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Bio-Inspired Computing and Networking
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Bio-Inspired Computing and Networking

Bio-Inspired Computing and Networking

ByYang Xiao
Edition 1st Edition
First Published 2011
eBook Published 19 April 2016
Pub. location Boca Raton
Imprint CRC Press
DOIhttps://doi.org/10.1201/b10781
Pages 552 pages
eBook ISBN 9781420080339
SubjectsComputer Science, Engineering & Technology
Get Citation

Get Citation

Xiao, Y. (2011). Bio-Inspired Computing and Networking. Boca Raton: CRC Press, https://doi.org/10.1201/b10781
ABOUT THIS BOOK

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract
CONTENTS
ABOUT THIS BOOK

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract
ABOUT THIS BOOK
ABOUT THIS BOOK

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

TABLE OF CONTENTS
part |2 pages
Section I. ANIMAL BEHAVIORS AND ANIMAL COMMUNICATIONS
chapter 1|16 pages
Animal Models for Computing and Communications: Past Approaches and Future Challenges
ByKAREN L. BALES, CAROLYN D. KITZMANN
View abstract
chapter 2|22 pages
Social Behaviors of the California Sea Lion, Bottlenose Dolphin, and Orca Whale
ByNEIL WILLIAM ADAMS AND YANG XIAO
View abstract
part |2 pages
Section II. BIO-INSPIRED COMPUTING AND ROBOTS
chapter 3|26 pages
Social Insect Societies for the Optimization of Dynamic NP-Hard Problems
BySTEPHAN A. HARTMANN, PEDRO C. PINTO, THOMAS A. RUNKLER, AND JOÃOM.C. SOUSA
View abstract
chapter 4|26 pages
Bio-Inspired Locomotion Control of the Hexapod Robot Gregor III
ByPAOLO ARENA, LUCA PATANÉ
View abstract
chapter 5|44 pages
BEECLUST: A Swarm Algorithm Derived from Honeybees: Derivation of the Algorithm, Analysis by Mathematical Models, and Implementation on a Robot Swarm
ByTHOMAS SCHMICKL, HEIKO HAMANN
View abstract
chapter 6|28 pages
Self-Organizing Data and Signal Cellular Systems
ByANDRÉ STAUFFER, GIANLUCA TEMPESTI
View abstract
chapter 7|42 pages
Bio-Inspired Process Control
ByKONRADWOJDAN, KONRAD SWIRSKI, MICHAL WARCHOL, GRZEGORZ JARMOSZEWICZ, TOMASZ CHOMIAK
View abstract
chapter 8|16 pages
Multirobot Search Using Bio-Inspired Cooperation and Communication Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ANDMONICA ANDERSON
ByBRIANAWELLMAN, QUINTON ALEXANDER
View abstract
chapter 9|18 pages
Abstractions for Planning and Control of Robotic Swarms
ByCALIN BELTA
View abstract
chapter 10|32 pages
Ant-Inspired Allocation: Top-Down Controller Design for Distributing a Robot Swarm among Multiple Tasks
BySPRING BERMAN, ÁDÁM HALÁSZ, ANDM. ANI HSIEH
View abstract
chapter 11|28 pages
Human Peripheral Nervous System Controlling Robots
ByPANAGIOTIS K. ARTEMIADIS, KOSTAS J. KYRIAKOPOULOS
View abstract
part |2 pages
Section III. BIO-INSPIRED COMMUNICATIONS AND NETWORKS
chapter 12|46 pages
Adaptive Social Hierarchies: From Nature to Networks
View abstract
chapter 13|18 pages
Chemical Relaying Protocols
ByDANIELE MIORANDI, IACOPO CARRERAS, FRANCESCO DE PELLEGRINI, IMRICH CHLAMTAC, VILMOS SIMON, AND ENDRE VARGA
View abstract
chapter 14|22 pages
Attractor Selection as Self-Adaptive Control Mechanism for Communication Networks
ByKENJI LEIBNITZ, MASAYUKI MURATA, TETSUYA YOMO
View abstract
chapter 15|18 pages
Topological Robustness of Biological Systems for Information Networks—Modularity
ByS. EUM, S. ARAKAWA, ANDMASAYUKI MURATA
View abstract
chapter 16|18 pages
Biologically Inspired Dynamic Spectrum Access in Cognitive Radio Networks
ByBARIS ATAKAN, OZGUR B. AKAN
View abstract
chapter 17|30 pages
Weakly Connected Oscillatory Networks for Information Processing
ByMICHELE BONNIN, FERNANDO CORINTO, ANDMARCO GILLI
View abstract
chapter 18|24 pages
Modeling the Dynamics of Cellular Signaling for Communication Networks
ByJIAN-QIN LIU AND KENJI LEIBNITZ
View abstract
chapter 19|40 pages
A Biologically Inspired QoS-Aware Architecture for Scalable, Adaptive, and Survivable Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . PASKORN CHAMPRASERT AND JUNICHI SUZUKI
View abstract
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