Organic Computing -- A Paradigm Shift for Complex Systems

Organic Computing has emerged as a challenging vision for future information processing systems. Its basis is the insight that we will increasingly be surrounded by and depend on large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicating freely, and organising themselves in order to perform actions and services required by the users.

These networks of intelligent systems surrounding us open fascinating ap-plication areas and at the same time bear the problem of their controllability. Hence, we have to construct such systems as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation towards human needs as opposed to a pure implementation of the tech-nologically possible seems absolutely central. The technical systems, which can achieve these goals will have to exhibit life-like or "organic" properties. "Organic Computing Systems" adapt dynamically to their current environmental conditions. In order to cope with unexpected or undesired events they are self-organising, self-configuring, self-optimising, self-healing, self-protecting, self-explaining, and context-aware, while offering complementary interfaces for higher-level directives with respect to the desired behaviour. First steps towards adaptive and self-organising computer systems are being undertaken. Adaptivity, reconfigurability, emergence of new properties, and self-organisation are hot top-ics in a variety of research groups worldwide.

This book summarises the results of a 6-year priority research program (SPP) of the German Research Foundation (DFG) addressing these fundamental challenges in the design of Organic Computing systems. It presents and discusses the theoretical foundations of Organic Computing, basic methods and tools, learning techniques used in this context, architectural patterns and many applications. The final outlook shows that in the mean-time Organic Computing ideas have spawned a variety of promising new projects.

1100827900
Organic Computing -- A Paradigm Shift for Complex Systems

Organic Computing has emerged as a challenging vision for future information processing systems. Its basis is the insight that we will increasingly be surrounded by and depend on large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicating freely, and organising themselves in order to perform actions and services required by the users.

These networks of intelligent systems surrounding us open fascinating ap-plication areas and at the same time bear the problem of their controllability. Hence, we have to construct such systems as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation towards human needs as opposed to a pure implementation of the tech-nologically possible seems absolutely central. The technical systems, which can achieve these goals will have to exhibit life-like or "organic" properties. "Organic Computing Systems" adapt dynamically to their current environmental conditions. In order to cope with unexpected or undesired events they are self-organising, self-configuring, self-optimising, self-healing, self-protecting, self-explaining, and context-aware, while offering complementary interfaces for higher-level directives with respect to the desired behaviour. First steps towards adaptive and self-organising computer systems are being undertaken. Adaptivity, reconfigurability, emergence of new properties, and self-organisation are hot top-ics in a variety of research groups worldwide.

This book summarises the results of a 6-year priority research program (SPP) of the German Research Foundation (DFG) addressing these fundamental challenges in the design of Organic Computing systems. It presents and discusses the theoretical foundations of Organic Computing, basic methods and tools, learning techniques used in this context, architectural patterns and many applications. The final outlook shows that in the mean-time Organic Computing ideas have spawned a variety of promising new projects.

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Organic Computing -- A Paradigm Shift for Complex Systems

Organic Computing -- A Paradigm Shift for Complex Systems

Organic Computing -- A Paradigm Shift for Complex Systems

Organic Computing -- A Paradigm Shift for Complex Systems

Paperback(2011)

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Overview

Organic Computing has emerged as a challenging vision for future information processing systems. Its basis is the insight that we will increasingly be surrounded by and depend on large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicating freely, and organising themselves in order to perform actions and services required by the users.

These networks of intelligent systems surrounding us open fascinating ap-plication areas and at the same time bear the problem of their controllability. Hence, we have to construct such systems as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation towards human needs as opposed to a pure implementation of the tech-nologically possible seems absolutely central. The technical systems, which can achieve these goals will have to exhibit life-like or "organic" properties. "Organic Computing Systems" adapt dynamically to their current environmental conditions. In order to cope with unexpected or undesired events they are self-organising, self-configuring, self-optimising, self-healing, self-protecting, self-explaining, and context-aware, while offering complementary interfaces for higher-level directives with respect to the desired behaviour. First steps towards adaptive and self-organising computer systems are being undertaken. Adaptivity, reconfigurability, emergence of new properties, and self-organisation are hot top-ics in a variety of research groups worldwide.

This book summarises the results of a 6-year priority research program (SPP) of the German Research Foundation (DFG) addressing these fundamental challenges in the design of Organic Computing systems. It presents and discusses the theoretical foundations of Organic Computing, basic methods and tools, learning techniques used in this context, architectural patterns and many applications. The final outlook shows that in the mean-time Organic Computing ideas have spawned a variety of promising new projects.


Product Details

ISBN-13: 9783034801294
Publisher: Springer Basel
Publication date: 05/06/2011
Series: Autonomic Systems Series , #1
Edition description: 2011
Pages: 627
Product dimensions: 6.10(w) x 9.25(h) x 0.06(d)

Table of Contents

Chapter 1 Theoretical Foundations

1.1 Adaptivity and Self-organisation in Organic Computing Systems Hartmut Schmeck Christian Müller-Schloer Emre Çakar Moez Mnif Urban Richter 5

1.2 Quantitative Emergence Moez Mnif Christian Müller-Schloer 39

1.3 Divergence Measures as a Generalised Approach to Quantitative Emergence Dominik Fisch Martin Jänicke Christian Müller-Schloer Bernhard Sick 53

1.4 Emergent Control Peter Kreyssig Peter Dittrich 67

1.5 Constraining Self-organisation Through Corridors of Correct Behaviour: The Restore Invariant Approach Florian Nafz Hella Seebach Jan-Philipp Steghöfer Gerrit Anders Wolfgang Reif 79

1.6 Ant Inspired Methods for Organic Computing Alexander Scheidler Arne Brutschy Konrad Diwold Daniel Merkle Martin Middendorf 95

1.7 Organic Computing: Metaphor or Model? Mathias Gutmann Benjamin Rathgeber Tareq Syed 111

Chapter 2 Methods and Tools

2.1 Model-Driven Development of Self-organising Control Applications Helge Parzyjegla Arnd Schröter Enrico Seib Sebastian Holzapfel Matthäus Wander Jan Richling Arno Wacker Hans-Ulrich Heiβ Gero Mühl Torben Weis 131

2.2 How to Design and Implement Self-organising Resource-Flow Systems Hella Seebach Florian Nafz Jan-Philipp Steghöfer Wolfgang Reif 145

2.3 Monitoring and Self-awareness for Heterogeneous, Adaptive Computing Systems David Kramer Rainer Buchty Wolfgang Karl 163

2.4 Generic Emergent Computing in Chip Architectures Marc Reichenbach Ralf Seidler Dietmar Fey Benjamin Pfundt 179

2.5 Multi-objective Intrinsic Evolution of Embedded Systems Paul Kaufmann Marco Platzner 193

2.6 Organisation-Oriented Chemical Programming Naoki Matsumaru Peter Kreyssig Peter Dittrich 207

2.7 Hovering Data Clouds for Organic Computing Sebastian Ebers Sándor P. Fekete Stefan Fischer Horst Hellbrück Björn Hendriks Axel Wegener 221

Chapter 3 Learning

3.1 Aspects of Learning in OC Systems Emre Cakar Nugroho Fredivianus Jörg Hähner Jürgen Branke Christian Müller-Schloer Hartmut Schmeck 237

3.2 Combining Software and Hardware LCS for Lightweight On-chip Learning Andreas Bernauer Johannes Zeppenfeld Oliver Bringmann Andreas Herkersdorf Wolfgang Rosenstiel 253

3.3 Collaborative Learning by Knowledge Exchange Dominik Fisch Edgar Kalkowski Bernhard Sick 267

3.4 A Framework for Controlled Self-optimisation in Modular System Architectures Werner Brockmann Nils Rosemann Erik Maehle 281

3.5 Increasing Learning Speed by Imitation in Multi-robot Societies Alexander Jungmann Bernd Kleinjohann Willi Richert 295

3.6 Learning to Look at Humans Thomas Walther Rolf P. Würtz 309

Chapter 4 Architectures

4.1 Observation and Control of Organic Systems Sven Tomforde Holger Prothmann Jürgen Branke Jörg Hähner Moez Mnif Christian Müller-Schloer Urban Richter Hartmut Schmeck 325

4.2 Organic Computing Middleware for Ubiquitous Environments Michael Roth Julia Schmitt Rolf Kiefhaber Florian Kluge Theo Ungerer 339

4.3 DodOrg-A Self-adaptive Organic Many-core Architecture Thomas Ebi David Kramer Christian Schuck Alexander von Renteln Jürgen Becker Uwe Brinkschulte Jörg Henkel Wolfgang Karl 353

4.4 The Artificial Hormone System-An Organic Middleware for Self-organising Real-Time Task Allocation Alexander von Renteln Uwe Brinkschulte Mathias Pacher 369

4.5 ORCA: An Organic Robot Control Architecture Werner Brockmann Erik Maehle Karl-Erwin Grosspietsch Nils Rosemann Bojan Jakimovski 385

4.6 The EPOC Architecture-Enabling Evolution Under Hard Constraints Moritz Neukirchner Steffen Stein Rolf Ernst 399

4.7 Autonomic System on Chip Platform Abdelmajid Bouajila Johannes Zeppenfeld Walter Stechele Andreas Bernauer Oliver Bringmann Wolfgang Rosenstiel Andreas Herkersdorf 413

Chapter 5 Applications

5.1 Organic Traffic Control Holger Prothmann Sven Tomforde Jürgen Branke Jörg Hähner Christian Müller-Schloer Hartmut Schmeck 431

5.2 Methods for Improving the Flow of Traffic Sándor P. Fekete Björn Hendriks Christopher Tessars Axel Wegener Horst Hellbrück Stefan Fischer Sebastian Ebers 447

5.3 Applying ASoC to Multi-core Applications for Workload Management Johannes Zeppenfeld Abdelmajid Bouajila Walter Stechele Andreas Bernauer Oliver Bringmann Wolfgang Rosenstiel Andreas Herkersdorf 461

5.4 Efficient Adaptive Communication from Resource-Restricted Transmitters Stephan Sigg Michael Beigl Behnam Banitalebi 473

5.5 OrganicBus: Organic Self-organising Bus-Based Communication Systems Tobias Ziermann Stefan Wildermann Jürgen Teich 489

5.6 OC Principles in Wireless Sensor Networks Jakob Salzmann Ralf Behnke Dirk Timmermann 503

5.7 Application of the Organic Robot Control Architecture ORCA to the Six-Legged Walking Robot OSCAR Erik Maehle Werner Brockmann Karl-Erwin Grosspietsch Adam El Sayed Auf Bojan Jakimovski Stephan Krannich Marek Litza Raphael Maas Ahmad Al-Homsy 517

5.8 Energy-Awareness in Self-organising Robotic Exploration Teams Bastian Degener Barbara Kempkes Friedhelm Meyer auf der Heide 531

5.9 A Fast Hierarchical Learning Approach for Autonomous Robots Alexander Jungmann Bernd Kleinjohann Willi Richert 545

5.10 Emergent Computing with Marching Pixels for Real-Time Smart Camera Applications Dietmar Fey Marcus Komann 559

Chapter 6 Status and Outlook

6.1.1 OC Techniques Applied to Solve Reliability Problems in Future 1000-Core Processors Arne Garbade Sebastian Weis Sebastian Schlingmann Theo Ungerer 575

6.1.2 Dynamic Classification for Embedded Real-Time Systems Florian Kluge Jörg Mische Theo Ungerer 579

6.1.3 On the Future of Chemistry-Inspired Computing Peter Kreyssig Peter Dittrich 583

6.1.4 Agent-Based Thermal Management for Multi-core Architectures Thomas Ebi Janmartin Jahn Jörg Henkel 587

6.1.5 Trust Management-Handling Uncertainties in Embedded Systems Werner Brockmann Andreas Buschermöhle Jens Hülsmann Nils Rosemann 589

6.1.6 OC-Trust: Towards Trustworthy Organic Computing Systems Jan-Philipp Steghöfer Wolfgang Reif 593

6.1.7 Emergence in Action Matthias Werner Jan Richling Hans-Ulrich Heiss 597

6.1.8 Organic Computing in Off-highway Machines Sanaz Mostaghim Hartmut Schmeck Micaela Wünsche Marcus Geimer Timo Kautzmann 601

6.1.9 Decentralised Energy Management for Smart Homes Florian Allerding Birger Becker Hartmut Schmeck 605

6.1.10 Self-organising Distributed Smart Camera Systems Michael Wittke Jörg Hähner 609

6.1.11 Organic Network Control Bjorn Hurling Sven Tomforde Jörg Hähner 611

6.2 Organic Computing: Quo vadis? Christian Müller-Schloer Hartmut Schmeck 615

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