Sustainable pricing for cloud services using data analytics
Liew, Keen Hao
Date of Issue2016-05-19
School of Electrical and Electronic Engineering
Data centers are growing rapidly over the years with the extensive development of various services and products over the network. Data center that allocates different job requests to multiple tiers to be serviced is considered in order to get some insights regarding deferrable jobs. In this project, we are implementing Receding Horizon Control (RHC) based scheduling to target on the matter of provision of source for deferrable jobs. On top of that, the problem regarding the optimum provision of server at different tiers will be formulated and resolved in two different approaches, which is the minimization of operational cost and joint minimization of capital and operational cost with the use of a discrete time model. Subsequently, we would like to aim to provide an efficient way to substitute more renewable energy into the grid to replace brown energy by offering reasonable monetary incentives without adding on too much additional expenditures to the provider on deadline deferral. From there, we aim to achieve energy efficiency. By using data analytic tools, we also aim to propose some suitable yet sustainable pricing scheme for the cloud service market by implementing different strategies. Last but not least, the proposed method and scheme demonstrated by us succeeds notably good performance according to different significant performance factors involved in the system.
Final Year Project (FYP)
Nanyang Technological University