autonomic computing concepts, infrastructure, and applications

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Autonomic
Computing
Concepts, Infrastructure,
and Applications
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Autonomic
Computing
Concepts, Infrastructure,
and Applications
CRC Press is an imprint of the
Taylor & Francis Group, an informa business
Boca Raton London New York
Edited by
Manish Parashar
Salim Hariri
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CRC Press
Taylor & Francis Group
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© 2007 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
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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

and the CRC Press 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, the underlying information infrastructure (e.g., the Internet) globally
aggregates large numbers of independent computing and communication
resources, data stores, and sensor networks, and is itself similarly large, het-
erogeneous, dynamic, and complex. The combined scale, complexity, hetero-
geneity, and dynamism of networks, systems, and applications have made our
computational and information infrastructures brittle, unmanageable, and
insecure. This has necessitated the investigation of an alternate paradigm for
system and application design, which is based on strategies used by biologi-
cal systems to deal with similar challenges — a vision that has been referred
to as autonomic computing.

The Autonomic Computing Paradigm has been inspired by the human auto-
nomic nervous system. Its overarching goal is to realize computer and soft-
ware systems and applications that can manage themselves in accordance
with high-level guidance from humans. Autonomic systems are character-
ized by their self-* properties including self-configuration, self-healing, self-
optimization, and self-protection. Meeting the grand challenges of autonomic
computing requires scientific and technological advances in a wide variety
of fields, as well as new programming paradigms and software and system
architectures that support the effective integration of the constituent tech-
nologies. The goal of this handbook, titled “Autonomic Computing: Concepts,
Infrastructure and Applications,” is to give a comprehensive overview of the
state-of-the-art of this emerging research area, which many believe to be the
next paradigm for designing and implementing future computing systems
and services.
Overview of the Handbook: The handbook is organized into four parts. Part I
of the handbook focuses on the “The Autonomic Computing Paradigm” and
includes chapters that present the vision, underlying concepts, challenges and
requirements, and proposed architectures. In Chapter 1, Alan Ganek provides
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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all systems could, or indeed, should be constructed as autonomic systems, in
Chapter 2, David W.Bustard andRoy Sterritt present a requirements engineer-
ing perspective of autonomic computing and examine the implications of the
requirements of autonomic systems from a software engineering perspective.
In Chapter 3, Robbert van Renesse and Kenneth P. Birman argue that auto-

nomic systems cannot be built simply by composing autonomic components,
but that an autonomic system-wide monitoring and control infrastructure is
required as well. In Chapter 4, Manish Parashar investigates the challenges
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,in Chapter 5, John Sweitzer and Christine Draperpresent
an architecture for autonomic computing and detail its four key aspects, i.e.,
process definition, resource definition, technical reference architecture, and
application patterns. The chapter highlights the fundamental functions of the
“autonomic manager” and “touchpoint” building blocks of the architecture,
and summarizes an initial set of application patterns commonly found in
autonomic computing systems.
Parts II and III of this handbook focus on achieving self-* properties in
autonomic systems and applications. Part II presents different approaches
and infrastructures for enabling autonomic behaviors. In Chapter 6, Tom De
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
et al. investigate the use of emergent properties for constructing autonomic
systems and realizing self-* properties. In Chapter 8, Sherif Abdelwahed and
Nagarajan Kandasamy describes a more formal control theoretic approach
using model-based control and optimization strategies to design autonomic
computing systems that continually optimize their performance in response
to changing workload demands and operating conditions. Since some auto-
nomic applications cannot be built from scratch, it is necessary to transpar-
ently introduce autonomic behaviors into existing composite systems with-
out modifying the existing code. In Chapter 9, S. Masoud Sadjadi and Philip
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
and An-Cheng Huang present an architecture that separates service-specific
knowledge, represented as a service recipe, from generic functionality,
and supports automatic service-specific optimizations of a broad class of
services.
Part III of the handbook presents core enabling systems, technologies, and
services that support the realization of self-* properties in autonomic systems
and applications. In Chapter 11, Hua Liu and Manish Parashar et al. describe
the Accord programming system that extends existing programming systems
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.
In Chapter 12, Thomas Heinis et al. describe a self-configuring composition
engine for Grid and Web services that achieves self-configuring, self-tuning,
and self-healing behaviors in the presence of varying workloads. Dynamic
collaboration among self-managing resourcesis a key requirement for system-
level self-management. In Chapter 13, David Chess et al. establish a set of
behaviors, interfaces, and patterns of interaction within the Unity system to
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,
Robert Adams et al. propose an approach for the management of large scale
distributed services based on scalable publish-subscribe event systems, scal-
able WS-based deployment, and model-based management. The autonomic
systems and prototypes described in this handbook have been typically im-
plemented through middleware or through OS modifications. As an alter-
nate, in Chapter 16, Lenitra Durham et al. investigate autonomic computing

support at the hardware/physical layer and describe platform support for
autonomics.
Part IV, the final part of this handbook, focuses on specific realizations of
self-* properties in autonomic systems and applications. Chapter 17, the first
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
et al. present a system that exhibits self-* properties and successfully reallo-
cates servers when workload changes and/or when servers fail. Chapter 18
examines how a managed execution environment can be leveraged to sup-
port runtime system adaptations. In this chapter, Rean Griffith et al. describe
the Kheiron adaptation framework that dynamically attaches/detaches an
engine capable of performing reconfigurations and repairs on a target system
while it executes. Kheiron remains transparent to the application and does
not require recompilation of the application or specially compiled versions
of the runtime. In Chapter 19, Arjav Chakravarti et al. describe the Organic
Grid, which is a biologically inspired and fully decentralized approach to
the organization of computation. Organic Grid is based on the autonomous
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
between geographically distributed application components. In Chapter 20,
Viraj Bhat et al. present the design and implementation of a self-managing
data-streaming service based on online control and optimization strategies.
In Chapter 21, Bithika Khargharia et al. discuss the construction of an auto-
nomic data center using autonomic clusters, servers and device components,
and demonstrate autonomic power and performance management for a three
tier data center. In Chapter 22, Guofei Jiang et al. propose a novel fault de-
tection method based on trace analysis in application servers. The approach
uses varied-length n-grams and automata to characterize normal traces and

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to detect abnormal behaviors and faults. In Chapter 23, Guangzhi Qu and
Salim Hariri address the self-management and self-protection of networks,
and presents methodologies for effectively detecting network attacks in real
time. These methodologies configure network and system resources and ser-
vices to proactively recover from network attacks and prevent the attacks
from propagating in the network.
Once again, thegoal of this handbookis to provide readers with anoverview
of the emerging discipline of autonomic computing. We do hope that it will
lead to insights into the underlying concepts and issues, current approaches
and research efforts, and outstanding challenges of the field, and will inspire
further research in this promising area.
Acknowledgements: This book has been made possible due to the efforts and
contributions of many individuals. First and foremost, we would like to ac-
knowledge all the contributors for their tremendous efforts in puttingtogether
excellent chapters that are comprehensive, informative, and timely.We would
like to thank the reviewers for their excellent comments and suggestions.
We would also like to thank Nora Konopka, Jessica Vakili, and the team at
Taylor & Francis Group LLC–CRC Press for patiently helping us put this book
together. Finally, we would like to acknowledge the support of our families
and would like to dedicate this book to them.
Credits: Based on “Emergence: A Paradigm for Robust and Scalable
Distributed Applications”, by Richard Anthony which appeared in First
International Conference on Autonomic Computing (ICAC), New York, USA,
May 2004 IEEE.
Based on “Self-Optimization in Computer Systems via Online Control: Ap-
plication to Power Management,” by authors N. Kandasamy, S. Abdelwahed,
and J. P. Hayes in the Proceedings of the IEEE Conf. Autonomic

Computing (ICAC), pp. 54–61, 2004, C[2004] IEEE.
Based on “Online Control for Self-Management in Computing Systems,”
by authors S. Abdelwahed, N. Kandasamy, and S. Neema in the Proceeding of
the 10th IEEE Real-Time and Embedded Tech. & Application Symp. (RTAS),
pp. 368–375, 2004, c[2004] IEEE.
Based on “Building Self-adapting Services Using Service-specific Knowl-
edge”, by An-Cheng Huang and Peter Steenkiste, which appeared in Four-
teenth IEEE International Symposium on High-Performance Distributed
Computing (HPDC-14), Research Triangle Park, NC, July 24–27, 2005, C 2005
IEEE; and based on “Building Self-configuring Services Using Service-
specific Knowledge,” by An-Cheng Huang and Peter Steenkiste, which
appeared in 13th IEEE Symposium on High-Performance Distributed
Computing (HPDC’04), IEEE, June 2004, Honolulu, Hawaii, pages 45–54, C
2004 IEEE.
Based on “An autonomic service architecture for self-managing grid
application”, by H. Liu, V. Bhat, M. Parashar and S. Klasky, which appeared
in Proceedings of the 6th IEEE/ACM International Workshop on Grid
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Computing (Grid 2005), Seattle, WA, USA, IEEE Computer Society Press,
pp. 132–139, November 2005.
Based on Enablingself-management of component-based high-performance
scientific applications”, by H. Liu and M. Parashar, which appeared in
Proceedings of the 14th IEEE International Symposium on High Per-
formance Distributed Computing (HPDC 2005), Research Triangle Park, NC,
USA, IEEE Computer Society Press, pp. 59–68, July 2005.
Based on “Accord: A programming framework for autonomic applica-
tions”, by H. Liu and M. Parashar, which appeared in IEEE Transactions
on Systems, Man and Cybernetics, Special Issue on Engineering Autonomic

Systems, Editors: R. Sterritt and T. Bapty, IEEE Press, 2005.
Based on “Design and Evaluation of an Autonomic Workflow Engine”,
by Thomas Heinis, Cesare Pautasso and Gustavo Alonso which appeared
in the proceedings of the Second International Conference on Autonomic
Computing, 2005 (pp 27–38).
Based on “Implementing Diverse Messaging Models with Self-Managing
Properties using IFLOW”, by Vibhore Kumar,Zhongtang Cai, Brain F.Cooper,
Greg Eisenhauer, Karsten Schwan, Mohamed Mansour, Balasubramaniam
Seshasayee, Patrick Widener which appeared in IEEE International
Conference on Autonomic Computing, 2006, ICAC’06.
Based on Lenitra M. Durham, Milan Milenkovic, and Phil Cayton, “Plat-
form Support for Autonomic Computing: a Research Vehicle,” in Proceedings
of the Third International Conference on Autonomic Computing, pp. 293–294, June
13–16, 2006, C 2006 IEEE.
Based on Paper title “Resource Allocation for autonomic data centers
using analytic performance models” which appeared in the Proceedings of
the 2005 IEEE International Conference on Autonomic Computing (ICAC’05),
Seattle, Washington, June 13–16, 2005.
Based ontheir chapterin “Self-organizing Scheduling on the Organic Grid”.
Based on “Autonomic Power and Performance Management for Com-
puting Systems”, by Bithika Khargharia, Salim Hariri and Mazin S. Yousil
which appeared in “IEEE InternationalConferenceon Autonomic Computing,
2006, ICAC ’06.
Dr. Manish Parashar
Professor, Department of Electrical and Computer Engineering, Rutgers
The State University of New Jersey, Piscataway, NJ, USA
Dr. Salim Hariri
Professor, Department of Electrical and Computer Engineering
University of Arizona, Tucson, AZ, USA
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About the Editors
Dr. Manish Parashar is Professor of Electrical and Computer Engineering at
Rutgers University, where he also is director of the Applied Software Systems
Laboratory. He has received the Rutgers Board of Trustees Award for Excel-
lence in Research (2004-2005), NSF CAREER Award (1999), and the Enrico
Fermi Scholarship from Argonne National Laboratory (1996). His research
interests include autonomic computing, parallel and distributed computing
(including peer-to-peer and Grid computing), scientific computing, and soft-
ware engineering.
Manish is a senior member of IEEE and of the executive committee of the
IEEE Computer Society Technical Committee on Parallel Processing (TCPP),
part of the IEEE Computer Society Distinguished Visitor Program (2004-2006),
and a member of ACM. He is the co-founder of the IEEE International Confer-
ence on Autonomic Computing (ICAC) and has served as General Co-Chair
of ICAC 2004, 2005, and 2006. He is actively involved in the organization of
conferences and workshops, and has served as general and program chairs
for several conferences/workshops. He also serves on various steering com-
mittees and journal editorial boards.
Manish has co-authored over 200 technical papers in international journals
and conferences, has co-authored/edited over 15 books and proceedings,
and has contributed to several others, all in the broad area of computational
science and applied parallel and distributed computing.
Manish received a BE degree in Electronics and Telecommunications from
Bombay University, India and MS and Ph.D. degrees in Computer Engineer-
ing from Syracuse University. For more information, please visit http://www.

caip.rutgers.edu/∼parashar/.
Dr. Salim Hariri is Professor of Electrical and Computer Engineering at
The University of Arizona. He is the director of the Center for Advanced
TeleSysMatics (CAT): Next Generation Network Centric Systems. CAT is a
technology transfer center to facilitate the interactions and collaborations
among researchers in academia, industry as well as government research
labs and is a vehicle for academic research to be transitioned to industry.
Salim is the Editor-In-Chief for the Cluster Computing Journal (Springer,
that presents research techniques
and results in the area of high speed networks, parallel and distributed com-
puting, software tools, and network-centric applications. He is the founder
of the IEEE International Symposium on High Performance Distributed
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Computing (HPDC) and the co-founder of the IEEE International Confer-
ence on Autonomic Computing. His current research focuses on autonomic
computing, self protection and self-healing of networked systems and ser-
vices, and high performance distributed computing. He has co-authored over
200 journal and conference research papers, and is the co-author/editor of
three books, Tools and Environments for Parallel and Distributed Computing
(Wiley, 2004), Virtual Computing: Concept, Design and Evaluation (Kluwer,
2001), and Active Middleware Services (Kluwer, 2000).
Salim received his B.S. from Damascus University, M.S. degree in Computer
Engineering from The Ohio State University in 1982 and Ph.D. in Computer
Engineering from University of Southern California in 1986. For further in-
formation, please visit />TEAM LinG
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Contributors

Hasan Abbasi
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Sherif Abdelwahed
Institute for Software Integrated
Systems
Vanderbilt University
Nashville, TN, U.S.A.
Robert Adams
Intel
Hillsboro, OR, U.S.A.
Sandip Agarwala
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Gustavo Alonso
Department of Computer Science
ETH Zurich
Zurich, Switzerland
Richard Anthony
Department of Computer Science
University of Greenwich
Greenwich, London, UK
Gerald Baumgartner
Department of Computer Science
Louisiana State University
Baton Rouge, LA, U.S.A.
Mohamed N. Bennani
Oracle, Inc.

Portland, OR, U.S.A.
Viraj Bhat
Department of Electrical and
Computer Engineering
Rutgers University
Piscataway, NJ, U.S.A.
Kenneth P. Birman
Department of Computer Science
Cornell University
Ithaca, NY, U.S.A.
Paul Brett
Intel
Hillsboro, OR, U.S.A.
Alun Butler
Department of Computer Science
University of Greenwich
Greenwich, London, UK
David W. Bustard
School of Computing and
Information Engineering
Faculty of Engineering
University of Ulster at Coleraine
Coleraine, Co. Londonderry
Northern Ireland
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Zhongtang Cai
College of Computing
Georgia Institute of Technology

Atlanta, GA, U.S.A.
Phil Cayton
Corporate Technology Group
Intel Corporation
Hillsboro, OR, U.S.A.
Arjav Chakravarti
The MathWorks, Inc.
Natick, MA, U.S.A.
Haifeng Chen
Robust and Secure System Group
NEC Laboratories America
Princeton, NJ, U.S.A.
David M. Chess
Distributed Computing
Department
IBM Thomas J. Watson
Research Center
Hawthorne, NY, U.S.A.
Brian F. Cooper
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
TomDeWolf
Department of Computer Science
K.U. Leuven
Leuven, Belgium
Christine Draper
IBM
U.S.A.
Lenitra Durham

Corporate Technology Group
Intel Corporation
Hillsboro, OR, U.S.A.
Greg Eisenhauer
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Alan Ganek
IBM
Autonomic Computing
Somers, NY, U.S.A.
Ada Gavrilovska
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Rean Griffith
Department of Computer Science
Columbia University
New York, NY, U.S.A.
James E. Hanson
Distributed Computing
Department
IBM Thomas J. Watson
Research Center
Hawthorne, NY, U.S.A.
Salim Hariri
Department of Electrical and
Computer Engineering
University of Arizona
Tucson, AZ, U.S.A.

Thomas Heinis
Department of Computer Science
ETH Zurich
Zurich, Switzerland
Tom Holvoet
Department of Computer Science
K.U. Leuven
Leuven, Belgium
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An-Cheng Huang
Department of Computer Science
Carnegie Mellon University
Pittsburgh, PA, U.S.A.
Mohammed Ibrahim
Department of Computer Science
University of Greenwich
Greenwich, London, UK
Subu Iyer
HP Labs
Palo Alto, CA, U.S.A.
Guofei Jiang
Robust and Secure System Group
NEC Laboratories America
Princeton, NJ, U.S.A.
Gail Kaiser
Department of Computer Science
Columbia University
New York, NY, U.S.A.

Nagarajan Kandasamy
Electrical and Computer
Engineering Department
Drexel University
Philadelphia, PA, U.S.A.
Jeffrey O. Kephart
Distributed Computing
Department
IBM Thomas J. Watson
Research Center
Hawthorne, NY, U.S.A.
Bithika Khargharia
Department of Electrical and
Computer Engineering
University of Arizona
Tucson, AZ, U.S.A.
Vibhore Kumar
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Mario Lauria
Dept. of Computer Science
and Engineering
Dept. of Biomedical Informatics
The Ohio State University
Columbus, OH, U.S.A.
Hua Liu
Xerox
Webster, NY, U.S.A.
Jay Lofstead

College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Mohamed Mansour
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Philip K. McKinley
Professor of Computer Science
and Engineering
Michigan State University
East Lansing, MI, U.S.A.
Daniel A. Menasc´e
Department of Computer Science
George Mason University
Fairfax, VA, U.S.A.
Milan Milenkovic
Corporate Technology Group
Intel Corporation
Hillsboro, OR, U.S.A.
Dejan Milojicic
HP Labs
Palo Alto, CA, U.S.A.
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Manish Parashar
Department of Electrical and
Computer Engineering
Rutgers University

Piscataway, NJ, U.S.A.
Cesare Pautasso
Department of Computer Science
ETH Zurich
Zurich, Switzerland
Guangzhi Qu
Department of Electrical and
Computer Engineering
University of Arizona
Tucson, AZ, U.S.A.
Sandro Rafaeli
HP Brazil
Porto Alegre, Brazil
S. Masoud Sadjadi
School of Computing and
Information Sciences
Florida International
University
Miami, FL, U.S.A.
Karsten Schwan
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Balasubramanian Seshasayee
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Peter Steenkiste
Department of Computer
Science and Electrical

and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA, U.S.A.
Roy Sterritt
School of Computing and
Mathematics
University of Ulster
Jordanstown campus
Newtownabbey, Co. Antrim
Northern Ireland
John Sweitzer
IBM
U.S.A.
Vanish Talwar
HP Labs
Palo Alto, CA, U.S.A.
Cristian Ungureanu
Robust and Secure System Group
NEC Laboratories America
Princeton, NJ, U.S.A.
Giuseppe Valetto
Department of Computer Science
Columbia University
New York, NY, U.S.A.
Robbert van Renesse
Department of Computer Science
Cornell University
Ithaca, NY, U.S.A.
Ian Whalley
Distributed Computing

Department
IBM Thomas J. Watson
Research Center
Hawthorne, NY, U.S.A.
Steve R. White
Distributed Computing
Department
IBM Thomas J. Watson
Research Center
Hawthorne, NY, U.S.A.
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Patrick Widener
Department of Computer Science
University of New Mexico
Albuquerque, NM, U.S.A.
Matt Wolf
College of Computing
Georgia Institute of Technology
Atlanta, GA, U.S.A.
Kenji Yoshihira
Robust and Secure System Group
NEC Laboratories America
Princeton, NJ, U.S.A.
Mazin Yousif
Corporate Technology Group
Intel Corporation
Hillsboro, OR, U.S.A.
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Contents
Part I The Autonomic Computing Paradigm
1
1 Overview of Autonomic Computing: Origins, Evolution,
Direction 3
Alan Ganek
2 A Requirements Engineering Perspective on Autonomic
Systems Development 19
David W. Bustard and Roy Sterritt
3 Autonomic Computing: A System-Wide Perspective 35
Robbert van Renesse and Kenneth P. Birman
4 Autonomic Grid Computing: Concepts, Requirements,
and Infrastructure 49
Manish Parashar
5 Architecture Overview for Autonomic Computing 71
John W. Sweitzer and Christine Draper
Part II Self-* Properties — Approaches and Infrastructures 99
6 A Taxonomy for Self-
∗
Properties in Decentralized
Autonomic Computing 101
Tom De Wolf and Tom Holvoet
7 Exploiting Emergence in Autonomic Systems 121
Richard Anthony, Alun Butler, and Mohammed Ibrahim
8 A Control-Based Approach to Autonomic Performance

Management in Computing Systems 149
Sherif Abdelwahed and Nagarajan Kandasamy
9 Transparent Autonomization in Composite Systems 169
S. Masoud Sadjadi and Philip K. McKinley
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10 Recipe-Based Service Configuration and Adaptation 189
Peter Steenkiste and An-Cheng Huang
Part III Achieving Self-* Properties — Enabling Systems,
Technologies, and Services
209
11 A Programming System for Autonomic Self-Managing
Applications 211
Hua Liu and Manish Parashar
12 A Self-Configuring Service Composition Engine 237
Thomas Heinis, Cesare Pautasso, and Gustavo Alonso
13 Dynamic Collaboration in Autonomic Computing 253
David M. Chess, James E. Hanson, Jeffrey O. Kephart, Ian Whalley,
and Steve R. White
14 AutoFlow: Autonomic Information Flows for Critical
Information Systems 275
Karsten Schwan, Brian F. Cooper, Greg Eisenhauer, Ada Gavrilovska,
Matt Wolf, Hasan Abbasi, Sandip Agarwala, Zhongtang Cai,
Vibhore Kumar, Jay Lofstead, Mohamed Mansour, Balasubramanian
Seshasayee, and Patrick Widener
15 Scalable Management — Technologies for Management of
Large-Scale, Distributed Systems 305
Robert Adams, Paul Brett, Subu Iyer, Dejan Milojicic, Sandro Rafaeli,
and Vanish Talwar

16 Platform Support for Autonomic Computing: A Research
Vehicle 329
Lenitra Durham, Milan Milenkovic, Phil Cayton, and Mazin Yousif
Part IV Realization of Self * Properties 351
17 Dynamic Server Allocation for Autonomic Service Centers in the
Presence of Failures 353
Daniel A. Menasc
´
e and Mohamed N. Bennani
18 Effecting Runtime Reconfiguration in Managed Execution
Environments 369
Rean Griffith, Giuseppe Valetto, and Gail Kaiser
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November 13, 2006 10:38 9367 9367˙C000
19 Self-Organizing Scheduling on the Organic Grid 389
Arjav Chakravarti, Gerald Baumgartner, and Mario Lauria
20 Autonomic Data Streaming for High-Performance Scientific
Applications 413
Viraj Bhat, Manish Parashar, and Nagarajan Kandasamy
21 Autonomic Power and Performance Management
of Internet Data 435
Bithika Khargharia and Salim Hariri
22 Trace Analysis for Fault Detection in Application Servers 471
Guofei Jiang, Haifeng Chen, Cristian Ungureanu, and Kenji Yoshihira
23 Anomaly-Based Self Protection against Network Attacks 493
Guangzhi Qu and Salim Hariri
Index 523
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November 13, 2006 10:38 9367 9367˙C000
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