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Pareto Front Based Realistic Soft Real-Time Task Scheduling with Multi-objective Genetic Algorithm in Unstructured Heterogeneous Distributed System
[chapter]
2010
Lecture Notes in Computer Science
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Communication contention in APN list scheduling algorithm ( ...
DAG; Distributed system; Edge scheduling; Genetic algorithm; Heterogeneous system; Link
contention; Multi-objective Optimization; Precedence constraint; Real time system; Routing;
Soft real time; ...
To optimize objectives, we use Pareto front based technique, vector based method. ...
doi:10.1007/978-3-642-13067-0_30
fatcat:rfyqy2ztnjgv3edjxjtesx6sgq
Survey on Models and Methodology for Emergency Relief and Staff Scheduling
[chapter]
2017
Lecture Notes in Electrical Engineering
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Multiple objectives in terms of cost, timing window, priorities and travel routes are the driving factors in the scheduling task. ...
The stochastic scenarios and uncertainty in demands make the scheduling task complex. ...
For solving problem of emergency transportation scheduling in the relief supply chains, a multi-objective fuzzy optimization was applied by Zheng et al. ...
doi:10.1007/978-3-319-52171-8_1
fatcat:myay3hgpevf7niclbqug4w76pm
Monarch Butterfly Optimization for Reliable Scheduling in Cloud
2021
Computers Materials & Continua
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In this paper, Multi-Objective Improved Monarch Butterfly Optimization (MOIMBO) algorithm is applied to solve multi-objective task scheduling problems in the cloud in preparation for Pareto optimal solutions ...
The scheduling of the cloud tasks is a well-recognized NP-hard problem. The Task scheduling problem is convoluted while convincing different objectives, which are dispute in nature. ...
Funding Statement: The authors received no specific funding for this study.
Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study. ...
doi:10.32604/cmc.2021.018159
fatcat:sfzblz4ygfhwjpgbwgw5fd4dsy
An Analysis of Task Scheduling in Cloud Computing using Evolutionary and Swarm-based Algorithms
2014
International Journal of Computer Applications
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This paper analyzes various evolutionary and swarm based task scheduling algorithms that address the above mentioned problem. ...
So there is a requirement of appropriate scheduling of tasks which will help to manage the escalating costs of data intensive applications. ...
A REVIEW OF OPTIMIZATION TECHNIQUES FOR TASK SCHEDULING The efficiency of task scheduling directly affects the performance of the system. ...
doi:10.5120/15473-4158
fatcat:f6zqwehlq5cidey2yszxzsj35a
Modeling and Solving Multisite Scheduling Problems
[chapter]
2006
Planning in Intelligent Systems
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This paper presents an approach that adopts modeling and problem solving techniques used for local scheduling problems for the new global scheduling problems. ...
In the multi site-scheduling scenario we differentiate between a global and a local scheduling level. ...
The prototypical multi-site scheduling system (MUSTsystem) supports all the scheduling and coordination tasks of a distributed production environment. ...
doi:10.1002/0471781266.ch9
fatcat:447p5ecpmrhz3nuk5oqhuf5bv4
An Automated Task Scheduling Model Using a Multi-objective Improved Cuckoo Optimization Algorithm
2022
International Journal of Intelligent Engineering and Systems
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In this paper, we first propose an optimization model based on a Multi-Objective Improved Cuckoo Search Algorithm (MOICS) to optimize task scheduling problems in a cloud environment this reduces both the ...
Then there's the discrete multi-objective task scheduling problem to solve, as well as automatically assigning work to cloud nodes. ...
The contributions for the MOICS algorithm are: • Our approach formulates the task-scheduling problem as a multi-objective optimization problem in a cloud system, intending to reduce total execution durations ...
doi:10.22266/ijies2022.0228.27
fatcat:jaf32y2fqfakfojsvie3ae2hni
Study of Task Scheduling in Cloud Computing Environment Using Soft Computing Algorithms
2015
International Journal of Modern Education and Computer Science
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This paper gives a comprehensive survey on such problems and provide a detailed analysis of some best scheduling techniques from the domain of soft computing with their performance in cloud computing. ...
So there must be some intelligent distribution of user's work on the available resources which will result in an optimized computing environment. ...
Lizheng [9] proposed a Particle swarm optimization techniques for multi objective task assignment in cloud computing environment. ...
doi:10.5815/ijmecs.2015.03.05
fatcat:f3ze6c3nwnemzfwchipts6kqqq
Load balancing in cloud computing – A hierarchical taxonomical classification
2019
Journal of Cloud Computing: Advances, Systems and Applications
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Load unbalancing problem is a multi-variant, multi-constraint problem that degrades performance and efficiency of computing resources. ...
Load balancing techniques cater the solution for load unbalancing situation for two undesirable facets-overloading and under-loading. ...
Acknowledgements The authors are grateful to the editor and anonymous referees for their valuable comments and suggestions. Only the authors are responsible for the views expressed and mistakes made. ...
doi:10.1186/s13677-019-0146-7
fatcat:3w7nv5srfbbjjlp4jl3s55hrlq
Thematic issue on "advanced intelligent scheduling algorithms for smart manufacturing systems"
2019
Memetic Computing
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The first paper titled "An improved differential evolution algorithm for solving a distributed assembly flexible job shop scheduling problem" by Wu et al. proposes a multi-objective memetic algorithm by ...
After a double-blinded peer-review process, seven papers have been accepted and B Ling Wang included in this issue, covering various innovative intelligent optimization techniques for different kinds of ...
Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ...
doi:10.1007/s12293-019-00297-y
fatcat:akjwpjwdije7zhgqlyn6gkdioy
Minimizing Time in Scheduling of Independent Tasks Using Distance-Based Pareto Genetic Algorithm Based on MapReduce Model
2016
Circuits and Systems
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In DS, most of the task scheduling problem is formulated as multi-objective optimization problem. This paper aims to develop the optimal schedules by minimizing makespan and flow time simultaneously. ...
Distributed Systems (DS) have a collection of heterogeneous computing resources to process user tasks. ...
These characteristics of GA used to find the best optimal schedule for multi-objective problem in distributed systems. ...
doi:10.4236/cs.2016.76063
fatcat:rqmx7o76evanrc3cn2mtq6olru
Parallel Evolutionary Algorithms for Energy Aware Scheduling
[chapter]
2011
Studies in Computational Intelligence
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In computing systems, minimizing energy consumption can significantly reduces the amount of energy bills. The demand for computing systems steadily increases and the cost of energy continues to rise. ...
In terms of completion time, the obtained schedules are also shorter than those of other algorithms. ...
We would like to thank the technical staffs of the Grid'5000 and the clusters of University of Mons for making their clusters accessible and fully operational. ...
doi:10.1007/978-3-642-21271-0_4
fatcat:sejk7d5dnrefzmmcji4zzm5xgy
Multi-Objective Optimization for scientific workflow task scheduling in IaaS Cloud
2018
International Journal of Engineering & Technology
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This paper explores the multi-objective optimization applications in scientific workflow task scheduling in IaaS cloud and the related algorithms employed. ...
Traditional computer networks are not suitable for handling scientific applications and hence ubiquitous distributed networks like cloud are prominent in hosting scientific applications. ...
Acknowledgement The corresponding author would like to thank Pondicherry University for providing UGC Non-Net fellowship for carrying out his research work. ...
doi:10.14419/ijet.v7i4.6.20457
fatcat:6nwjwrxhcbc67iletcd6jycwhy
Multi Objective Task Scheduling in Cloud Environment Using Nested PSO Framework
2015
Procedia Computer Science
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This paper focuses on task scheduling using a multi-objective nested Particle Swarm Optimization(TSPSO) to optimize energy and processing time. ...
Finally, the results were compared to existing scheduling algorithms and found that the proposed algorithm (TSPSO) provide an optimal balance results for multiple objectives. ...
This is known as the concept of pareto-optimality. In order to deal with the multi-objective nature of task scheduling problem, a multi-objective PSO based framework was proposed. ...
doi:10.1016/j.procs.2015.07.419
fatcat:tv24fxnelndjbevrehnp4vywtu
Using game theory for scheduling tasks on multi-core processors for simultaneous optimization of performance and energy
2008
Proceedings, International Parallel and Distributed Processing Symposium (IPDPS)
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In this paper, we address the problem of power-aware scheduling/mapping of tasks onto heterogeneous and homogeneous multi-core processor architectures. ...
The objective of scheduling is to minimize the energy consumption as well as the makespan of computationally intensive problems. ...
For such a multi-objectives optimization problem, there is no unique solution [8] . Figure 2 illustrates the concept of the MOO problem with conflicting objective functions. ...
doi:10.1109/ipdps.2008.4536420
dblp:conf/ipps/AhmadRK08
fatcat:4krzdxkrsvhnfj6symdpjiyofi
A Comparative Study of Task Scheduling and Load Balancing Techniques with MCT using ETC on Computational Grids
2017
Indian Journal of Science and Technology
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Objectives: In this paper various task scheduling algorithm along with load distribution techniques investigated to ensure efficient mapping of tasks to resources and for coherent resource utilization ...
Considered parameters for comparisons are scheduling approaches, techniques, findings, benefits, pros and cons. ...
In a view of task scheduling the main objective of multi objective optimization is load balancing, minimizing make span time and cost. ...
doi:10.17485/ijst/2017/v10i32/110751
fatcat:modlvzdrmrdtvix57sriqfzqgi
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