Unified read requests

Most work on multimedia storage systems has assumed that clients will be serviced using a round-robin strategy. The server services the clients in rounds and each client is allocated a time slice within that round. Furthermore, most such algorithms are evaluated on the basis of a tightly specified cost function. This is the basis for well known algorithms such as FCFS, SCAN, SCAN-EDF, etc. In this paper, we describe a Request Merging (RM) module that takes as input, a set of client requests, and a set of constraints on the desired performance such as client waiting time or maximum disk bandwidth, and a cost function. It produces as output, a Unified Read Request (URR), telling the storage server which data items to read, and when the clients would like these data items to be delivered to them. Given a cost function of, a URR is optimal if there is no other URR satisfying the constraints with a lower cost. We present three algorithms in this paper, each of which accomplishes this kind of request merging. The first algorithm OptURR is guaranteed to produce minimal cost URRs with respect to arbitrary cost functions. In general, the problem of computing an optimal URR is NP-complete, even when only two data objects are considered. To alleviate this problem, we develop two other algorithms, called GreedyURR and FastURR that may produce sub-optimal URRs. but which have some nicer computational properties. We will report on the pros and cons of these algorithms through an experimental evaluation.