Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 203-224 |
| Number of pages | 22 |
| Journal | Multimedia Tools and Applications |
| Volume | 20 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2003 Aug 1 |
| Externally published | Yes |
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Keywords
- Cost function
- Multimedia storage server
- Optimality
- Request merging
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Information Systems
- Computer Graphics and Computer-Aided Design
- Software
- Theoretical Computer Science
- Computational Theory and Mathematics
Cite this
Unified read requests. / Hwang, Een Jun; Prabhakaran, B.
In: Multimedia Tools and Applications, Vol. 20, No. 3, 01.08.2003, p. 203-224.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Unified read requests
AU - Hwang, Een Jun
AU - Prabhakaran, B.
PY - 2003/8/1
Y1 - 2003/8/1
N2 - 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.
AB - 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.
KW - Cost function
KW - Multimedia storage server
KW - Optimality
KW - Request merging
UR - http://www.scopus.com/inward/record.url?scp=0038446760&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0038446760&partnerID=8YFLogxK
U2 - 10.1023/A:1024058404247
DO - 10.1023/A:1024058404247
M3 - Article
AN - SCOPUS:0038446760
VL - 20
SP - 203
EP - 224
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
SN - 1380-7501
IS - 3
ER -