Table Of ContentAutonomic
Computing
Concepts, Infrastructure,
and Applications
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Autonomic
Computing
Concepts, Infrastructure,
and Applications
Edited by
Manish Parashar
Salim Hariri
Boca Raton London New York
CRC Press is an imprint of the
Taylor & Francis Group, an informa business
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CRC Press
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Library of Congress Cataloging‑in‑Publication Data
Autonomic computing : concepts, infrastructure, and applications / editor(s):
Manish Parashar and Salim Hariri.
p. cm.
Includes bibliographical references and index.
ISBN‑13: 978‑0‑8493‑9367‑9 (alk. paper)
ISBN‑10: 1‑4200‑0935‑4 (alk. paper)
1. Autonomic computing. I. Parashar, Manish, 1967‑ II. Hariri, Salim. III.
Title.
QA76.9.A97A96 2007
004‑‑dc22 2006024028
Visit the Taylor & Francis Web site at
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Dedication
To Gowrie and Anushka - Manish Parashar
To Sonia, Lana and George - Salim Hariri
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Preface
Introduction: Advances in networking and computing technologies, and
software tools have resulted in an explosive growth in applications and
information services that influence all aspects of our life. These sophisti-
cated applications and services are complex, heterogeneous, and dynamic.
Further,theunderlyinginformationinfrastructure(e.g.,theInternet)globally
aggregates large numbers of independent computing and communication
resources,datastores,andsensornetworks,andisitselfsimilarlylarge,het-
erogeneous,dynamic,andcomplex.Thecombinedscale,complexity,hetero-
geneity,anddynamismofnetworks,systems,andapplicationshavemadeour
computational and information infrastructures brittle, unmanageable, and
insecure.Thishasnecessitatedtheinvestigationofanalternateparadigmfor
systemandapplicationdesign,whichisbasedonstrategiesusedbybiologi-
calsystemstodealwithsimilarchallenges—avisionthathasbeenreferred
toasautonomiccomputing.
TheAutonomicComputingParadigmhasbeeninspiredbythehumanauto-
nomicnervoussystem.Itsoverarchinggoalistorealizecomputerandsoft-
ware systems and applications that can manage themselves in accordance
with high-level guidance from humans. Autonomic systems are character-
izedbytheirself-*propertiesincludingself-configuration,self-healing,self-
optimization,andself-protection.Meetingthegrandchallengesofautonomic
computing requires scientific and technological advances in a wide variety
offields,aswellasnewprogrammingparadigmsandsoftwareandsystem
architectures that support the effective integration of the constituent tech-
nologies.Thegoalofthishandbook,titled“AutonomicComputing:Concepts,
Infrastructure and Applications,” is to give a comprehensive overview of the
state-of-the-artofthisemergingresearcharea,whichmanybelievetobethe
next paradigm for designing and implementing future computing systems
andservices.
OverviewoftheHandbook:Thehandbookisorganizedintofourparts.PartI
ofthehandbookfocusesonthe“TheAutonomicComputingParadigm”and
includeschaptersthatpresentthevision,underlyingconcepts,challengesand
requirements,andproposedarchitectures.InChapter1,AlanGanekprovides
an overview of autonomic computing and its origins, evolution, and direc-
tion. This chapter defines autonomic computing, i.e., creating systems that
are self-aware and self-managing to help reduce management complexity,
increase availability, and enhance flexibility. Starting from the premise that
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allsystemscould,orindeed,shouldbeconstructedasautonomicsystems,in
Chapter2,DavidW.BustardandRoySterrittpresentarequirementsengineer-
ingperspectiveofautonomiccomputingandexaminetheimplicationsofthe
requirementsofautonomicsystemsfromasoftwareengineeringperspective.
In Chapter 3, Robbert van Renesse and Kenneth P. Birman argue that auto-
nomicsystemscannotbebuiltsimplybycomposingautonomiccomponents,
butthatanautonomicsystem-widemonitoringandcontrolinfrastructureis
requiredaswell.InChapter4,ManishParasharinvestigatesthechallenges
of emerging wide-area Grid environments and applications, and motivates
self-management as a means for addressing these challenges. This chapter
presents autonomic Grid computing solutions and sample autonomic Grid
applications.Finally,inChapter5,JohnSweitzerandChristineDraperpresent
anarchitectureforautonomiccomputinganddetailitsfourkeyaspects,i.e.,
process definition, resource definition, technical reference architecture, and
applicationpatterns.Thechapterhighlightsthefundamentalfunctionsofthe
“autonomicmanager”and“touchpoint”buildingblocksofthearchitecture,
and summarizes an initial set of application patterns commonly found in
autonomiccomputingsystems.
Parts II and III of this handbook focus on achieving self-* properties in
autonomic systems and applications. Part II presents different approaches
andinfrastructuresforenablingautonomicbehaviors.InChapter6,TomDe
Wolf and Tom Holvoet present a taxonomy of self-* properties for decen-
tralized autonomic computing systems, and use the taxonomy to guide the
design and verification of self-* properties. In Chapter 7, Richard Anthony
etal.investigatetheuseofemergentpropertiesforconstructingautonomic
systemsandrealizingself-*properties.InChapter8,SherifAbdelwahedand
Nagarajan Kandasamy describes a more formal control theoretic approach
usingmodel-basedcontrolandoptimizationstrategiestodesignautonomic
computingsystemsthatcontinuallyoptimizetheirperformanceinresponse
tochangingworkloaddemandsandoperatingconditions.Sincesomeauto-
nomic applications cannot be built from scratch, it is necessary to transpar-
ently introduce autonomic behaviors into existing composite systems with-
outmodifyingtheexistingcode.InChapter9,S.MasoudSadjadiandPhilip
K. McKinley address this requirement and describe transparent shaping to
enable dynamic adaptations of existing applications. Chapter 10 addresses
the design of self-* systems in which adaptive behavior can be specified as
a set of externalized adaptation strategies. In this chapter, Peter Steenkiste
andAn-ChengHuangpresentanarchitecturethatseparatesservice-specific
knowledge, represented as a service recipe, from generic functionality,
and supports automatic service-specific optimizations of a broad class of
services.
PartIIIofthehandbookpresentscoreenablingsystems,technologies,and
servicesthatsupporttherealizationofself-*propertiesinautonomicsystems
andapplications.InChapter11,HuaLiuandManishParasharetal.describe
theAccordprogrammingsystemthatextendsexistingprogrammingsystems
to enable the development of self-managing Grid applications by allowing
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application and system behaviors to be dynamically specified at runtime.
InChapter12,ThomasHeinisetal.describeaself-configuringcomposition
engineforGridandWebservicesthatachievesself-configuring,self-tuning,
and self-healing behaviors in the presence of varying workloads. Dynamic
collaborationamongself-managingresourcesisakeyrequirementforsystem-
level self-management. In Chapter 13, David Chess et al. establish a set of
behaviors,interfaces,andpatternsofinteractionwithintheUnitysystemto
support such dynamic collaborations. In Chapter 14, Karsten Schwan et al.
describe the AutoFlow project designed to meet the critical performance
requirements of distributed information flow applications. In Chapter 15,
RobertAdamsetal.proposeanapproachforthemanagementoflargescale
distributedservicesbasedonscalablepublish-subscribeeventsystems,scal-
ableWS-baseddeployment,andmodel-basedmanagement.Theautonomic
systemsandprototypesdescribedinthishandbookhavebeentypicallyim-
plemented through middleware or through OS modifications. As an alter-
nate,inChapter16,LenitraDurhametal.investigateautonomiccomputing
support at the hardware/physical layer and describe platform support for
autonomics.
PartIV,thefinalpartofthishandbook,focusesonspecificrealizationsof
self-*propertiesinautonomicsystemsandapplications.Chapter17,thefirst
chapter in this part, studies how autonomic computing techniques can be
used to dynamically allocate servers to application environments in a way
that maximizes a global utility function. In this chapter, Daniel A. Menasce
etal.presentasystemthatexhibitsself-*propertiesandsuccessfullyreallo-
catesserverswhenworkloadchangesand/orwhenserversfail.Chapter18
examines how a managed execution environment can be leveraged to sup-
portruntimesystemadaptations.Inthischapter,ReanGriffithetal.describe
the Kheiron adaptation framework that dynamically attaches/detaches an
enginecapableofperformingreconfigurationsandrepairsonatargetsystem
while it executes. Kheiron remains transparent to the application and does
not require recompilation of the application or specially compiled versions
oftheruntime.InChapter19,ArjavChakravartietal.describetheOrganic
Grid, which is a biologically inspired and fully decentralized approach to
theorganizationofcomputation.OrganicGridisbasedontheautonomous
scheduling of strongly mobile agents on a peer-to-peer network. Efficient
and robust data streaming services are a critical requirement of emerging
Grid applications, which are based on seamless interactions and coupling
betweengeographicallydistributedapplicationcomponents.InChapter20,
Viraj Bhat et al. present the design and implementation of a self-managing
data-streaming service based on online control and optimization strategies.
InChapter21,BithikaKharghariaetal.discusstheconstructionofanauto-
nomicdatacenterusingautonomicclusters,serversanddevicecomponents,
anddemonstrateautonomicpowerandperformancemanagementforathree
tier data center. In Chapter 22, Guofei Jiang et al. propose a novel fault de-
tectionmethodbasedontraceanalysisinapplicationservers.Theapproach
usesvaried-lengthn-gramsandautomatatocharacterizenormaltracesand
