Evaluation of expanded heuristics in a heterogeneous distributed data staging network

Providing up-to-date input to users´ applications is an important data management problem for a heterogeneous distributed computing environment, where each data storage location and intermediate node may have different data available, different storage limitations and different communication links available. Sites in the heterogeneous network request data items, and each request has an associated deadline and priority. In a military situation, the data staging problem involves positioning data for facilitating a faster access time when it is needed by programs that will aid in decision making. This work concentrates on solving a basic version of the data-staging problem in which all parameter values for the communication system and the data-request information represent the best-known information collected so far, and they stay fixed throughout the scheduling process. The heterogeneous network is assumed to be over-subscribed, and not all requests for data items can be satisfied. Three multiple-source, shortest-path algorithm-based procedures for finding a near-optimal schedule of the communication steps for staging the data are described. Each procedure can be used with each of three cost criteria developed in this paper (based on results from earlier experiments). A subset of the possible procedure/cost criterion combinations are evaluated in simulation studies considering different priority weighting schemes, different average numbers of links used to satisfy each data request, and different network loadings. The proposed heuristics are shown to perform well with respect to upper and lower bounds