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  4. GSR: A global seek-optimizing real-time disk-scheduling algorithm
 
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GSR: A global seek-optimizing real-time disk-scheduling algorithm

Journal
Journal of Systems and Software
Journal Volume
80
Journal Issue
2
Pages
198-215
Date Issued
2007
Author(s)
Chang, H.-P.
Chang, R.-I.
Shih, W.-K.
Chang, R.-C.
Chang, Hsung-Pin
Chang, Ray-I
Shih, Wei-Kuan
Chang, Ruei-Chuan
RAY-I CHANG  
DOI
10.1016/j.jss.2006.03.045
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-33846088369&partnerID=MN8TOARS
http://scholars.lib.ntu.edu.tw/handle/123456789/332752
Abstract
Earliest-deadline-first (EDF) is good for scheduling real-time tasks in order to meet timing constraint. However, it is not good enough for scheduling real-time disk tasks to achieve high disk throughput. In contrast, although SCAN can maximize disk throughput, its schedule results may violate real-time requirements. Thus, during the past few years, various approaches were proposed to combine EDF and SCAN (e.g., SCAN-EDF and RG-SCAN) to resolve the real-time disk-scheduling problem. However, in previous schemes, real-time tasks can only be rescheduled by SCAN within a local group. Such restriction limited the obtained data throughput. In this paper, we proposed a new globally rescheduling scheme for real-time disk scheduling. First, we formulate the relations between the EDF schedule and the SCAN schedule of input tasks as EDF-to-SCAN mapping (ESM). Then, on the basis of ESM, we propose a new real-time disk-scheduling algorithm: globally seek-optimizing rescheduling (GSR) scheme. Different from previous approaches, a task in GSR may be rescheduled to anywhere in the input schedule to optimize data throughput. Owing to such a globally rescheduling characteristic, GSR obtains a higher disk throughput than previous approaches. Furthermore, we also extend the GSR to serve fairly non-real-time tasks. Experiments show that given 15 real-time tasks, our data throughput is 1.1 times that of RG-SCAN. In addition, in a mixed workload, compared with RG-SCAN, our GSR achieves over 7% improvement in data throughput and 33% improvement in average response time. © 2006 Elsevier Inc. All rights reserved.
Type
journal article

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