JOURNAL ARTICLE

Multi Objective Task Scheduling in Cloud Environment Using Nested PSO Framework

R. K. Jena

Year: 2015 Journal:   Procedia Computer Science Vol: 57 Pages: 1219-1227   Publisher: Elsevier BV

Abstract

Cloud computing is an emerging computing paradigm with a large collection of heterogeneous autonomous systems with flexible computational architecture. Task scheduling is an important step to improve the overall performance of the cloud computing. Task scheduling is also essential to reduce power consumption and improve the profit of service providers by reducing processing time. This paper focuses on task scheduling using a multi-objective nested Particle Swarm Optimization(TSPSO) to optimize energy and processing time. The result obtained by TSPSO was simulated by an open source cloud platform (CloudSim). Finally, the results were compared to existing scheduling algorithms and found that the proposed algorithm (TSPSO) provide an optimal balance results for multiple objectives.

Keywords:
CloudSim Computer science Cloud computing Distributed computing Scheduling (production processes) Particle swarm optimization Fixed-priority pre-emptive scheduling Two-level scheduling Fair-share scheduling Dynamic priority scheduling Rate-monotonic scheduling Quality of service Mathematical optimization Operating system Computer network Algorithm

Metrics

139
Cited By
32.40
FWCI (Field Weighted Citation Impact)
17
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
© 2026 ScienceGate Book Chapters — All rights reserved.