Ant Colony Optimization Algorithm For Load Balancing In Grid Computing Uum Press
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Ant Colony Optimization Algorithm For Load Balancing In Grid Computing Uum Press
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Author : Ku Ruhana Ku Mahamud
language : en
Publisher: UUM Press
Release Date : 2012-01-01
Ant Colony Optimization Algorithm For Load Balancing In Grid Computing Uum Press written by Ku Ruhana Ku Mahamud and has been published by UUM Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with Computers categories.
Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. The proposed algorithm is known as the enhance Ant Colony Optimization (EACO). The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. The resource allocation problem is modelled as a graph that can be used by the ant to deliver its pheromone. This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element. The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job. EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. Experimental results show that EACO produced better grid resource management solution.
Load Balancing Using Enhanced Ant Algorithm In Grid Computing
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Author : Husna Jamal Abdul Nasir
language : en
Publisher:
Release Date : 2010
Load Balancing Using Enhanced Ant Algorithm In Grid Computing written by Husna Jamal Abdul Nasir and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
An Ant Colony Optimization Algorithm For Load Balancing In Parallel Machines With Sequence Dependent Setup Times
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Author : Timur Keskinturk
language : en
Publisher:
Release Date : 2012
An Ant Colony Optimization Algorithm For Load Balancing In Parallel Machines With Sequence Dependent Setup Times written by Timur Keskinturk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
This study introduces the problem of minimizing average relative percentage of imbalance (ARPI) with sequence-dependent setup times in a parallel-machine environment. A mathematical model that minimizes ARPI is proposed. Some heuristics, and two metaheuristics, an ant colony optimization algorithm and a genetic algorithm are developed and tested on various random data. The proposed ant colony optimizationmethod outperforms heuristics and genetic algorithm. On the other hand, heuristics using the cumulative processing time obtain better results than heuristics using setup avoidance and a hybrid rule in assignment.
Quantum Particle Swarm Optimization Technique For Load Balancing In Cloud Computing
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Author : Elrasheed Ismail Sultan
language : en
Publisher:
Release Date : 2013
Quantum Particle Swarm Optimization Technique For Load Balancing In Cloud Computing written by Elrasheed Ismail Sultan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Logic programming categories.
Cloud Computing systems are widely applied in many fields such as communication data management, web application, network monitoring, financial management and so on. The distributed Cloud Computing technology has been produced as the development of the computer network and distributed computing technology. Researches on data Cloud Computing become the necessary trend in the distributed Cloud Computing system domain since the sources and application of the data are distributed and the scale of the applications enlarges quickly. Load management is the focus of research in both of the area in distributed Cloud Computing systems and centralized Cloud Computing systems. Although researches on the load management in the cloud systems is similar to that of traditional parallel and distributed systems in many aspects, essential differences exist between them. The choice of a scheduling strategy has significant impact on the runtime Central Processing Unit, memory consumption as well as the storage systems. Load balancing optimization techniques such as Ant Colony Optimization (ACO), First Come First Served (FCFS), Round Robin (RR) and Particle Swarm Optimization (PSO) are popular techniques being used for scheduling and load balancing. However, these techniques have its weaknesses in terms of minimizing makespan, computation cost and communication cost. In this study, load balancing technique in Cloud Computing called Quantum Particle Swarm Optimization (QPSO) technique proposed by considering only minimization of makespan, computation cost and communication cost. Performance of the QPSO technique based on many heuristic algorithms it is comprised the following steps. Firstly, tasks are assigned averagely to the machines according to a special initialization policy. Then the optimal criterion for exchanging tasks between two machines is proposed and exploited to speed up the improving process towards load balance. Secondly, this thesis proposes job-combination based static algorithm for load balancing where all jobs should organized into the standard job combinations, each task of which consists of one to four jobs. Then they are assigned to the machines according to the assignment algorithm for job combinations, which is a special integer partition algorithm. Finally, the result of experiment shows that QPSO can achieve at least three times cost saving as compared with ACO, FCFS, RR and PSO.
Ant Colony Optimization Algorithms
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-07-01
Ant Colony Optimization Algorithms written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-01 with Computers categories.
What Is Ant Colony Optimization Algorithms The Ant Colony Optimization Algorithm, also known as ACO, is a probabilistic technique for addressing computational problems in the fields of computer science and operations research. These problems can be boiled down to the task of finding good paths through graphs. The behavior of natural ants served as inspiration for the development of multi-agent systems, which are represented by artificial ants. The communication of biological ants through the use of pheromones is frequently the major paradigm that is adopted. Combinations of artificial ants and local search algorithms have become the technique of choice for several optimization tasks involving some kind of graph, such as internet routing and vehicle routing. This is because these combinations are able to find optimal solutions more quickly than traditional methods. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Ant colony optimization algorithms Chapter 2: Job-shop scheduling Chapter 3: Open-shop scheduling Chapter 4: Quadratic assignment problem Chapter 5: Generalized assignment problem Chapter 6: Set cover problem Chapter 7: Partition problem Chapter 8: Bankruptcy prediction Chapter 9: Protein-protein interaction Chapter 10: Protein folding (II) Answering the public top questions about ant colony optimization algorithms. (III) Real world examples for the usage of ant colony optimization algorithms in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of ant colony optimization algorithms. What is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Ant Colony Optimization Algorithm For Dynamic Scheduling For Jobs In Computational Grid
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Author :
language : en
Publisher:
Release Date : 2012
Ant Colony Optimization Algorithm For Dynamic Scheduling For Jobs In Computational Grid written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Ant algorithm categories.
Load Balancing In A Distributed Network Environment
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Author : Neeharika Veerisetty
language : en
Publisher:
Release Date : 2013
Load Balancing In A Distributed Network Environment written by Neeharika Veerisetty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Ant algorithms categories.
A Unified Ant Colony Optimization Algorithm For Continuous Optimization
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Author : Tianjun Liao
language : en
Publisher:
Release Date : 2013
A Unified Ant Colony Optimization Algorithm For Continuous Optimization written by Tianjun Liao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Design Implementation And Performance Analysis Of The Ant Colony Optimization Algorithm For Routing In Ad Hoc Network
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Author : Mohammad Towhidul Islam
language : en
Publisher:
Release Date : 2004
Design Implementation And Performance Analysis Of The Ant Colony Optimization Algorithm For Routing In Ad Hoc Network written by Mohammad Towhidul Islam and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
The Utilization Of The Ant Colony Optimization Technique As An Efficient Solution To The Task Scheduling Problem In Heterogeneous Multiprocessor Computing Environments
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Author : Nekiesha Shantelle Edward
language : en
Publisher:
Release Date : 2016
The Utilization Of The Ant Colony Optimization Technique As An Efficient Solution To The Task Scheduling Problem In Heterogeneous Multiprocessor Computing Environments written by Nekiesha Shantelle Edward and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Algorithms categories.