Computing Networks E-Book

Pascale Vicat-Blanc

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 316

Veröffentlichungsjahr: 2013

Beschreibung

"Computing Networks" explores the core of the new distributed computing infrastructures we are using today: the networking systems of clusters, grids and clouds. It helps network designers and distributed-application developers and users to better understand the technologies, specificities, constraints and benefits of these different infrastructures' communication systems.

Cloud Computing will give the possibility for millions of users to process data anytime, anywhere, while being eco-friendly. In order to deliver this emerging traffic in a timely, cost-efficient, energy-efficient, and reliable manner over long-distance networks, several issues such as quality of service, security, metrology, network-resource scheduling and virtualization are being investigated since 15 years. "Computing Networks" explores the core of clusters, grids and clouds networks, giving designers, application developers and users the keys to better construct and use these powerful infrastructures.

Leseprobe

Table of Contents

Introduction

Chapter 1: From Multiprocessor Computers to the Clouds

1.1. The explosion of demand for computing power

1.2. Computer clusters

1.3. Computing grids

1.4. Computing in a cloud

1.5. Conclusion

Chapter 2: Utilization of Network Computing Technologies

2.1. Anatomy of a distributed computing application

2.2. Programming models of distributed parallel applications

2.3. Coordination of distributed resources in a grid

2.4. Conclusion

Chapter 3: Specificities of Computing Networks

3.1. Typology of computing networks

3.2. Network transparency

3.3. Detailed analysis of characteristics expected from protocols

3.4. Conclusion

Chapter 4: The Challenge of Latency in Computing Clusters

4.1. Key principles of high-performance networks for clusters

4.2. Software support for high-performance networks

4.3. Description of the main high-performance networks

4.4. Convergence between fast and traditional networks

4.5. Conclusion

Chapter 5: The Challenge of Throughput and Distance

5.1. Obstacles to high rate

5.2. Operating principle and limits of TCP congestion control

5.3. Limits of TCP over long distances

5.4. Configuration of TCP for high speed

5.5. Alternative congestion-control approaches to that of standard TCP

5.6. Exploration of TCP variants for very high rate

5.7. Conclusion

Chapter 6: Measuring End-to-End Performances

6.1. Objectives of network measurement and forecast in a grid

6.2. Problem and methods

6.3. Grid network-performance measurement systems

6.4. Performance forecast

6.5. Conclusion

Chapter 7: Optical Technology and Grids

7.1. Optical networks and switching paradigms

7.2. Functional planes of transport networks

7.3. Unified control plane: GMPLS/automatic switched transport networks

Chapter 8: Bandwidth on Demand

8.1. Current service model: network neutrality

8.2. Peer model for bandwidth-delivery services

8.3. Overlay model for bandwidth-providing services

8.4. Bandwidth market

8.5. Conclusion

Chapter 9: Security of Computing Networks

9.1. Introductory example

9.2. Principles and methods

9.3. Communication security

9.4. Network virtualization and security

9.5. Conclusion

Chapter 10: Practical Guide for the Configuration of High-speed Networks

10.1. Hardware configuration

10.2. Importance of the tuning of TCP parameters

10.3. Short practical tuning guide

10.4. Use of multi-flow

10.5. Conclusion

Conclusion From Grids to the Future Internet

Bibliography

Acronyms and Definitions

Index

First published 2011 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd 27-37 St George’s Road London SW19 4EU UKwww.iste.co.ukJohn Wiley & Sons, Inc. 111 River Street Hoboken, NJ 07030 USAwww.wiley.com

© ISTE Ltd 2011

The rights of Pascale Vicat-Blanc, Sébastien Soudan, Romaric Guillier, Brice Goglin to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Cataloging-in-Publication Data

Reseaux de calcul. English

Computing networks : from cluster to cloud computing / Pascale Vicat-Blanc ... [et al.].

p. cm.

Includes bibliographical references and index.

ISBN 978-1-84821-286-2

1. Computer networks. I. Vicat-Blanc, Pascale. II. Title.

TK5105.5.R448613 2011 004.6--dc22

2011006658

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library ISBN 978-1-84821-286-2

Introduction

Since the advent of the computer in 1940, computing power needs have not ceased to increase. Today, great scientific fields such as high-energy physics, astrophysics, climatology, biology and medical imagery rely on new mutualization technologies and worldwide sharing of computer potential across international grids to meet the huge demand for data processing. Every day, researchers submit hundreds of computations to large-scale distributed infrastructures such as the European Enabling Grids for E-sciencE grid (EGEE) [EGE 04], which gathers more than 100,000 processors. Soon European Grid Infrastructure (EGI) and TeraGrid [PRO 11] in the United States will each be able to aggregate more than double this number of processors. In the near future many industrial domains, such as automobile, energy and transport, which are increasingly relying on digital simulation, will be able to benefit from large shared reservoirs of computer resources. This approach will shortly be extended to e-commerce, finance and the leisure industry.

Over the past 15 years, three key technologies have followed each other in response to this growing computing power demand. These technologies embody the revolution of network computing: computer clusters, computing grids and computing clouds. A quick definition of these is as follows:

– a computing cluster is a collection of PCs interconnected via local-area, very-low-latency, high-speed networks;

– a computing grid is the aggregation of a very large number of distributed computing and storage resources, interconnected via wide-area networks. There are computing grids dedicated to intensive computations of data grids that store, process and give access to massive amounts of data in the order of hundreds of gigabytes or even several terabytes;

– a computing cloud provides access services to resources via the Internet. The underlying infrastructure is totally concealed from users. The available resources are generally virtual machines housed in resource centers, also called data centers.

Originally, it was the spectacular advances in transmission and communication technologies that enabled researchers to imagine these distributed architectures. These technologies made the aggregation and mutualization of computer equipment possible, which led to the rise in power of global computing. The hardware and software of interconnection networks, which are transparent in appearance, play a complex role that is difficult to grasp and not often studied. Yet the place of the network is central and its evolution will certainly be a key to ubiquitous computer systems to come.

Indeed, to make full use of a mutualized communication network, sharing policies implemented by robust and scalable arbitration and orchestration mechanisms are necessary. Today these mechanisms are included in distributed software called communication protocols. These protocols mask the complexity of the hardware and the organization of exchanges. Services of information transfer over a network rely on communication protocols and software that are built according to a layered model and the end-to-end principle. These architectural principles offer an interesting and robust compromise between the need for reliability and that for performance. They are well adapted for low-to-average speeds and unreliable network infrastructures, both when transport needs are relatively homogeneous and when security constraints are rather low. In the context of high-speed networks and computing grid environments, the orders of magnitude and ratios of the constants in use are quite far from the hypotheses initially made for communication software protocols and architecture design. For example, the size of an Ethernet frame (between 64 and 1,500 bytes) – a parameter that indirectly conditions the maximum size of transfer units sent over an IP network – was defined to satisfy propagation constraints on a 200 m coaxial cable and a throughput of 10 Mbit/s. Today optical links are used and throughputs can be greater than 10 Gbit/s. At the time when the Internet Protocol (IP) was being designed, access rates were in the order of 64 kbit/s in wide-area networks. Today, optical fibers are deployed with access rates from 100 Mbit/s to 1 Gbit/s. There are links of over 100 Gbit/s in network cores.

In the Internet, since the workload is not controlled by the network itself, it is traditionally the transport layer – the first end-to-end layer – that carries out the adaptation to fluctuations in performance linked to load changes. The complexity of the transport layer depends on the quality of service offered by the underlying network in terms of strict delay or loss-ratio service guarantees. In the IP model, which offers a best-effort network service, two main transport protocols are classically used:

– a rudimentary protocol, the User Datagram Protocol or UDP, which only carries out stream multiplexing; and

– a very sophisticated reliable protocol, Transmission Control Protocol or TCP, which carries out the adaptation to packet losses as well as congestion control by send-rate control. TCP was designed for a network layer with no guaranteed quality of service (IP), for local-area networks and low-speed wide-area networks, and for a limited number of application classes.

The transport protocols are not really well adapted to very-high-speed infrastructures. Let us take the example of a simple TCP connection over a link between Lyon (France) and Montreal (Canada), with a round trip delay in the order of 100ms and a 10 Gbit end-to-end throughput. Due to the design of the TCP congestion-avoidance algorithm, if one single packet is lost, it will take one hour and 40 minutes to repair and regain maximum speed. The TCP protocol is designed to react dynamically (i.e. in an interval of a few milliseconds) to congestion phenomena. It is not very reactive, however, in such conditions!

Over the past 10 years, a certain number of alternatives to TCP have been put forward and introduced in modern exploitation systems.

The protocol aspect is not the sole parameter to take into consideration for evaluating and improving end-to-end performance. Actually, in the very core of the communication nodes used, delays due to different data movement and control operations within a machine are significant compared to the delays encountered on the network itself (cables and routers). The heterogeneity of performance needs must also be taken into consideration.

The protocols used in the context of distributed computing have gradually became increasingly diverse because of the heterogeneity of the underlying physical technologies and applications needs. When the end-user of a cluster or a grid struggles to obtain the performance, however, he or she could expect delays with regard to the theoretical performance of the hardware used. He or she often has difficulties understanding where the problems with performance come from.

For this reason, this book invites the reader to concentrate more specifically on the core of distributed multi-machine architectures: the interconnection network and its communication protocols. The objective is to present, synthesize and articulate the different network technologies used by current and future distributed computing infrastructures. As these technologies are very heterogeneous in their physical characteristics and software, our aim is to propose the correct level of abstraction to help the reader structure and understand the main problems. It distinguishes the guidelines that, on the one hand, have oriented the technological evolution at the hardware and software levels, and on the other hand can guide programmers and users of distributed computing applications to adopt a programming model and an infrastructure adapted to their specific needs.

This book therefore has two objectives:

– to enable the reader who is familiar with communication networks to better understand the stakes and challenges that the new distributed computing revolution poses to networks and to their communication software;

– to enable the reader who is familiar with distributed computing to better understand the limits of current hardware and software tools, and how he or she can best adapt his or her application to the computing and communication infrastructure that is at his or her disposal to obtain the best possible performance.

To achieve these two objectives, we alternately move from one point of view to the other, introducing the core principles of distributed computing and networks and progressively detailing the most innovative approaches in these two fields.

In Chapter 1, we identify the needs, motivations and forces pushing the computer sector, over the years, towards distributed computing and the massive use of computing networks. We go into the details of the different network computing technologies that have evolved and show the technological and conceptual differences between them.

In Chapter 2 we classify distributed computing applications and analyze the communication specificities and constraints of each one of these classes of applications. In particular, we introduce the Message-Passing Interface communication library, or MPI, which is frequently used by distributed parallel application programmers.

In Chapter 3 we review the core principles of traditional communication networks and their protocols. We make an inventory of their limits compared to distributed computing constraints, which are introduced in the previous chapter. We then analyze the path of communications in a TCP/IP context.

The next two chapters are devoted to a detailed analysis of two major challenges that distributed computing poses to the network: latency and throughput. Two types of characteristic applications serve to illustrate their aim:

– delay-sensitive parallel computing applications; and

– communication-intensive, throughput-sensitive applications

In these chapters, we also discuss the direct interaction between the hardware level and the software level – a characteristic element of distributed computing.

Chapter 4 studies how the challenge of latency was overcome in computer cluster infrastructures to address the needs of applications that are very sensitive to information-routing delay between computing units.

Chapter 5 focuses on the needs of applications transferring significant masses of data in order to take them from their acquisition point to the computing centers where they are processed as well as to move them between storage spaces to conserve them and make them available to large and very scattered communities. We therefore study how the TCP protocol reacts in high bandwidth-delay product environments and detail the different approaches put forward to enable high-speed transport of information over very long distances.

Chapter 6 deals with performance measurement and prediction. It enables the reader, coming from the field of distributed computing, to understand the contributions of network performance measurement, prediction infrastructures and tools.

Chapter 7 shows how new optical switching technologies make it possible to provide a protected access to a communication capability adapted to the needs of each application.

Chapter 8 presents new dynamic bandwidth-management services, such as those currently proposed in the Open Grid Forum that suggest solutions for applications with sporadic needs relating to speeds that are not very high.

Chapter 9 introduces the issue of security and its principles in computing networks. This chapter presents the main solutions currently deployed as well as a few keys capable of increasing user confidence in distributed computing infrastructures.

Chapter 10 proposes a few protocol- and system-parameterization examples and exercises for obtaining high performance in a very-high-speed network with tools currently available in the Linux system.

To conclude, we summarize the different network technologies and protocols used in network computing, and provide a few perspectives for future networks that will integrate, among other things, our future worldwide computing power reserve.

Chapter 1

From Multiprocessor Computers to the Clouds

1.1. The explosion of demand for computing power

The demand for computing power continues to grow because of the technological advances in methods of digital acquisition and processing, the subsequent explosion of volumes of data, and the expansion of connectivity and information exchange. This ever-increasing demand varies depending on the scientific, industrial and domestic sectors considered.

Scientific applications have always needed increasing computing resources. Nevertheless, a new fact has appeared in the past few years: today’s science relies on a very complex interdependence between disciplines, technologies and equipment.

In many disciplines the scientist can no longer work alone at his or her table or with his or her blank sheet of paper. He or she must rely on other specialists to provide him or her with the complementary and indispensable technical and methodological tools for his or her own research. This is what is called the development of multidisciplinarity.