Approximation Strategy Based on Data Merging for Static Data Management in Networks

We studied static data management problem based on data merging in general networks with object to minimize the total costs. By using greedy and LP-dual method, an initial placement is acquired. Given network G=(V, E) and data set X, we can achieve a constant ratio approximation algorithm.The key of our method is to construct some clusters based on hierarchical structure for requests. In order to get the initial placement, we preciously discuss an approximation strategy for a variance of facility location with service installation cost.