Software defined just-in-time caching in an enterprise storage system

Abstract

A software defined storage environment is one in which logical storage resources and services are completely abstracted from physical storage systems. Therefore, not only can storage resources cross physical boundaries, but they can also be defined by software and provisioned automatically, for instance, by the applications that consume them. In this paper, we present a novel software defined cooperative caching (SDCC) framework that operates at the block layer and manages the placement of data in different tiers and caches that span multiple servers and storage systems in an integrated and coherent fashion. A programming interface complements the core framework by giving the applications an interface to control data organization across the storage, thereby allowing the block storage infrastructure to be software defined. The SDCC framework allows applications to actively influence the data layout while also benefitting from the system-wide knowledge and resource management capabilities of the storage system. We present an experimental study conducted using real workloads, and the results demonstrate the performance benefits gained with SDCC, as well as the potential for consolidating multiple different workloads that share the same storage server.

Efficient Software-Based Mobile Cloud Computing Framework

“…IBM may be seen as a leader through literature, as well as VMWare and Microsoft [9][11] [13][14] [15]. Traditional cloud environments do offer a degree of storage resource abstraction through virtualization; however in order to have a more powerful environment which enables these resources to be autonomously managed, SDS solutions are needed.…”

“…In [13] the authors introduce their SDS solution for just-in time caching, aimed at optimising use of Solid State Drives (SSD) in server environments. Flash storage offers huge performance gains over traditional storage drives but carries a considerable financial cost; therefore it tends to be more suited for caching.…”

Efficient and agile storage management in software defined environments

“…The SDN approach can therefore be divided into two dimensions, both of which apply to SDS as well, as illustrated in the following examples: (1) a horizontal dimension of global optimization across nodes, where control plane functions shift from a fully distributed model to a centralized model in order to enable global optimization across the nodes; and (2) a vertical dimension of the level of software integration of the control and data planes. As an example of global optimization applied to SDS, consider storage systems where an individual storage system level tiering policy [5] is configured. A global tiering optimization policy across multiple storage systems would be able to rebalance the load by moving data to a more idle storage system, possibly passing along the original tiering information of that data to improve placement within the new system.…”