Using Lightweight Transactions and Snapshots for Fault-Tolerant Services Based on Shared Storage Bricks

To satisfy current and future application needs in a cost effective manner, storage systems are evolving from mono-lithic disk arrays to networked storage architectures based on commodity components. So far, this architectural transi-tion has mostly been envisioned as a way to scale capacity and performance. In this work we examine how the block-level interface exported by such networked storage systems can be extended to deal with reliability. Our goals are: (a) At the design level, to examine how strong reliability se-mantics can be offered at the block level; (b) At the imple-mentation level, to examine the mechanisms required and how they may be provided in a modular and configurable manner. We first discuss how transactional-type semantics may be offered at the block level. We present a system design that uses the concept of atomic update intervals combined with existing, block-level locking and snapshot mechanisms, in contrast to the more common journaling techniques. We discuss in detail the design of the associated mechanisms and the trade-offs and challenges when dividing the re-quired functionality between the file-system and the block-level storage. Our approach is based on a unified and thus, non-redundant set of mechanisms for providing reliability both at the block and file level. Our design and imple-mentation effectively provide a tunable, lightweight trans-actions mechanism to higher system and application layers. Finally, we describe how the associated protocols can be implemented in a modular way in a prototype storage sys-tem we are currently building. As our system is currently being implemented, we do not present performance results

Fairness in a data center

Existing data centers utilize several networking technologies in order to handle the performance requirements of different workloads. Maintaining diverse networking technologies increases complexity and is not cost effective. This results in the current trend to converge all traffic into a single networking fabric. Ethernet is both cost-effective and ubiquitous, and as such it has been chosen as the technology of choice for the converged fabric. However, traditional Ethernet does not satisfy the needs of all traffic workloads, for the most part, due to its lossy nature and, therefore, has to be enhanced to allow for full convergence. The resulting technology, Data Center Bridging (DCB), is a new set of standards defined by the IEEE to make Ethernet lossless even in the presence of congestion. As with any new networking technology, it is critical to analyze how the different protocols within DCB interact with each other as well as how each protocol interacts with existing technologies in other layers of the protocol stack. This dissertation presents two novel schemes that address critical issues in DCB networks: fairness with respect to packet lengths and fairness with respect to flow control and bandwidth utilization. The Deficit Round Robin with Adaptive Weight Control (DRR-AWC) algorithm actively monitors the incoming streams and adjusts the scheduling weights of the outbound port. The algorithm was implemented on a real DCB switch and shown to increase fairness for traffic consisting of mixed-length packets. Targeted Priority-based Flow Control (TPFC) provides a hop-by-hop flow control mechanism that restricts the flow of aggressor streams while allowing victim streams to continue unimpeded. Two variants of the targeting mechanism within TPFC are presented and their performance evaluated through simulation

A quasi-static routing scheme for cross-connected storage area network.

Yang Qin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves [65]-[67]).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Thesis Overview --- p.7Chapter 2 --- Storage Area Network(SAN) --- p.9Chapter 2.1 --- Fibre Channel Protocol --- p.11Chapter 2.2 --- Switched Fibre Channel SAN --- p.16Chapter 2.2.1 --- Cascaded Topology --- p.17Chapter 2.2.2 --- Meshed Topology --- p.17Chapter 2.2.3 --- Cross-Connected Topology --- p.19Chapter 2.2.4 --- Routing Scheme in Cross-Connected SAN --- p.21Chapter 3 --- Path Switching --- p.24Chapter 3.1 --- Cross-path Switching Principle --- p.24Chapter 3.2 --- Capacity Assignment --- p.28Chapter 3.3 --- Route Assignment --- p.31Chapter 4 --- Path Switching in Cross-Connected SAN --- p.34Chapter 4.1 --- Path Switching in SAN --- p.34Chapter 4.1.1 --- Connectionless Traffic --- p.36Chapter 4.1.2 --- Connection-Oriented Traffic --- p.39Chapter 4.1.3 --- Mixed Traffic --- p.47Chapter 4.2 --- Measurement Based Algorithm --- p.53Chapter 4.3 --- Repetition Rate --- p.59Chapter 5 --- Conclusion --- p.6

Simulation and design of storage area network

Master'sMASTER OF ENGINEERIN

Evaluation of different SAN Technologies for virtual machine hosting

This thesis covers a problem which companies faces every day: Finding a Storage Area Network(SAN) solution that tackles the rising demands from users and their software and when working with virtualization environments. In this paper it will be showed a way to investigate and identify, from a selection of SAN technologies, which is the most efficient and optimal based on scenarios that fits real life experiences. The approach taken was to create an experimental setup in a controlled environment that fits real life experience. The benchmark tool bonnie++ was used to simulate activity and interpreted by an analysis script tool developed by the author. Distributed Replicated Block Device(DRBD), Network File System(NFS), Parallel Virtual File System(PVFS), Internet SCSI(ISCSI) and ATA over Ethernet(AoE) are the SAN technologies which will be evaluated and discussed. The optimal SAN technologies will be chosen based on a certain criterias such as raw performance and stability.Master i nettverks- og systemadministrasjo

Improving Storage with Stackable Extensions

Storage is a central part of computing. Driven by exponentially increasing content generation rate and a widening performance gap between memory and secondary storage, researchers are in the perennial quest to push for further innovation. This has resulted in novel ways to “squeeze” more capacity and performance out of current and emerging storage technology. Adding intelligence and leveraging new types of storage devices has opened the door to a whole new class of optimizations to save cost, improve performance, and reduce energy consumption. In this dissertation, we first develop, analyze, and evaluate three storage exten- sions. Our first extension tracks application access patterns and writes data in the way individual applications most commonly access it to benefit from the sequential throughput of disks. Our second extension uses a lower power flash device as a cache to save energy and turn off the disk during idle periods. Our third extension is designed to leverage the characteristics of both disks and solid state devices by placing data in the most appropriate device to improve performance and save power. In developing these systems, we learned that extending the storage stack is a complex process. Implementing new ideas incurs a prolonged and cumbersome de- velopment process and requires developers to have advanced knowledge of the entire system to ensure that extensions accomplish their goal without compromising data recoverability. Futhermore, storage administrators are often reluctant to deploy specific storage extensions without understanding how they interact with other ex- tensions and if the extension ultimately achieves the intended goal. We address these challenges by using a combination of approaches. First, we simplify the stor- age extension development process with system-level infrastructure that implements core functionality commonly needed for storage extension development. Second, we develop a formal theory to assist administrators deploy storage extensions while guaranteeing that the given high level goals are satisfied. There are, however, some cases for which our theory is inconclusive. For such scenarios we present an experi- mental methodology that allows administrators to pick an extension that performs best for a given workload. Our evaluation demostrates the benefits of both the infrastructure and the formal theory