Search Results - (( job application ((use algorithm) OR (bees algorithm)) ) OR ( its application _ algorithm ))*
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Multi objective bee colony optimization framework for grid job scheduling
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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Conference or Workshop Item -
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid
Published 2012“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Monograph -
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Impatient job scheduling under cloud computing
Published 2012“…The limitations of those algorithms were addressed and this leads to the proposition of an algorithm that has the ability to map the impatient jobs to virtual machines near its input, output, application, or forth party. …”
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Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Experimental performance analysis of job scheduling algorithms on computational grid using real workload traces
Published 2017“…Grid, an infrastructure for resource sharing, currently has shown its importance in many scientific applications requiring tremendously high computational power. …”
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Article -
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New heuristic function in ant colony system for job scheduling in grid computing
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Conference or Workshop Item -
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Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm
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Comparison of path planning in simulated robot
Published 2020“…This is because each path planning algorithm has its own applicable domain, performance, advantages and disadvantages in various situations. …”
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Final Year Project / Dissertation / Thesis -
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A conflict-based priority dispatching rule and operation-based approaches to job shops
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Citation Index Journal -
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Modelling refers to constructing a model to depict the structure of the application with its tasks and describing the interactions between them. …”
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Bee foraging behaviour techniques for grid scheduling problem
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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Article -
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing
Published 2013“…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. …”
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Thesis