TY - JOUR
T1 - Cloud computing resource scheduling and a survey of its evolutionary approaches
AU - Zhan, Zhi Hui
AU - Liu, Xiao Fang
AU - Gong, Yue Jiao
AU - Zhang, Jun
AU - Chung, Henry Shu Hung
AU - Li, Yun
PY - 2015/7/1
Y1 - 2015/7/1
N2 - A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon.
AB - A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon.
KW - ant colony optimization
KW - cloud computing
KW - evolutionary computation
KW - genetic algorithm
KW - particle swarm optimization
KW - resource scheduling
UR - http://www.scopus.com/inward/record.url?scp=84939803867&partnerID=8YFLogxK
U2 - 10.1145/2788397
DO - 10.1145/2788397
M3 - Article
AN - SCOPUS:84939803867
SN - 0360-0300
VL - 47
JO - ACM Computing Surveys
JF - ACM Computing Surveys
IS - 4
M1 - 63
ER -