An improved binary PSO-based task scheduling algorithm in green cloud computing

Author

Lili Xu ; Kun Wang ; Zhiyou Ouyang ; Xin Qi

Author_Institution

Key Lab. of Broadband Wireless Commun. & Sensor Network Technol., Nanjing Univ. of Posts & Telecommun., Nanjing, China

fYear

2014

Firstpage

126

Lastpage

131

Abstract

Cloud computing is experiencing a rapid development since a large amount of data need to be addressed. How to carry on the reasonable task scheduling plays a vital role in the efficiency of cloud computing. This paper proposes a green cloud task-scheduling algorithm (GCTA) based on the improved binary particle swarm optimization(BPSO). The main contribution of our work is avoiding matrix operations by using pipelined number for virtual machines and redefining the position and velocity of particle. Simulation shows that the proposed GCTA has less execution time, and reduces resource consumption accordingly.

Keywords

cloud computing; green computing; particle swarm optimisation; pipeline processing; scheduling; virtual machines; BPSO; GCTA; binary PSO-based task scheduling algorithm; binary particle swarm optimization; green cloud computing; green cloud task-scheduling algorithm; particle position; particle velocity; pipelined number; virtual machines; Cloud computing; Job shop scheduling; Particle swarm optimization; Scheduling algorithms; Virtual machining; binary particle swarm optimization (BPSO); green cloud; task scheduling algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Networking in China (CHINACOM), 2014 9th International Conference on

Type

conf

DOI

10.1109/CHINACOM.2014.7054272

Filename

7054272