Data Staging Algorithm in Clouds

In this paper, we study about efficiently achieving data staging and caching on a set of advantage sites with a less cost in a cloud system. In this we focus on the problem of prices of high bandwidth which is charged by cloud providers for uploads and downloads of customer data. Unlike the traditional research, we do not design to identify the access patterns to facilitate the future requests. Instead, with information probably known in advance, while minimizing the monetary costs for caching and transmitting the data items requested by user. our goal for designing this paper is to efficiently stage the shared data items to predetermined sites at promoter time instants to align with the patterns. In this we create the single or multiple copies of data items and store on the some vantage site. We present a bulk transfer system that opportunistically exploits the excess capacities of network links to deliver bulk content cheaply and efficiently. When the ratio of transmission cost and caching cost is low, a single copy of each data item can efficiently serve to all the requested user. In multi copy situation, our main focus on the tradeoff between the transmission cost and storing cost by controlling the upper bounds of transmissions and copies. The upper bound can be on per-item basis or on all-item basis. Based on dynamic programming techniques, we present efficient optimal solutions to all these cases provided that the upper bound is poly nominally surrounded by the number of service requests and the number of distinct data items.