“A Noble Approach for Scheduling of Task Graph Using DAG to Reduce the Overall Makespan”
Prasant Singh Yadav1, P.K Yadav2, Karunesh Paratp Yadav3
1Prasant Singh Yadav, Ph.D Computer Science Scholar, Dr. APJAKTU, Lucknow (U.P), India.
2Dr. Pradeep .Kumar Yadav, Principal, Scientist CSIR-CBRI, Roorkee (Uttarakhand), India.
3Dr. K.P Yadav, Vice Chancellor, Sangam University, Bhilwara (Rajasthan) India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 961-968 | Volume-8 Issue-5, June 2019 | Retrieval Number: E7052068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Arrangement of the tasks is the most essential factor to attain equilibrate load, at the distributed computing environment. The arrangement of the task networks is very perilous to the functioning of the multiprocessor computation scheme. It pacts toward the distribution of errands to most appropriate node with maintaining the order of consignment with regard to the sequence of task execution on each node. Here the primary goal is to decrease the overall achievement time or makespan. It’s well known that the direct Acyclic Graph (DAG) arrangement problem is NP-complete for this numerous heuristics approaches have been offered. Through this research paper we suggest a noble approach of task Scheduling algorithm for dissimilar processors having different competencies. As we discovered in printed approaches used to allocate a weight or task into the processors ominously alter the presentation of arrangement procedures. We proposed a brand new tactic Performance Effective Task Organization Algorithm (PETOA) for locale the tasks from the order with respective precedence based on Highest Directed Edge Path (HDEP) and following it in accordance with the tasks priorities the selected task will be allocated on these suitably capable processors on the task takes the Minimal Completion Time MCT). The projected method was confirmed on a number of arbitrarily created problems of various dimensions plus types, resulting from better results than earlier methods.
Keywords: Tasak Scheduling, DAG, MCT, DCS, MCT, PETOA, TASK GRAPH, HDEP.
Scope of the Article: Computer Graphics