Design and implementation of fuzzy priority deadline job scheduling algorithm in heterogeneous grid computing
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ORIGINAL RESEARCH
Design and implementation of fuzzy priority deadline job scheduling algorithm in heterogeneous grid computing C. Daniel Sundar Rajan1 Received: 6 March 2020 / Accepted: 30 May 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In heterogeneous distributed computing system, huge amount of attention is attracted by task scheduling process in recent days. Scheduling of task is an important problem, where, overall completion of task is completed within a shortest achievable time by scheduling dissimilar task to target processors. This research work concentrates on designing and implementing a fuzzy priority deadline based task scheduling algorithm (FPDSA) having a fuzzy deadline limitation to competent job execution. This proposed FPDSA algorithm is compared with conventional task scheduling techniques like,Improvised Deadline Scheduling Algorithm (IDSA), Earliest Deadline First (EDF) and Prioritized Based Deadline Scheduling Algorithm with respect to Average Actual Execution (AAE) and amount of Non-Delayedand Delayed Jobs. For 4000 tasks, proposed algorithm achieves 7.45%, 27.94% and 30.84% less AAE than IDSA, EDF, and PDSA and for same number of tasks, computational results by proposed FPDSA for non-delayed tasks are 0.32%, 2.17%, and 1.70% higher than IDSA, EDF, and PDSA. This enhances proposed FPDSA’s performance when compared to present scheduling algorithms and illustratesFPDSA is more appropriate scheduling technique forgrid system. Keywords Fuzzy logic · Task scheduling · FPDSA · EDF · IDSA · PDSA
1 Introduction Grid computing is a computer’s geologically distributed resources interconnection from complex administrative domains offers a virtual computing model. Effectively transmit the task of Scheduling is major issues in grid system (Mingsheng et al. 2003). While presenting computing tasks to grid system, grid setting resources can be shared by users. The major objective of a grid computing environment is momentous services distribution to users and connecting computing system with extensively disseminated resources (Foster et al. 2001; El Amine and Boumhidi 2018). In earlier days, grid had appeared in a prospective platform for addressing applications in various fields (Wang et al. 2012). It has numerous advantages for administrators and developers. In system, based on grid environments available resources, computation of grid environment differs for processing capacity, communication bandwidth and * C. Daniel Sundar Rajan [email protected] 1
Department of Management, Oxford Engineering College, Tiruchirappalli, India
heterogeneous capabilities (De Oliveira and da Silva Fraga 2000). Grid system resource scheduling is a key for source difficulty which revolves into a necessary subject in grid systems. Grid computing shared nodes is used for resolving difficulties in high computing performance and throughput from computing node to node distributed about world (Selvi and Manimegalai 2015). Grid environments distributed computation and resource sharing fac
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