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Dissertation Title: Scalable and manageable storage systems

Candidate: Khalil Amiri, CMU ECE (amiri+@cs.cmu.edu)

Advisor: Prof. Garth Gibson

Committee: Professors G. Gibson, G. Ganger,
 M. Satyanarayanan, D. Sieworiek and J. Wilkes

Date: Tuesday September 26, 2000

Time: 10 am

Room: 4623 Wean Hall

Thesis talk Abstract:

Emerging applications such as data warehousing, multimedia content
distribution, electronic commerce and medical and satellite databases
have substantial storage requirements that are growing at 3X to 5X per
year. Such applications require scalable, highly-available and
cost-effective storage systems.  Traditional storage systems rely on a
central controller (file server, disk array controller) to access
storage and copy data between storage devices and clients which limits
their scalability.

This dissertation proposes an architecture, network-attached secure
disks (NASD), that eliminates the single controller bottleneck
allowing throughput and bandwidth of an array to scale with increasing
capacity up to the largest sizes desired in practice. NASD enables
direct access from client to storage devices, allowing aggregate
bandwidth to scale with the number of nodes.

In a NASD system, each client acts as its own storage (RAID)
controller, performing all the functions required to manage redundancy
and access its data. As a result, multiple controllers can be
accessing and managing shared storage devices concurrently. Without
proper provisions, this concurrency can corrupt redundancy codes and
cause hosts to read incorrect data. This dissertation proposes a
transactional approach to ensure correctness in highly concurrent NASD
arrays. It proposes distributed timestamp ordering protocols that
exploit trends towards increased device intelligence to ensure
correctness while scaling well with system size.

Emerging NASD storage arrays consist of storage devices with excess
cycles in their on-disk controllers, which can be used to execute
filesystem function traditionally executed on the host. Programmable
storage devices increase the flexibility in partitioning filesystem
function between clients and storage devices. The heterogeneity in
resource availability among servers, clients and network links causes
optimal function partitioning to change across sites and with time.
This dissertation proposes an automatic approach which allows function
partitioning to be changed and optimized at run-time by relying only
on the black-box monitoring of functional components and of resource
availability in the storage system.