Dispatching Strategy Study for Cloud Storage Resource Bidding of Double Auction Based on PSO Computing Method

Li Sun

Abstract


As an effective computing mode, the cloud computing is provided with many economic characteristics since its invention, including utility market characteristic of computing resource, scale economics of cloud market and payment characteristic of resource supply. The supply-demand relation is reflected and mediated by the price escalation in the economics, which is applicable to the dynamic resource dispatching characteristic of cloud environment. The article here provides the study of the resource supply strategy in the cloud computing based on double auction and bidding mechanism of the economics, and the PSO is integrated to achieve the maximization of business volume and benefits.


Full Text:

PDF

References


Alrawahi A.S., Lee K. (2012). Multi-attribute combinatorial marketplaces for cloud resource trading, Proceedings of the 2nd International Conference on Cloud and Green Computing and 2nd International Conference on Social Computing and Its Applications, CGC/SCA, 81-88.

Chang H.S., Bae S. (2011).Utility adaptive service brokering mechanism for personal cloud serv ice, Proceedings of Military Communications Conference 2011, IEEE Computer, 1622-1627.

Chang V., Walters R.J., Wills G. (2013). The development that leads to the Cloud Computing Business Framework, International Journal of Information Management, 33(3), 524-538.

Deepti T., Hande K.N. (2012). VM management for cross-cloud computing environment, Proceedings of the International Conference on Communication Systems and Network Technologies, CSNT, 731-735.

Jing X., Yuan W.Z. (2012). A priority based scheduling strategy for virtual machine allocation in cloud computing environment, Proceedings of the International Conference on Cloud Computing and Service Computing, CSC, 50-55.

Li C.L., Li L.Y. (2004). Competitive Proportional Resource Allocation Policy for Computational Grid, Future Generation Computer Systems, 20(6), 1041-1054.

Martinez C.G. (2012). Study of resource management for multitenant database systems in cloud computing, University of Colorado at Denver Computer Science, 22(3), 21-40.

Mohammed A. (2013). Implementing a Dynamic Scaling of Web Applications in a Virtualized Cloud Computing Environment, Rochester Institute of Technology, 14(2), 22-41.

Tuan L.G., Trinh A. (2010). A Scale-Free Network Inspired Data Center Architecture,ACM SIGCOMM Computer Communication Review, 40(5), 4-12.

Wang G., Yu H.C. (2013). Task scheduling algorithm based on improved Min-Min algorithm in cloud computing environment, Applied Mechanics and Material, 2429-2432.

Wang L., Ai L.H. (2012). Task scheduling policy based on ant colony optimization in cloud computing environment, Proceedings of 2nd International Conference on Logistics, Informatics and Service Science, LISS, 953-957.

Xiao Y.P., Xu G.X., Liu Y.B. (2013).A metadata-driven cloud computing application virtualization model, Journal of Computers, 8(6), 1571-1579.

Yong A., Xin Z., Jie K. (2013). Application of information resource view on cloud computing service, Journal of Computational Information Systems, 9(2), 593-601.


Refbacks

  • There are currently no refbacks.


Revista de la Facultad de Ingeniería,

ISSN: 2443-4477; ISSN-L:0798-4065

Edif. del Decanato de la Facultad de Ingeniería,

3º piso, Ciudad Universitaria,

Apartado 50.361, Caracas 1050-A,

Venezuela.

© Universidad Central de Venezuela