of rese...

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Autores principales:	Fatma Mbarek, Volodymyr Mosorov
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ant colony optimization nearest-neighbor load balancing hybrid nearest-neighbor ant colony optimization distributed computing systems Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/93e483ec9f494432abe2736c8ba4ea41
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spelling	oai:doaj.org-article:93e483ec9f494432abe2736c8ba4ea412021-11-25T16:38:30ZHybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management10.3390/app1122108072076-3417https://doaj.org/article/93e483ec9f494432abe2736c8ba4ea412021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10807https://doaj.org/toc/2076-3417Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of research. Dynamic load balancing is feasible in distributed computing systems since it is a significant key to maintaining stability of heterogeneous distributed computing systems (HDCS). The challenge of load balancing is an objective function of optimization with exponential complexity of solutions. The problem of dynamic load balancing raises with the scale of the HDCS and it is hard to tackle effectively. The solution to this unsolvable issue is being explored under a particular algorithm paradigm. A new codification strategy, namely hybrid nearest-neighbor ant colony optimization (ACO-NN), which, based on the metaheuristic ant colony optimization (ACO) and an approximate nearest-neighbor (NN) approaches, has been developed to establish a dynamic load balancing algorithm for distributed systems. Several experiments have been conducted to explore the efficiency of this stochastic iterative load balancing algorithm; it is tested with task and nodes accessibility and proved to be effective with diverse performance metrics.Fatma MbarekVolodymyr MosorovMDPI AGarticleant colony optimizationnearest-neighborload balancinghybrid nearest-neighbor ant colony optimizationdistributed computing systemsTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10807, p 10807 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ant colony optimization nearest-neighbor load balancing hybrid nearest-neighbor ant colony optimization distributed computing systems Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	ant colony optimization nearest-neighbor load balancing hybrid nearest-neighbor ant colony optimization distributed computing systems Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Fatma Mbarek Volodymyr Mosorov Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
description	Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of research. Dynamic load balancing is feasible in distributed computing systems since it is a significant key to maintaining stability of heterogeneous distributed computing systems (HDCS). The challenge of load balancing is an objective function of optimization with exponential complexity of solutions. The problem of dynamic load balancing raises with the scale of the HDCS and it is hard to tackle effectively. The solution to this unsolvable issue is being explored under a particular algorithm paradigm. A new codification strategy, namely hybrid nearest-neighbor ant colony optimization (ACO-NN), which, based on the metaheuristic ant colony optimization (ACO) and an approximate nearest-neighbor (NN) approaches, has been developed to establish a dynamic load balancing algorithm for distributed systems. Several experiments have been conducted to explore the efficiency of this stochastic iterative load balancing algorithm; it is tested with task and nodes accessibility and proved to be effective with diverse performance metrics.
format	article
author	Fatma Mbarek Volodymyr Mosorov
author_facet	Fatma Mbarek Volodymyr Mosorov
author_sort	Fatma Mbarek
title	Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
title_short	Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
title_full	Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
title_fullStr	Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
title_full_unstemmed	Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management
title_sort	hybrid nearest-neighbor ant colony optimization algorithm for enhancing load balancing task management
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/93e483ec9f494432abe2736c8ba4ea41
work_keys_str_mv	AT fatmambarek hybridnearestneighborantcolonyoptimizationalgorithmforenhancingloadbalancingtaskmanagement AT volodymyrmosorov hybridnearestneighborantcolonyoptimizationalgorithmforenhancingloadbalancingtaskmanagement
_version_	1718413090030092288

Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

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