Ganging of Resources via Fuzzy Manhattan Distance Similarity with Priority Tasks Scheduling in Cloud Computing

• Autorzy: Priya S. S. , Mehata K. M. , Banu W. A.

Identyfikatory

DOI

10.26636/jtit.2018.108916

• Języki publikacji: EN

Abstrakty

EN

This paper proposes a fuzzy Manhattan distance-based similarity for gang formation of resources (FMDSGR) method with priority task scheduling in cloud computing. The proposed work decides which processor is to execute the current task in order to achieve efficient resource utilization and effective task scheduling. FMDSGR groups the resources into gangs which rely upon the similarity of resource characteristics in order to use the resources effectively. Then, the tasks are scheduled based on the priority in the gang of processors using gang-based priority scheduling (GPS). This reduces mainly the cost of deciding which processor is to execute the current task. Performance has been evaluated in terms of makespan, scheduling length ratio, speedup, efficiency and load balancing. CloudSim simulator is the toolkit used for simulation and for demonstrating experimental results in cloud computing environments.

Słowa kluczowe

EN

clustering; pre-processing; quality of service; resource allocation

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2018
• Tom: nr 1
• Strony: 32--41
• Opis fizyczny: Bibliogr. 31 poz., rys., tab.

Twórcy

autor

Priya S. S.

• Department of Computer Science and Engineering, B. S. Abdur Rahman University, Chennai, Tamil Nadu, India

autor

Mehata K. M.

• School of Computer, Information and Mathematical Sciences at B. S. Abdur Rahman University, Chennai, Tamil Nadu, India

autor

Banu W. A.

• Department of Computer Science and Engineering, B. S. Abdur Rahman University, Chennai, Tamil Nadu, India

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).