TY - JOUR
T1 - A study of optimal allocation of computing resources in cloud manufacturing systems
AU - Laili, Yuanjun
AU - Tao, Fei
AU - Zhang, Lin
AU - Sarker, Bhaba R.
PY - 2012/11
Y1 - 2012/11
N2 - As a new advanced service-oriented networked manufacturing model, cloud manufacturing (CMfg) has been proposed recently. The optimal allocation of computing resources (OACR) is a core part for implementing CMfg. High heterogeneity, high dynamism, and virtualization make the OACR problem more complex than the traditional scheduling problems in grid system or cloud computing system. In this paper, a new comprehensive model for OACR is proposed in the CMfg system. In this model, all main computation, communication, and reliability constraints in the special circumstances are considered. To solve the OACR problem, a new improved niche immune algorithm was presented. Associated with the niche strategy, new heuristics are designed flexibly based on the characteristics of the problem and pheromone is added for adaptive searching. Experiments demonstrate the effectiveness of the designed heuristic information and show NIA's high performances for addressing the OACR problem compared with other intelligent algorithms.
AB - As a new advanced service-oriented networked manufacturing model, cloud manufacturing (CMfg) has been proposed recently. The optimal allocation of computing resources (OACR) is a core part for implementing CMfg. High heterogeneity, high dynamism, and virtualization make the OACR problem more complex than the traditional scheduling problems in grid system or cloud computing system. In this paper, a new comprehensive model for OACR is proposed in the CMfg system. In this model, all main computation, communication, and reliability constraints in the special circumstances are considered. To solve the OACR problem, a new improved niche immune algorithm was presented. Associated with the niche strategy, new heuristics are designed flexibly based on the characteristics of the problem and pheromone is added for adaptive searching. Experiments demonstrate the effectiveness of the designed heuristic information and show NIA's high performances for addressing the OACR problem compared with other intelligent algorithms.
KW - Cloud manufacturing (CMfg)
KW - Computing resources
KW - Intelligent algorithms
KW - Optimal allocation
UR - https://www.scopus.com/pages/publications/84870057530
U2 - 10.1007/s00170-012-3939-0
DO - 10.1007/s00170-012-3939-0
M3 - 文章
AN - SCOPUS:84870057530
SN - 0268-3768
VL - 63
SP - 671
EP - 690
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
IS - 5-8
ER -