IMPROVE DYNAMIC VIEW AND OPTIMIZATION FOR DATA TRANSFER IN CLOUD DATA CENTERS

Abstract

Cloud Storage Providers (CSPs) provide geographic databases with different cost savings classes. One of the main customer issues of Cloud users is the exploitation of these storage classes and the cost of at least different jobs. This price includes residential value (i.e. storage, maintenance and expenditure) and potential transfer cost (network price). To solve this problem, we recommend the preview algorithm that changes liners programming and linear programming techniques with accurate knowledge of workload. Due to the problem of high end of this process, more awareness is needed; we recommend two online methods to stop advertising between residential and transfer expenses and to convert storage class into CSP. This is the first online algorithm that determines the cost and maximum cost requirements. More expensive data store residences spend 2 offline instructions on any webpage or cost savings. The second online approach uses "Reader Horizontal Control" (RHC) technology, which uses the time, spent using information and information for future file load information. As a result of proposed suggestions, face book Jobs was demonstrated by simulation using work-based operations.