Artificial Life Cooperation Principle for Wireless Network Distributed System Design

Hong Guang Zhang; Yuan An Liu; Bi Hua Tang; Yan Qin; Zhi Peng Jia

doi:10.4028/www.scientific.net/AMR.433-440.835

Paper Titles

Algal Control by Low-Frequency, Low-Power Ultrasonic in Eutrophic Water Bodies
p.811

Optimal Allocation of Heat Exchanger Area for Vapor-Compression Heat Pump Plants
p.817

Wavelet Neural Network Optimization Based on Hybrid Hierarchy Genetic Algorithm
p.823

Urban Traffic Signal Coordinated Control Optimization with Bus Priority Based on Quantum Genetic Algorithm
p.829

Artificial Life Cooperation Principle for Wireless Network Distributed System Design
p.835

Wind Speed Forecast for Wind Farms Based on Phase Space Reconstruction of Wavelet Neural Network
p.840

The Newly AND-OR FNN Modeling and Application
p.846

Multi-Scale Stereo Analysis Based on Local Multi-Model Monogenic Image Feature Descriptors
p.853

The Application of Mutual Control Monitoring and Communication Technology in Intelligent Building Safety Mitigation System –The Design of Computer Communication Interface and Control Platform
p.860

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 433-440Artificial Life Cooperation Principle for Wireless...

Artificial Life Cooperation Principle for Wireless Network Distributed System Design

Abstract:

Wireless network distributed systems have become commonplace due to the wide availability of low-cost, high performance computers and network devices. With the increase of slave nodes of distributed systems, the performance of distributed systems often fall significantly or management infrastructure of distributed systems often does not scale well. Wireless network distributed system design method of using artificial life cooperation principle is proposed. Design principle of mutual cooperation among slave nodes and open wireless communication links of wireless network distributed systems make the topology of distributed system is able to handle the dynamic increase of system size and recover the unexpected failure of system services. The proposed design method for constructing distributed systems could optimize the scalability and reliability of distributed systems.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 433-440)

Pages:

835-839

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.433-440.835

Citation:

Cite this paper

Online since:

January 2012

Authors:

Hong Guang Zhang, Yuan An Liu, Bi Hua Tang, Yan Qin, Zhi Peng Jia

Keywords:

Artificial Life, Cooperation Principle, Distributed System, Reliability, Scalability, Wireless Network

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] J. Wanga and S. Premvuti, Resource sharing in distributed robotic systems based on a wireless medium access protocol (CSMA/CD-W), Robotics and Autonomous Systems, vol. 19, Nov. 1996, pp.33-56, doi: 10. 1016/ S0921 -8890 (96) 00032-2.

DOI: 10.1016/s0921-8890(96)00032-2

Google Scholar

[2] K. M. Ganegedara, J. A. ayalath, K. M. Kumara, D. N. Pandithage, B. G. Samaranayake, E. M. Ekanayake, et al, Implementation of a Low Cost Wireless Distributed Control System using GSM Network, IEEE Region 10 and the Third international Conference on 2008 Industrial and Information Systems, IEEE Press, Dec. 2008, pp.1-6.

DOI: 10.1109/iciinfs.2008.4798435

Google Scholar

[3] J. V. Capella, A. Bonastre, R. Ors and J. J. Serrano, Distributed and mobile systems based on wireless networks: definition of a generic control architecture, 2004 IEEE International Conference on Industrial Technology, vol. 2, Dec. 2004, pp.830-835.

DOI: 10.1109/icit.2004.1490182

Google Scholar

[4] J. Ota, Multi-agent robot systems as distributed autonomous systems, Advanced Engineering Informatics, vol. 20, Jan. 2006, pp.59-70, doi: 10. 1016 / j. aei. 2005. 06. 002.

DOI: 10.1016/j.aei.2005.06.002

Google Scholar

[5] K. J. Kim and S. B. Cho, A comprehensive overview of the applications of artificial life, Artificial Life, vol. 12, Winter 2006, pp.153-182, doi: 10. 1162 / 106454606775186455.

DOI: 10.1162/106454606775186455

Google Scholar

[6] C. G. Langton, Artificial life. Santa Fe: Addison2 Wesley Publishing Company, 1989, pp.20-23.

Google Scholar

[7] J. C. Heudin, Artificial life and evolutionary computing in machine perception, Proceedings of 1995 Computer Architectures for Machine Perception, IEEE Press, Sep. 1995, pp.418-428, doi: 10. 1109 /CAMP. 1995. 521067.

DOI: 10.1109/camp.1995.521067

Google Scholar

[8] F. R. Miranda, J. E. Kogler, E. M. Hernandez, and M. L. Netto, An artificial life approach for the animation of cognitive characters, Computers & Graphics, vol. 25, Dec. 2001, pp.955-964, doi: 10. 1016 /S0097-8493(01)00151-0.

DOI: 10.1016/s0097-8493(01)00151-0

Google Scholar

[9] H. Inoue, Y. Funyu, K. Kishino, T. Jinguji, M. Shiozawa, S. Yoshikawa and T. Nakao, Development of artificial life based optimization system, Proceedings of 2001 Parallel and Distributed Systems, IEEE Press, Jun. 2001, pp.429-436.

DOI: 10.1109/icpads.2001.934850

Google Scholar

[10] Y. K. Henry, W. K. Vicky and K. S. Alex, A cooperative control model for multiagent-based material handling systems, Expert Systems with Applications, vol. 26, Jan. 2009, pp.233-247, doi: 10. 1016/ j. eswa. 2007. 09. 025.

DOI: 10.1016/j.eswa.2007.09.025

Google Scholar

[11] H. W. Thimbleby, I. H. Witten and D. J. Pullinger, Concepts of cooperation in artificial life, IEEE Transactions on Systems, Man and Cybernetics, IEEE Press, Jul. 1995, pp.1166-1171 , doi: 10. 1109 / 21. 391298.

DOI: 10.1109/21.391298

Google Scholar