Redundant disk arrays: Reliable, parallel secondary storage

During the past decade, advances in processor and memory technology have given rise to increases in computational performance that far outstrip increases in the performance of secondary storage technology. Coupled with emerging small-disk technology, disk arrays provide the cost, volume, and capacity of current disk subsystems, by leveraging parallelism, many times their performance. Unfortunately, arrays of small disks may have much higher failure rates than the single large disks they replace. Redundant arrays of inexpensive disks (RAID) use simple redundancy schemes to provide high data reliability. The data encoding, performance, and reliability of redundant disk arrays are investigated. Organizing redundant data into a disk array is treated as a coding problem. Among alternatives examined, codes as simple as parity are shown to effectively correct single, self-identifying disk failures

Separating data from metadata for robustness and scalability

textWhen building storage systems that aim to simultaneously provide robustness, scalability, and efficiency, one faces a fundamental tension, as higher robustness typically incurs higher costs and thus hurts both efficiency and scalability. My research shows that an approach to storage system design based on a simple principle—separating data from metadata—can yield systems that address elegantly and effectively that tension in a variety of settings. One observation motivates our approach: much of the cost paid by many strong protection techniques is incurred to detect errors. This observation suggests an opportunity: if we can build a low-cost oracle to detect errors and identify correct data, it may be possible to reduce the cost of protection without weakening its guarantees. This dissertation shows that metadata, if carefully designed, can serve as such an oracle and help a storage system protect its data with minimal cost. This dissertation shows how to effectively apply this idea in three very different systems: Gnothi—a storage replication protocol that combines the high availability of asynchronous replication and the low cost of synchronous replication for a small-scale block storage; Salus—a large-scale block storage with unprecedented guarantees in terms of consistency, availability, and durability in the face of a wide range of server failures; and Exalt—a tool to emulate a large storage system with 100 times fewer machines.Computer Science

Straggler-Resilient Distributed Computing

In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of University of Bergen's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.Utbredelsen av distribuerte datasystemer har økt betydelig de siste årene. Dette skyldes først og fremst at behovet for beregningskraft øker raskere enn hastigheten til en enkelt datamaskin, slik at vi må bruke flere datamaskiner for å møte etterspørselen, og at det blir stadig mer vanlig at systemer er spredt over et stort geografisk område. Dette paradigmeskiftet medfører mange tekniske utfordringer. En av disse er knyttet til "straggler"-problemet, som er forårsaket av forsinkelsesvariasjoner i distribuerte systemer, der en beregning forsinkes av noen få langsomme noder slik at andre noder må vente før de kan fortsette. Straggler-problemet kan svekke effektiviteten til distribuerte systemer betydelig i situasjoner der en enkelt node som opplever en midlertidig overbelastning kan låse et helt system. I denne avhandlingen studerer vi metoder for å gjøre beregninger av forskjellige typer motstandsdyktige mot slike problemer, og dermed gjøre det mulig for et distribuert system å fortsette til tross for at noen noder ikke svarer i tide. Metodene vi foreslår er skreddersydde for spesielle typer beregninger. Vi foreslår metoder tilpasset distribuert matrise-vektor-multiplikasjon (som er en grunnleggende operasjon i mange typer beregninger), distribuert maskinlæring og distribuert sporing av en tilfeldig prosess (for eksempel det å spore plasseringen til kjøretøy for å unngå kollisjon). De foreslåtte metodene utnytter redundans som enten blir introdusert som en del av metoden, eller som naturlig eksisterer i det underliggende problemet, til å kompensere for manglende delberegninger. For en av de foreslåtte metodene utnytter vi redundans for også å øke effektiviteten til kommunikasjonen mellom noder, og dermed redusere mengden data som må kommuniseres over nettverket. I likhet med straggler-problemet kan slik kommunikasjon begrense effektiviteten i distribuerte systemer betydelig. De foreslåtte metodene gir signifikante forbedringer i ventetid og pålitelighet sammenlignet med tidligere metoder.The number and scale of distributed computing systems being built have increased significantly in recent years. Primarily, that is because: i) our computing needs are increasing at a much higher rate than computers are becoming faster, so we need to use more of them to meet demand, and ii) systems that are fundamentally distributed, e.g., because the components that make them up are geographically distributed, are becoming increasingly prevalent. This paradigm shift is the source of many engineering challenges. Among them is the straggler problem, which is a problem caused by latency variations in distributed systems, where faster nodes are held up by slower ones. The straggler problem can significantly impair the effectiveness of distributed systems—a single node experiencing a transient outage (e.g., due to being overloaded) can lock up an entire system. In this thesis, we consider schemes for making a range of computations resilient against such stragglers, thus allowing a distributed system to proceed in spite of some nodes failing to respond on time. The schemes we propose are tailored for particular computations. We propose schemes designed for distributed matrix-vector multiplication, which is a fundamental operation in many computing applications, distributed machine learning—in the form of a straggler-resilient first-order optimization method—and distributed tracking of a time-varying process (e.g., tracking the location of a set of vehicles for a collision avoidance system). The proposed schemes rely on exploiting redundancy that is either introduced as part of the scheme, or exists naturally in the underlying problem, to compensate for missing results, i.e., they are a form of forward error correction for computations. Further, for one of the proposed schemes we exploit redundancy to also improve the effectiveness of multicasting, thus reducing the amount of data that needs to be communicated over the network. Such inter-node communication, like the straggler problem, can significantly limit the effectiveness of distributed systems. For the schemes we propose, we are able to show significant improvements in latency and reliability compared to previous schemes.Doktorgradsavhandlin

Reducing Internet Latency : A Survey of Techniques and their Merit

Bob Briscoe, Anna Brunstrom, Andreas Petlund, David Hayes, David Ros, Ing-Jyh Tsang, Stein Gjessing, Gorry Fairhurst, Carsten Griwodz, Michael WelzlPeer reviewedPreprin

Fifth NASA Goddard Conference on Mass Storage Systems and Technologies

This document contains copies of those technical papers received in time for publication prior to the Fifth Goddard Conference on Mass Storage Systems and Technologies held September 17 - 19, 1996, at the University of Maryland, University Conference Center in College Park, Maryland. As one of an ongoing series, this conference continues to serve as a unique medium for the exchange of information on topics relating to the ingestion and management of substantial amounts of data and the attendant problems involved. This year's discussion topics include storage architecture, database management, data distribution, file system performance and modeling, and optical recording technology. There will also be a paper on Application Programming Interfaces (API) for a Physical Volume Repository (PVR) defined in Version 5 of the Institute of Electrical and Electronics Engineers (IEEE) Reference Model (RM). In addition, there are papers on specific archives and storage products

A software architecture for electro-mobility services: a milestone for sustainable remote vehicle capabilities

To face the tough competition, changing markets and technologies in automotive industry, automakers have to be highly innovative. In the previous decades, innovations were electronics and IT-driven, which increased exponentially the complexity of vehicle’s internal network. Furthermore, the growing expectations and preferences of customers oblige these manufacturers to adapt their business models and to also propose mobility-based services. One other hand, there is also an increasing pressure from regulators to significantly reduce the environmental footprint in transportation and mobility, down to zero in the foreseeable future. This dissertation investigates an architecture for communication and data exchange within a complex and heterogeneous ecosystem. This communication takes place between various third-party entities on one side, and between these entities and the infrastructure on the other. The proposed solution reduces considerably the complexity of vehicle communication and within the parties involved in the ODX life cycle. In such an heterogeneous environment, a particular attention is paid to the protection of confidential and private data. Confidential data here refers to the OEM’s know-how which is enclosed in vehicle projects. The data delivered by a car during a vehicle communication session might contain private data from customers. Our solution ensures that every entity of this ecosystem has access only to data it has the right to. We designed our solution to be non-technological-coupling so that it can be implemented in any platform to benefit from the best environment suited for each task. We also proposed a data model for vehicle projects, which improves query time during a vehicle diagnostic session. The scalability and the backwards compatibility were also taken into account during the design phase of our solution. We proposed the necessary algorithms and the workflow to perform an efficient vehicle diagnostic with considerably lower latency and substantially better complexity time and space than current solutions. To prove the practicality of our design, we presented a prototypical implementation of our design. Then, we analyzed the results of a series of tests we performed on several vehicle models and projects. We also evaluated the prototype against quality attributes in software engineering

Goddard Conference on Mass Storage Systems and Technologies, volume 2

Papers and viewgraphs from the conference are presented. Discussion topics include the IEEE Mass Storage System Reference Model, data archiving standards, high-performance storage devices, magnetic and magneto-optic storage systems, magnetic and optical recording technologies, high-performance helical scan recording systems, and low end helical scan tape drives. Additional discussion topics addressed the evolution of the identifiable unit for processing (file, granule, data set, or some similar object) as data ingestion rates increase dramatically, and the present state of the art in mass storage technology

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends

The Third NASA Goddard Conference on Mass Storage Systems and Technologies

This report contains copies of nearly all of the technical papers and viewgraphs presented at the Goddard Conference on Mass Storage Systems and Technologies held in October 1993. The conference served as an informational exchange forum for topics primarily relating to the ingestion and management of massive amounts of data and the attendant problems involved. Discussion topics include the necessary use of computers in the solution of today's infinitely complex problems, the need for greatly increased storage densities in both optical and magnetic recording media, currently popular storage media and magnetic media storage risk factors, data archiving standards including a talk on the current status of the IEEE Storage Systems Reference Model (RM). Additional topics addressed System performance, data storage system concepts, communications technologies, data distribution systems, data compression, and error detection and correction