Fault Tolerance Protection and Raid Technology for Networks: a Primer
Total Page:16
File Type:pdf, Size:1020Kb
Load more
										Recommended publications
									
								- 
												  Copy on Write Based File Systems Performance Analysis and ImplementationCopy On Write Based File Systems Performance Analysis And Implementation Sakis Kasampalis Kongens Lyngby 2010 IMM-MSC-2010-63 Technical University of Denmark Department Of Informatics Building 321, DK-2800 Kongens Lyngby, Denmark Phone +45 45253351, Fax +45 45882673 [email protected] www.imm.dtu.dk Abstract In this work I am focusing on Copy On Write based file systems. Copy On Write is used on modern file systems for providing (1) metadata and data consistency using transactional semantics, (2) cheap and instant backups using snapshots and clones. This thesis is divided into two main parts. The first part focuses on the design and performance of Copy On Write based file systems. Recent efforts aiming at creating a Copy On Write based file system are ZFS, Btrfs, ext3cow, Hammer, and LLFS. My work focuses only on ZFS and Btrfs, since they support the most advanced features. The main goals of ZFS and Btrfs are to offer a scalable, fault tolerant, and easy to administrate file system. I evaluate the performance and scalability of ZFS and Btrfs. The evaluation includes studying their design and testing their performance and scalability against a set of recommended file system benchmarks. Most computers are already based on multi-core and multiple processor architec- tures. Because of that, the need for using concurrent programming models has increased. Transactions can be very helpful for supporting concurrent program- ming models, which ensure that system updates are consistent. Unfortunately, the majority of operating systems and file systems either do not support trans- actions at all, or they simply do not expose them to the users.
- 
												  The Title Title: Subtitle March 2007sub title The Title Title: Subtitle March 2007 Copyright c 2006-2007 BSD Certification Group, Inc. Permission to use, copy, modify, and distribute this documentation for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE DOCUMENTATION IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DOCUMENTATION INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CON- SEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEG- LIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS DOCUMENTATION. NetBSD and pkgsrc are registered trademarks of the NetBSD Foundation, Inc. FreeBSD is a registered trademark of the FreeBSD Foundation. Contents Introduction vii 1 Installing and Upgrading the OS and Software 1 1.1 Recognize the installation program used by each operating system . 2 1.2 Recognize which commands are available for upgrading the operating system 6 1.3 Understand the difference between a pre-compiled binary and compiling from source . 8 1.4 Understand when it is preferable to install a pre-compiled binary and how to doso ...................................... 9 1.5 Recognize the available methods for compiling a customized binary . 10 1.6 Determine what software is installed on a system . 11 1.7 Determine which software requires upgrading . 12 1.8 Upgrade installed software . 12 1.9 Determine which software have outstanding security advisories .
- 
												  The Google File System (GFS)The Google File System (GFS), as described by Ghemwat, Gobioff, and Leung in 2003, provided the architecture for scalable, fault-tolerant data management within the context of Google. These architectural choices, however, resulted in sub-optimal performance in regard to data trustworthiness (security) and simplicity. Additionally, the application- specific nature of GFS limits the general scalability of the system outside of the specific design considerations within the context of Google. SYSTEM DESIGN: The authors enumerate their specific considerations as: (1) commodity components with high expectation of failure, (2) a system optimized to handle relatively large files, particularly multi-GB files, (3) most writes to the system are concurrent append operations, rather than internally modifying the extant files, and (4) a high rate of sustained bandwidth (Section 1, 2.1). Utilizing these considerations, this paper analyzes the success of GFS’s design in achieving a fault-tolerant, scalable system while also considering the faults of the system with regards to data-trustworthiness and simplicity. Data-trustworthiness: In designing the GFS system, the authors made the conscious decision not prioritize data trustworthiness by allowing applications to access ‘stale’, or not up-to-date, data. In particular, although the system does inform applications of the chunk-server version number, the designers of GFS encouraged user applications to cache chunkserver information, allowing stale data accesses (Section 2.7.2, 4.5). Although possibly troubling
- 
												  Introspection-Based Verification and ValidationIntrospection-Based Verification and Validation Hans P. Zima Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 E-mail: [email protected] Abstract This paper describes an introspection-based approach to fault tolerance that provides support for run- time monitoring and analysis of program execution. Whereas introspection is mainly motivated by the need to deal with transient faults in embedded systems operating in hazardous environments, we show in this paper that it can also be seen as an extension of traditional V&V methods for dealing with program design faults. Introspection—a technology supporting runtime monitoring and analysis—is motivated primarily by dealing with faults caused by hardware malfunction or environmental influences such as radiation and thermal effects [4]. This paper argues that introspection can also be used to handle certain classes of faults caused by program design errors, complementing the classical approaches for dealing with design errors summarized under the term Verification and Validation (V&V). Consider a program, P , over a given input domain, and assume that the intended behavior of P is defined by a formal specification. Verification of P implies a static proof—performed before execution of the program—that for all legal inputs, the result of applying P to a legal input conforms to the specification. Thus, verification is a methodology that seeks to avoid faults. Model checking [5, 3] refers to a special verification technology that uses exploration of the full state space based on a simplified program model. Verification techniques have been highly successful when judiciously applied under the right conditions in well-defined, limited contexts.
- 
												  Fault-Tolerant Components on AWSFault-Tolerant Components on AWS November 2019 This paper has been archived For the latest technical information, see the AWS Whitepapers & Guides page: Archivedhttps://aws.amazon.com/whitepapers Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Archived Contents Introduction .......................................................................................................................... 1 Failures Shouldn’t Be THAT Interesting ............................................................................. 1 Amazon Elastic Compute Cloud ...................................................................................... 1 Elastic Block Store ........................................................................................................... 3 Auto Scaling ....................................................................................................................
- 
												  Disk Array Data Organizations and RAIDGuest Lecture for 15-440 Disk Array Data Organizations and RAID October 2010, Greg Ganger © 1 Plan for today Why have multiple disks? Storage capacity, performance capacity, reliability Load distribution problem and approaches disk striping Fault tolerance replication parity-based protection “RAID” and the Disk Array Matrix Rebuild October 2010, Greg Ganger © 2 Why multi-disk systems? A single storage device may not provide enough storage capacity, performance capacity, reliability So, what is the simplest arrangement? October 2010, Greg Ganger © 3 Just a bunch of disks (JBOD) A0 B0 C0 D0 A1 B1 C1 D1 A2 B2 C2 D2 A3 B3 C3 D3 Yes, it’s a goofy name industry really does sell “JBOD enclosures” October 2010, Greg Ganger © 4 Disk Subsystem Load Balancing I/O requests are almost never evenly distributed Some data is requested more than other data Depends on the apps, usage, time, … October 2010, Greg Ganger © 5 Disk Subsystem Load Balancing I/O requests are almost never evenly distributed Some data is requested more than other data Depends on the apps, usage, time, … What is the right data-to-disk assignment policy? Common approach: Fixed data placement Your data is on disk X, period! For good reasons too: you bought it or you’re paying more … Fancy: Dynamic data placement If some of your files are accessed a lot, the admin (or even system) may separate the “hot” files across multiple disks In this scenario, entire files systems (or even files) are manually moved by the system admin to specific disks October 2010, Greg
- 
												  Network Reliability and Fault ToleranceNetwork Reliability and Fault Tolerance Muriel Medard´ [email protected] Laboratory for Information and Decision Systems Room 35-212 Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA 02139 Steven S. Lumetta [email protected] Coordinated Science Laboratory University of Illinois Urbana-Champaign 1308 W. Main Street, Urbana, IL 61801 1 Introduction The majority of communications applications, from cellular telephone conversations to credit card transactions, assume the availability of a reliable network. At this level, data are expected to tra- verse the network and to arrive intact at their destination. The physical systems that compose a network, on the other hand, are subjected to a wide range of problems, ranging from signal distor- tion to component failures. Similarly, the software that supports the high-level semantic interface 1 often contains unknown bugs and other latent reliability problems. Redundancy underlies all ap- proaches to fault tolerance. Definitive definitions for all concepts and terms related to reliability, and, more broadly, dependability, can be found in [AAC+92]. Designing any system to tolerate faults first requires the selection of a fault model, a set of possible failure scenarios along with an understanding of the frequency, duration, and impact of each scenario. A simple fault model merely lists the set of faults to be considered; inclusion in the set is decided based on a combination of expected frequency, impact on the system, and feasibility or cost of providing protection. Most reliable network designs address the failure of any single component, and some designs tolerate multiple failures. In contrast, few attempt to handle the adversarial conditions that might occur in a terrorist attack, and cataclysmic events are almost never addressed at any scale larger than a city.
- 
												  Identify Storage Technologies and Understand RAIDLESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals IdentifyIdentify StorageStorage TechnologiesTechnologies andand UnderstandUnderstand RAIDRAID LESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals Lesson Overview In this lesson, you will learn: Local storage options Network storage options Redundant Array of Independent Disk (RAID) options LESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals Anticipatory Set List three different RAID configurations. Which of these three bus types has the fastest transfer speed? o Parallel ATA (PATA) o Serial ATA (SATA) o USB 2.0 LESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals Local Storage Options Local storage options can range from a simple single disk to a Redundant Array of Independent Disks (RAID). Local storage options can be broken down into bus types: o Serial Advanced Technology Attachment (SATA) o Integrated Drive Electronics (IDE, now called Parallel ATA or PATA) o Small Computer System Interface (SCSI) o Serial Attached SCSI (SAS) LESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals Local Storage Options SATA drives have taken the place of the tradition PATA drives. SATA have several advantages over PATA: o Reduced cable bulk and cost o Faster and more efficient data transfer o Hot-swapping technology LESSON 4.1_4.2 98-365 Windows Server Administration Fundamentals Local Storage Options (continued) SAS drives have taken the place of the traditional SCSI and Ultra SCSI drives in server class machines. SAS have several
- 
												  Increasing Reliability and Fault Tolerance of a Secure Distributed Cloud StorageIncreasing reliability and fault tolerance of a secure distributed cloud storage Nikolay Kucherov1;y, Mikhail Babenko1;yy, Andrei Tchernykh2;z, Viktor Kuchukov1;zz and Irina Vashchenko1;yz 1 North-Caucasus Federal University,Stavropol,Russia 2 CICESE Research Center,Ensenada,Mexico E-mail: [email protected], [email protected], [email protected], [email protected], [email protected] Abstract. The work develops the architecture of a multi-cloud data storage system based on the principles of modular arithmetic. This modification of the data storage system allows increasing reliability of data storage and fault tolerance of the cloud system. To increase fault- tolerance, adaptive data redistribution between available servers is applied. This is possible thanks to the introduction of additional redundancy. This model allows you to restore stored data in case of failure of one or more cloud servers. It is shown how the proposed scheme will enable you to set up reliability, redundancy, and reduce overhead costs for data storage by adapting the parameters of the residual number system. 1. Introduction Currently, cloud services, Google, Amazon, Dropbox, Microsoft OneDrive, providing cloud storage, and data processing services, are gaining high popularity. The main reason for using cloud products is the convenience and accessibility of the services offered. Thanks to the use of cloud technologies, it is possible to save financial costs for maintaining and maintaining servers for storing and securing information. All problems arising during the storage and processing of data are transferred to the cloud provider [1]. Distributed infrastructure represents the conditions in which competition for resources between high-priority computing tasks of data analysis occurs regularly [2].
- 
												  • RAID, an Acronym for Redundant Array of Independent Disks Was Invented to Address Problems of Disk Reliability, Cost, and PerformanceRAID • RAID, an acronym for Redundant Array of Independent Disks was invented to address problems of disk reliability, cost, and performance. • In RAID, data is stored across many disks, with extra disks added to the array to provide error correction (redundancy). • The inventors of RAID, David Patterson, Garth Gibson, and Randy Katz, provided a RAID taxonomy that has persisted for a quarter of a century, despite many efforts to redefine it. 1 RAID 0: Striped Disk Array • RAID Level 0 is also known as drive spanning – Data is written in blocks across the entire array . 2 RAID 0 • Recommended Uses: – Video/image production/edition – Any app requiring high bandwidth – Good for non-critical storage of data that needs to be accessed at high speed • Good performance on reads and writes • Simple design, easy to implement • No fault tolerance (no redundancy) • Not reliable 3 RAID 1: Mirroring • RAID Level 1, also known as disk mirroring , provides 100% redundancy, and good performance. – Two matched sets of disks contain the same data. 4 RAID 1 • Recommended Uses: – Accounting, payroll, financial – Any app requiring high reliability (mission critical storage) • For best performance, controller should be able to do concurrent reads/writes per mirrored pair • Very simple technology • Storage capacity cut in half • S/W solutions often do not allow “hot swap” • High disk overhead, high cost 5 RAID 2: Bit-level Hamming Code ECC Parity • A RAID Level 2 configuration consists of a set of data drives, and a set of Hamming code drives. – Hamming code drives provide error correction for the data drives.
- 
												  Summer Student Project ReportSummer Student Project Report Dimitris Kalimeris National and Kapodistrian University of Athens June { September 2014 Abstract This report will outline two projects that were done as part of a three months long summer internship at CERN. In the first project we dealt with Worldwide LHC Computing Grid (WLCG) and its information sys- tem. The information system currently conforms to a schema called GLUE and it is evolving towards a new version: GLUE2. The aim of the project was to develop and adapt the current information system of the WLCG, used by the Large Scale Storage Systems at CERN (CASTOR and EOS), to the new GLUE2 schema. During the second project we investigated different RAID configurations so that we can get performance boost from CERN's disk systems in the future. RAID 1 that is currently in use is not an option anymore because of limited performance and high cost. We tried to discover RAID configurations that will improve the performance and simultaneously decrease the cost. 1 Information-provider scripts for GLUE2 1.1 Introduction The Worldwide LHC Computing Grid (WLCG, see also 1) is an international collaboration consisting of a grid-based computer network infrastructure incor- porating over 170 computing centres in 36 countries. It was originally designed by CERN to handle the large data volume produced by the Large Hadron Col- lider (LHC) experiments. This data is stored at CERN Storage Systems which are responsible for keeping and making available more than 100 Petabytes (105 Terabytes) of data to the physics community. The data is also replicated from CERN to the main computing centres within the WLCG.
- 
												  RAID Configuration Guide Motherboard E14794 Revised Edition V4 August 2018RAID Configuration Guide Motherboard E14794 Revised Edition V4 August 2018 Copyright © 2018 ASUSTeK COMPUTER INC. All Rights Reserved. No part of this manual, including the products and software described in it, may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any language in any form or by any means, except documentation kept by the purchaser for backup purposes, without the express written permission of ASUSTeK COMPUTER INC. (“ASUS”). Product warranty or service will not be extended if: (1) the product is repaired, modified or altered, unless such repair, modification of alteration is authorized in writing by ASUS; or (2) the serial number of the product is defaced or missing. ASUS PROVIDES THIS MANUAL “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OR CONDITIONS OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. IN NO EVENT SHALL ASUS, ITS DIRECTORS, OFFICERS, EMPLOYEES OR AGENTS BE LIABLE FOR ANY INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES (INCLUDING DAMAGES FOR LOSS OF PROFITS, LOSS OF BUSINESS, LOSS OF USE OR DATA, INTERRUPTION OF BUSINESS AND THE LIKE), EVEN IF ASUS HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES ARISING FROM ANY DEFECT OR ERROR IN THIS MANUAL OR PRODUCT. SPECIFICATIONS AND INFORMATION CONTAINED IN THIS MANUAL ARE FURNISHED FOR INFORMATIONAL USE ONLY, AND ARE SUBJECT TO CHANGE AT ANY TIME WITHOUT NOTICE, AND SHOULD NOT BE CONSTRUED AS A COMMITMENT BY ASUS. ASUS ASSUMES NO RESPONSIBILITY OR LIABILITY FOR ANY ERRORS OR INACCURACIES THAT MAY APPEAR IN THIS MANUAL, INCLUDING THE PRODUCTS AND SOFTWARE DESCRIBED IN IT.