A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System

Kumar, Harendra; Singh, M. P.; Yadav, Pradeep K.

doi:10.5120/12546-9030

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…A model for allocating the tasks to processors in heterogeneous distributed computing systems with the goal of maximizing the system reliability has been developed in [14]. Kumar et al [15] has developed a task allocation problem using fuzzy execution and fuzzy communication times. Recently V.Sriramdas et al [16] developed a tasks allocation model treating allocation factors as fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment

Kumar¹

2015

IJCA

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The development of distributed real time system (DRTS) has lead to there use in several applications including information processing, fluid flow, weather modeling, database systems, real-time high-speed simulation of dynamical systems, and image processing. Reliability analysis of these processing elements and communication links is one of the important parameter to get the system efficiency. We can improve the system performance (i.e. system cost, system reliability and processor utilization etc.) by scheduling the tasks to the processors properly in DRTS. In this paper, a new tasks allocation model has been developed with fuzzy execution times , and fuzzy inter tasks communication times , .The times has been defuzzified into crisp one by using Robust Ranking Method [RRM], Centre of Maxima Method [CoM] and Weight of Center of Area Method [CoA].The effect of inter processor distances on the tasks allocation has been considered while developing the model. Numerical examples show that the model presented in this paper is suitable for arbitrary number of processors with random program structure and more realistic and general in nature.

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Section: Introductionmentioning

confidence: 99%

A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment

Kumar¹

2015

IJCA

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Evaluation of Service Time in DCS using Fuzzy and Clustering Technique

Khandelwal¹,

Kumar

2020

2020 International Conference on Computational Performance Evaluation (ComPE)

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Task Allocation Model Based on Hierarchical Clustering and Impact of Different Distance Measures on the Performance

Kumar

Tyagi

2020

International Journal of Fuzzy System Applications

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This article observed a new strategy to the problem of tasks clustering and allocation for very large distributed real-time problems, in which software is consolidated hierarchically and hardware potentially spans various shared or dedicated links. Here, execution and communication times have been considered as a number. Existing strategies for tasks clustering and allocation are based on either executability or communication. This study's analytical model is a recurrence conjuration of two stages: formation of clusters and clusters allocation. A modified hierarchical clustering (MHC) algorithm is derived to cluster high communicated tasks and also an algorithm is developed for proper allocation of task clusters onto suitable processors in order to achieve optimal fuzzy response time and fuzzy system. Yang's and Hamming's distances are taken to demonstrate the impact of distance measures on the performance of the proposed model.

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A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System

Cited by 3 publications

References 12 publications

A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment

A Heuristic Model for Tasks Scheduling in Heterogeneous Distributed Real Time System under Fuzzy Environment

Evaluation of Service Time in DCS using Fuzzy and Clustering Technique

Task Allocation Model Based on Hierarchical Clustering and Impact of Different Distance Measures on the Performance

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