• DocumentCode
    3077025
  • Title

    A Resource Allocation Model for Hybrid Storage Systems

  • Author

    Hui Wang ; Varman, Peter

  • Author_Institution
    Rice Univ., Houston, TX, USA
  • fYear
    2015
  • fDate
    4-7 May 2015
  • Firstpage
    91
  • Lastpage
    100
  • Abstract
    Providing QoS guarantees for hybrid storage systems made up of both solid-state drives (SSDs) and hard disks (HDs) is a challenging problem. Since HDs and SSDs have widely different IOPS capacities, it is not sensible to treat the storage system as a monolithic black box, instead a useful QoS model must necessarily differentiate the IOs made to different device types. Traditional storage resource allocation models have largely been designed to provide QoS for a single resource type, and result in poor utilization and fairness when applied to multiple coupled resources. In this paper, we present a new resource allocation model for hybrid storage systems using a multi-resource framework. The model supports reservations and shares for clients sharing the storage system. Reservations specify the minimum throughput (IOPS) that a client must receive, while shares reflect its weight relative to other clients that are bottlenecked on the same device. We present a formal multi-resource allocation model to allocate IOPS to clients, together with an IO scheduling algorithm to maximize system throughput. The model and algorithms are validated with empirical results.
  • Keywords
    flash memories; input-output programs; quality of service; resource allocation; scheduling; HD; IO scheduling algorithm; IOPS capacities; QoS guarantees; QoS model; SSD; formal multiresource allocation model; hard disks; hybrid storage systems; monolithic black box; multiple coupled resources; multiresource framework; resource allocation model; solid-state drives; storage resource allocation models; system throughput; Drives; High definition video; Linear programming; Optimization; Quality of service; Resource management; Throughput; QoS; hybrid storage systems; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/CCGrid.2015.132
  • Filename
    7152475