A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads

In heterogeneous I/O workload environments, disk scheduling algorithms should support different QoS (Quality-of-Service) for each I/O request. For example, the algorithm should meet the deadlines of real-time requests and at the same time provide reasonable response time for best-effort requests. Th...

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Main Authors: Taeseok Kim, Hyokyung Bahn, Youjip Won
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/940850
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spelling doaj-5dc771dadd9f443299e637a6a7fe403f2020-11-25T02:03:47ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/940850940850A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O WorkloadsTaeseok Kim0Hyokyung Bahn1Youjip Won2Department of Computer Engineering, Kwangwoon University, Seoul 139-701, Republic of KoreaDepartment of Computer Science and Engineering, Ewha University, Seoul 120-750, Republic of KoreaDivision of Electrical and Computer Engineering, Hanyang University, Seoul 133-791, Republic of KoreaIn heterogeneous I/O workload environments, disk scheduling algorithms should support different QoS (Quality-of-Service) for each I/O request. For example, the algorithm should meet the deadlines of real-time requests and at the same time provide reasonable response time for best-effort requests. This paper presents a novel disk scheduling algorithm called G-SCAN (Grouping-SCAN) for handling heterogeneous I/O workloads. To find a schedule that satisfies the deadline constraints and seek time minimization simultaneously, G-SCAN maintains a series of candidate schedules and expands the schedules whenever a new request arrives. Maintaining these candidate schedules requires excessive spatial and temporal overhead, but G-SCAN reduces the overhead to a manageable level via pruning the state space using two heuristics. One is grouping that clusters adjacent best-effort requests into a single scheduling unit and the other is the branch-and-bound strategy that cuts off inefficient or impractical schedules. Experiments with various synthetic and real-world I/O workloads show that G-SCAN outperforms existing disk scheduling algorithms significantly in terms of the average response time, throughput, and QoS-guarantees for heterogeneous I/O workloads. We also show that the overhead of G-SCAN is reasonable for on-line execution.http://dx.doi.org/10.1155/2014/940850
collection DOAJ
language English
format Article
sources DOAJ
author Taeseok Kim
Hyokyung Bahn
Youjip Won
spellingShingle Taeseok Kim
Hyokyung Bahn
Youjip Won
A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
The Scientific World Journal
author_facet Taeseok Kim
Hyokyung Bahn
Youjip Won
author_sort Taeseok Kim
title A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
title_short A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
title_full A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
title_fullStr A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
title_full_unstemmed A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads
title_sort pruning-based disk scheduling algorithm for heterogeneous i/o workloads
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2014-01-01
description In heterogeneous I/O workload environments, disk scheduling algorithms should support different QoS (Quality-of-Service) for each I/O request. For example, the algorithm should meet the deadlines of real-time requests and at the same time provide reasonable response time for best-effort requests. This paper presents a novel disk scheduling algorithm called G-SCAN (Grouping-SCAN) for handling heterogeneous I/O workloads. To find a schedule that satisfies the deadline constraints and seek time minimization simultaneously, G-SCAN maintains a series of candidate schedules and expands the schedules whenever a new request arrives. Maintaining these candidate schedules requires excessive spatial and temporal overhead, but G-SCAN reduces the overhead to a manageable level via pruning the state space using two heuristics. One is grouping that clusters adjacent best-effort requests into a single scheduling unit and the other is the branch-and-bound strategy that cuts off inefficient or impractical schedules. Experiments with various synthetic and real-world I/O workloads show that G-SCAN outperforms existing disk scheduling algorithms significantly in terms of the average response time, throughput, and QoS-guarantees for heterogeneous I/O workloads. We also show that the overhead of G-SCAN is reasonable for on-line execution.
url http://dx.doi.org/10.1155/2014/940850
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