Scheduling of scientific workflows using a chaos-genetic algorithm

Fard, Golnar Gharooni; Moein-darbari, Fahime; Deldari, Hossein; Morvaridi, Anahita

doi:10.1016/j.procs.2010.04.160

Cited by 61 publications

(17 citation statements)

References 10 publications

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“…The results of the evaluation of the proposed algorithm with the two algorithms of [6] GA and [7] Genetic-Variable neighborhood search for scheduling independent tasks are presented in this section. All experiments have been done on a system running Windows XP operating system with configuration of 3 GHz CPU and 4GB of RAM.…”

Section: Discussionmentioning

confidence: 99%

“…The proposed scheduling is compared with two algorithms of [6] GA and [7] Genetic-Variable neighborhood search with regard to the parameters of time and cost. The results are investigated based on cost and user requests in different charts.…”

Section: Discussionmentioning

confidence: 99%

“…In fact, Vid has the likelihood of zero or one of Xid instead of indicating the speed in binary version. Its formula uses equation (6) to update the position of each dimension [10] …”

Section: Local Search Algorithms Following Binary Gravitational Attramentioning

confidence: 99%

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Proposing a scheduling algorithm to balance the time and cost using a genetic algorithm

Faraj¹,

Abadi²

2015

IJCATR

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Grid computing is a hardware and software infrastructure and provides affordable, sustainable, and reliable access. Its aim is to create a supercomputer using free resources. One of the challenges to the Grid computing is scheduling problem which is regarded as a tough issue. Since scheduling problem is a non-deterministic issue in the Grid, deterministic algorithms cannot be used to improve scheduling. In this paper, a combination of genetic algorithms and binary gravitational attraction is used for scheduling problem solving, where the reduction in the duty performance timing and cost-effective use of simultaneous resources are investigated. In this case, the user determines the execution time parameter and cost-effective use of resources. In this algorithm, a new approach that has led to a balanced load of resources is used in the selection of resources. Experimental results reveals that our proposed algorithm in terms of cost-time and selection of the best resource has reached better results than other algorithm.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Proposing a scheduling algorithm to balance the time and cost using a genetic algorithm

Faraj¹,

Abadi²

2015

IJCATR

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“…The combine points of genetic algorithm ratings with turbulent variables have allowed the solutions generated by this algorithm to be distributed throughout the search space and prevent early convergence of the algorithm. Better designs and products are obtained in shorter time and to get it the algorithm converges to a faster rate [2].…”

Section: Response Timementioning

confidence: 99%

Modeling and Evaluation of Intelligent Monitoring Systems at Urban Intersections to Improve Real-Time Monitoring of Congestion and Traffic Safety

Fatholahzadeh¹,

Akbarizadeh²,

Romoozi³

2018

IJCATR

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Abstract:In recent decades, with the advent of technology and information technology, transportation systems have also been moving in this direction, and one of the challenges of the transportation system is due to the multiplicity and increase of vehicle management and control. Many techniques and methods have been proposed in this field that in today's world, the use of intelligent systems has a higher efficiency. In fact, safety has the ability to reduce the number of vehicles with minimal delay and create discomfort for the users depends directly in order and arrangement to facilitate the immediate and direct involvement of the vehicle in traffic flow. One of the ways to demonstrate the efficiency of intelligent monitoring systems is create model before the implementation phase. This article aims at modeling and evaluating an intelligent surveillance system at urban intersections, which is carried out using colored petri nets. In the proposed method, first, the urban intersection architecture is described with the benefit of traffic rules then, the inconsistency and coincidence states are determined and finally, reliability and response time are measured by the CpnTools with the help of Petri Nets. The results show that the intelligent monitoring equipment related to the intelligent surveillance system increases the safety of the road network and, finally, has secured and fluent traffic.

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“…The performance here is analyzed by both qualitatively and quantitatively. Honey bee behavior is inspired load balancing of tasks in cloud computing environments [3]. In this paper, it has been examine the behavior of Honey Bee which inspired load balancing algorithm that was proposed with the aim to achieve well balanced load across virtual machines to maximize the throughput as well as to balance the priorities of the incoming tasks on the VMs.…”

Section: Literature Surveymentioning

confidence: 99%

An Improvised Scheduling Algorithm in Cloud Environment

Bajaj¹,

Sharma²

2017

IJCA

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The term scheduling implies relegating of the responsibilities to the accessible assets in some model design to finish the entire work. The target of the proposed work is to investigate the existing weighted round robin algorithm and propose a credulous methodology that defeats the downside of the existing algorithm and by consolidating both the analysis and make an enhance model which is more efficient and satisfy the user needs. The existing algorithm is not productive because of vast reaction time, high completion time, extensive turnaround time, high no. of task migration. Objective of this work is to evaluate the proposed scheduling algorithm by considering the capacities of the VM. The proposed algorithm also holds the benefits of the existing and defeating the issues. The algorithm has been compared with Weighted Round Robin(WRR) and Length based WRR it was observed that the Proposed WRR performed better than existing WRR and LWRR. Proposed WRR showed 99% improvement in Finish time over WRR. 20% and 40% improvement was observed in Task migration and Task delayed respectively over LWRR.

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Scheduling of scientific workflows using a chaos-genetic algorithm

Cited by 61 publications

References 10 publications

Proposing a scheduling algorithm to balance the time and cost using a genetic algorithm

Proposing a scheduling algorithm to balance the time and cost using a genetic algorithm

Modeling and Evaluation of Intelligent Monitoring Systems at Urban Intersections to Improve Real-Time Monitoring of Congestion and Traffic Safety

An Improvised Scheduling Algorithm in Cloud Environment

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