A Unified Scheduling Algorithm for Grid Applications

Aggarwal, Akshai; Aggarwal, Mona

doi:10.1109/hpcs.2006.10

Cited by 8 publications

(5 citation statements)

References 23 publications

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“…Aggarwal and Aggarwal [17] propose the UGSA (Unified Grid Scheduling Algorithm), which considers the system workload and the communication latency to schedule jobs. Applications are mapped in DAGs (Directed Acyclic Graph) which helps to define how processes will be allocated on processors.…”

Section: Related Workmentioning

confidence: 99%

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On Simulated Annealing for the Scheduling of Parallel Applications

Mello¹,

Senger

2008

2008 20th International Symposium on Computer Architecture and High Performance Computing

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A grid scheduling algorithm inspired on the simulated annealing meta-heuristic (SA) is presented. Guided by predictions about parallel applications resource usage, the algorithm uses SA to find a near-optimal solution which minimizes the overall execution time for scheduling problems on heterogeneous grids. The scheduling algorithm is validated by simulations, using a model which considers the mainly details about the distributed computers and the jobs, and is compared with other scheduling algorithms. The results allows identify the best SA parameters values, that are the learning rate and the iteration size, for each grid size. We found good results when simulating the scheduling algorithm for grid sizes near by 512 computers. We also observed that the SA computing cost do not jeopardize the scheduling results, which are better when compared with the performance of other scheduling disciplines.

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Section: Related Workmentioning

confidence: 99%

“…Although most of them just consider part of the application characteristics to schedule tasks [14][15][16][17][18].…”

Section: Related Workmentioning

confidence: 99%

On Simulated Annealing for the Scheduling of Parallel Applications

Mello¹,

Senger

2008

2008 20th International Symposium on Computer Architecture and High Performance Computing

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“…A batch scheduling scheme to minimize makespan and flowtime using Cellular Mementic Algorithms is proposed in Xhafa, Alba and Dorronsoro (2007). A scheduling model considering the availability of the computational resources, communication delays and the resource reservation is reported in Aggarwal and Aggarwal (2006). A SLA based scheduling scheme proposing an economy driven scheduler on commodity market is presented in Ranjan, Harwood, and Buyya (2006).…”

Section: Introductionmentioning

confidence: 99%

A Computational Grid Scheduling Model To Maximize Reliability Using Modified GA

Raza

Vidyarthi

2011

International Journal of Grid and High Performance Computing

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This paper presents a grid scheduling model to schedule a job on the grid with the objective of ensuring maximum reliability to the job under the current grid state. The model schedules a modular job to those resources that suit the job requirements in terms of resources while offering the most reliable environment. The reliability estimates depict true grid picture and considers the contribution of the computational resources, network links and the application awaiting allocation. The scheduling executes the interactive jobs while considering the looping structure. As scheduling on the grid is an NP hard problem, soft computing tools are often applied. This paper applies Modified Genetic Algorithm (MGA), which is an elitist selection method based on the two threshold values, to improve the solution. The MGA works on the basis of partitioning the current population in three categories: the fittest chromosomes, average fit chromosomes and the ones with worst fitness. The worst are dropped, while the fittest chromosomes of the current generation are mated with the average fit chromosomes of the previous generation to produce off-spring. The simulation results are compared with other similar grid scheduling models to study the performance of the proposed model under various grid conditions.

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“…A high level timed Petri net to model the workflow of grid tasks is proposed in (Yaojun, Changjun, & Xuemei, 2005) whereas a Game Theoritic approach is used in (Rzadca, Tryatram, & Wierzbicki, 2007). A scheduling model considering the availability of the computational resources, communication delays and the resource reservation is reported in (Aggrawal & Aggrawal, 2006).…”

Section: Introductionmentioning

confidence: 99%

A Scheduling Model with Multi-Objective Optimization for Computational Grids using NSGA-II

Raza

Vidyarthi

2010

International Journal of Applied Evolutionary Computation

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Scheduling a job on the grid is an NP Hard problem, and hence a number of models on optimizing one or other characteristic parameters have been proposed in the literature. It is expected from a computational grid to complete the job quickly in most reliable grid environment owing to the number of participants in the grid and the scarcity of the resources available. Genetic algorithm is an effective tool in solving problems that requires sub-optimal solutions and finds uses in multi-objective optimization problems. This paper addresses a multi-objective optimization problem by introducing a scheduling model for a modular job on a computational grid with a dual objective, minimizing the turnaround time and maximizing the reliability of the job execution using NSGA – II, a GA variant. The cost of execution on a node is measured on the basis of the node characteristics, the job attributes and the network properties. Simulation study and a comparison of the results with other similar models reveal the effectiveness of the model.

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A Unified Scheduling Algorithm for Grid Applications

Cited by 8 publications

References 23 publications

On Simulated Annealing for the Scheduling of Parallel Applications

On Simulated Annealing for the Scheduling of Parallel Applications

A Computational Grid Scheduling Model To Maximize Reliability Using Modified GA

A Scheduling Model with Multi-Objective Optimization for Computational Grids using NSGA-II

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