Selecting the most fitting resource for task execution

Chang, Ruay-Shiung; Lin, Chun-Fu; Chen, Jen-Jom

doi:10.1016/j.future.2010.09.003

Cited by 19 publications

(13 citation statements)

References 12 publications

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“…Paper [2] simulated SMF but without any machine failure. Therefore with a little effort, the SMF algorithm was simulated with machine failure of 20% and the results are shown in Average Execution Time (AET).…”

Section: Results and Discssionsmentioning

confidence: 99%

“…Global Information System (GIS) categorizes resources into L discrete levels according to the capability. We use speed of machine (MIPS) as job's resource requirement in our work whereas in [2], they use predicted execution time (PET). The calculation on PET consumes some time period and needs more works, hence we go for a simpler job's resource requirement.…”

Section: A Select Most Fitting (Smf) Resource Algorithmmentioning

confidence: 99%

“…GIS is responsible to group the nodes register to it into discrete levels based on different MIPS. We use the same simulation parameters as in [2], refer Table 2. We generate a set of speed of machine and a set of task length to be used by all of our experiments.…”

Section: Simulation Designmentioning

confidence: 99%

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Checkpointing in selected most fitted resource task scheduling in grid computing

Latip

San

Chanchary

2012

2012 7th International Conference on Computer Science &Amp; Education (ICCSE)

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Grid applications run on environment that is prone to different kinds of failures. Fault tolerance is the ability to ensure successful delivery of services despite faults that may occur. Our research adds fault tolerance capacity with checkpointing and machine failure, to the current research, Selected Most Fitted (SMF) Task Scheduling for grid computing. This paper simulates one of fault tolerance techniques for grid computing, which is implementing checkpointing into Select Most Fitting Resource for Task Scheduling algorithm (SMF). We applied the algorithm of MeanFailure with Checkpointing in the SMF algorithm and named it MeanFailureCP-SMF. The MeanFailureCP-SMF is simulated using Gridsim with initial checkpointing interval at 20% job execution time. Results show that with MeanFailureCP-SMF has reduce the average execution time (AET) compare to the current SMF and MeanFailure Algorithm.

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Section: Results and Discssionsmentioning

confidence: 99%

Section: A Select Most Fitting (Smf) Resource Algorithmmentioning

confidence: 99%

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Checkpointing in selected most fitted resource task scheduling in grid computing

Latip

San

Chanchary

2012

2012 7th International Conference on Computer Science &Amp; Education (ICCSE)

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“…The range method used in this research is to define the weightage of calculation items respectively. The range strategies have been applied by Chang et al (2011) in declaring the Prediction of Execution Time (PET) for all of the CPU. Then, the PET value has been allocated into several levels of ranges against CPU speed.…”

Section: Jcsmentioning

confidence: 99%

“…Then, the PET value has been allocated into several levels of ranges against CPU speed. The adopted methodologies used by Hwang et al (2010;Chang et al, 2011;Lee et al, 2011) has been reused in this research to complement the multi-instance broker invention.…”

Section: Jcsmentioning

confidence: 99%

Resource Broker Management by Adopting Self-Adaptive Multi-Instance Broker Scheduling in Grid Computing

Yahaya¹,

Latip²,

Abdullah³

et al. 2014

Journal of Computer Science

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A grid resource broker seeks to assign the appropriate jobs to the appropriate resources as part of resource management in the multi-grid environment. Multi instances of the broker system provides multiple instances of brokers to simultaneously process jobs between multiple resources in a hierarchical cluster grid environment. In this study, the multi-instance broker is developed using grid resource broker taxonomy properties. The number of broker instances to be used for each processing session is determined by calculating resources, computing power and workload. The Self-Adaptive Multi-Instance Broker Scheduling algorithm SAMiB was tested against iHLBA algorithm through four types of scenarios containing various mixes of background load and CPU speed. The SAMiB algorithm has achieved a decrease of 14.93% in makespan time for 2000 jobs, proving the suitability of the multiinstance broker concept for the hierarchical cluster grid environment.

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Load balanced transaction scheduling using Honey Bee Optimization considering performability in on‐demand computing system

Mahato

Singh

2017

Concurrency and Computation

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SummaryThe scheduling of load balanced transactions is an emerging problem in on‐demand computing system. This problem can be studied considering several parameters such as resource availability, performance, and reliability. The existing approaches to find the exact solutions for this problem are limited. This paper presents a Honey Bee Optimization (HBO)–based method to solve the mentioned problem. In this method, first, the load of the system is balanced and then the transactions are scheduled using foraging behavior of honey bees to find the optimal solutions. We also modify four known scheduling algorithms such as Ant Colony Optimization (ACO), Hierarchical Load Balanced Algorithm (HLBA), Dynamic and Decentralized Load Balancing (DLB), and Randomized to obtain transaction scheduling algorithms for the purpose of comparison with our proposed algorithm. The compared results show that the proposed algorithm performs better than the modified existing algorithms.

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Selecting the most fitting resource for task execution

Cited by 19 publications

References 12 publications

Checkpointing in selected most fitted resource task scheduling in grid computing

Checkpointing in selected most fitted resource task scheduling in grid computing

Resource Broker Management by Adopting Self-Adaptive Multi-Instance Broker Scheduling in Grid Computing

Load balanced transaction scheduling using Honey Bee Optimization considering performability in on‐demand computing system

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