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Pareto Front Based Realistic Soft Real-Time Task Scheduling with Multi-objective Genetic Algorithm in Unstructured Heterogeneous Distributed System [chapter]

Nafiseh Sedaghat, Hamid Tabatabaee-Yazdi, Mohammad-R Akbarzadeh-T
2010 Lecture Notes in Computer Science  
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]

Bhupesh Kumar Mishra, Thepparit Sinthamrongruk, Zeeshan Pervez, Keshav Dahal
2017 Lecture Notes in Electrical Engineering  
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

B. Gomathi, S. T. Suganthi, Karthikeyan Krishnasamy, J. Bhuvana
2021 Computers Materials & Continua  
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

Saurabh Bilgaiyan, Santwana Sagnika, Madhabananda Das
2014 International Journal of Computer Applications  
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]

Jürgen Sauer
2006 Planning in Intelligent Systems  
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  
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

Saurabh Bilgaiyan, Santwana Sagnika, Samaresh Mishra, Madhabananda Das
2015 International Journal of Modern Education and Computer Science  
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

Shahbaz Afzal, G. Kavitha
2019 Journal of Cloud Computing: Advances, Systems and Applications  
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"

Ling Wang, Guohua Wu, Liang Gao
2019 Memetic Computing  
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

Devarajan Rajeswari, Veerabadran Jawahar Senthilkumar
2016 Circuits and Systems  
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]

Yacine Kessaci, Mohand Mezmaz, Nouredine Melab, El-Ghazali Talbi, Daniel Tuyttens
2011 Studies in Computational Intelligence  
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

Arunkumar Panneerselvam, Bhuvaneswari Subbaraman
2018 International Journal of Engineering & Technology  
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

R.K. Jena
2015 Procedia Computer Science  
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

Ishfaq Ahmad, Sanjay Ranka, Samee Ullah Khan
2008 Proceedings, International Parallel and Distributed Processing Symposium (IPDPS)  
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

S. Sheikh, A. Nagaraju
2017 Indian Journal of Science and Technology  
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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