ACM Home Page
Please provide us with feedback. Feedback
Design patterns from biology for distributed computing
Full text PdfPdf (490 KB)
Source ACM Transactions on Autonomous and Adaptive Systems (TAAS) archive
Volume 1 ,  Issue 1  (September 2006) table of contents
Pages: 26 - 66  
Year of Publication: 2006
ISSN:1556-4665
Authors
Ozalp Babaoglu  University of Bologna, Bologna, Italy
Geoffrey Canright  Telenor R&D, Fornebu, Norway
Andreas Deutsch  Dresden University of Technology, Dresden, Germany
Gianni A. Di Caro  Istituto “Dalle Molle” di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland
Frederick Ducatelle  Istituto “Dalle Molle” di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland
Luca M. Gambardella  Istituto “Dalle Molle” di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland
Niloy Ganguly  Dresden University of Technology, Dresden, Germany
Márk Jelasity  University of Bologna, Bologna, Italy
Roberto Montemanni  Istituto “Dalle Molle” di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland
Alberto Montresor  University of Trento, Povo (TN), Italy
Tore Urnes  Telenor R&D, Fornebu, Norway
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 57,   Downloads (12 Months): 342,   Citation Count: 22
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1152934.1152937
What is a DOI?

ABSTRACT

Recent developments in information technology have brought about important changes in distributed computing. New environments such as massively large-scale, wide-area computer networks and mobile ad hoc networks have emerged. Common characteristics of these environments include extreme dynamicity, unreliability, and large scale. Traditional approaches to designing distributed applications in these environments based on central control, small scale, or strong reliability assumptions are not suitable for exploiting their enormous potential. Based on the observation that living organisms can effectively organize large numbers of unreliable and dynamically-changing components (cells, molecules, individuals, etc.) into robust and adaptive structures, it has long been a research challenge to characterize the key ideas and mechanisms that make biological systems work and to apply them to distributed systems engineering. In this article we propose a conceptual framework that captures several basic biological processes in the form of a family of design patterns. Examples include plain diffusion, replication, chemotaxis, and stigmergy. We show through examples how to implement important functions for distributed computing based on these patterns. Using a common evaluation methodology, we show that our bio-inspired solutions have performance comparable to traditional, state-of-the-art solutions while they inherit desirable properties of biological systems including adaptivity and robustness.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
 
2
 
3
Albert, R. and Barabási, A.-L. 2002. Statistical mechanics of complex networks. Rev. Modern Physics 74, 1 (Jan.), 47--97.
 
4
Alexander, C. 1977. A Pattern Language: Towns, Buildings, Construction. Center for Environmental Structure Series. Oxford University Press.
 
5
Arbib, M. A., Érdi, P., and Szentágothai, J. 1997. Neural Organization: Structure, Function and Dynamics. MIT Press., Cambridge MA.
 
6
Bailey, N. T. J. 1975. The Mathematical Theory of Infectious Diseases and Its Applications, 2nd ed. Griffin, London, UK.
 
7
Baras, J. S. and Mehta, H. 2003. A probabilistic emergent routing algorithm for mobile ad hoc networks. In Proceedings of Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt'03).
 
8
 
9
 
10
 
11
 
12
Canright, G., Deutsch, A., and Urnes, T. 2005. Chemotaxis-inspired load balancing. In Proceedings of the European Conference on Complex Systems (ECCS'05).
13
 
14
Clausen, T., Jacquet, P., Laouiti, A., Muhlethaler, P., Qayyum, A., and Viennot, L. 2001. Optimized link state routing protocol. In Proceedings of IEEE INMIC.
 
15
 
16
de Castro, L. N. and Timmis, J. 2002. Artificial Immune Systems. Springer Verlag, Berlin, Germany.
17
 
18
Deutsch, A., Ganguly, N., Canright, G., Jelasity, M., and Engø-Monsen, K. 2003. Models for advanced services in AHN, P2P networks. www.cs.unibo.it/bison/deliverables/D08.pdf.
 
19
Di Caro, G. A. 2003. Analysis of simulation environments for mobile ad hoc networks. Tech. Rep. 24-03 (Dec). IDSIA, Lugano, Switzerland.
 
20
Di Caro, G. A. 2004. Ant colony optimization and its application to adaptive routing in telecommunication networks. Ph.D. thesis, Faculté des Sciences Appliquées, Université Libre de Bruxelles, Brussels, Belgium.
 
21
Di Caro, G. A. and Dorigo, M. 1998. AntNet: Distributed stigmergetic control for communications networks. J. Artificial Intelli. Res. 9, 317--365.
 
22
Di Caro, G. A., Ducatelle, F., and Gambardella, L. M. 2004. AntHocNet: An ant-based hybrid routing algorithm for mobile ad hoc networks. In Proceedings of Parallel Problem Solving from Nature (PPSN) VIII. Lecture Notes in Computer Science, vol. 3242. Springer-Verlag, 461--470.
 
23
Di Caro, G. A., Ducatelle, F., and Gambardella, L. M. 2005a. AntHocNet: An adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Trans. Telecomm. (Special Issue on Self-Organization in Mobile Networking) 16, 5 (Sept.-Oct.), 443--455.
 
24
Di Caro, G. A., Ducatelle, F., and Gambardella, L. M. 2005b. Swarm intelligence for routing in mobile ad hoc networks. In Proceedings of the IEEE Swarm Intelligence Symposium.
 
25
Di Caro, G. A., Ducatelle, F., and Gambardella, L. M. 2006. Studies of routing performance in a city-like testbed for mobile ad hoc networks. Tech. rep. 07-06 (March). IDSIA, Lugano, Switzerland.
 
26
 
27
 
28
 
29
 
30
Ducatelle, F., Di Caro, G. A., and Gambardella, L. M. 2005a. Using ant agents to combine reactive and proactive strategies for routing in mobile ad hoc networks. Int. J. Computat. Intell. Appl. (Special Issue on Nature-Inspired Approaches to Networks and Telecommunications) 5, 2 (June), 169--184.
 
31
 
32
Elsässer, R. and Monien, B. 2003. Diffusion load balancing in static and dynamic networks. In Proceedings of the International Workshop on Ambient Intelligence Computing. 49--62.
 
33
Fewell, J. H. 2003. Social insect networks. Science 301, 26 (Sept.), 1867--1869.
 
34
Gamma, E., Helm, R., Johnson, R., and Vlissides, J. 1995. Design Patterns. Addison-Wesley.
 
35
Ganguly, N., Brusch, L., and Deutsch, A. 2005. Design and analysis of a bio-inspired search algorithm for peer to peer networks. In Self-Star Properties in Complex Information Systems. Lecture Notes in Computer Science, vol. 3460. Springer-Verlag, Berlin, Germany.
 
36
Ganguly, N., Canright, G., and Deutsch, A. 2004a. Design of a robust search algorithm for p2p networks. In 11th International Conference on High Performance Computing.
 
37
Ganguly, N., Canright, G., and Deutsch, A. 2004b. Design of an efficient search algorithm for p2p networks using concepts from natural immune systems. In 8th International Conference on Parallel Problem Solving from Nature.
 
38
Ganguly, N. and Deutsch, A. 2004a. A cellular automata model for immune based search algorithm. In 6th International Conference on Cellular Automata for Research and Industry.
 
39
Ganguly, N. and Deutsch, A. 2004b. Developing efficient search algorithms for p2p networks using proliferation and mutation. In 3rd International Conference on Artificial Immune Systems.
 
40
Glazier, J. A. and Graner, F. 1993. Simulation of the differential adhesion driven rearrangement of biological cells. Phys. Rev. E 47, 3, 2128--2154.
 
41
Günes, M., Kähmer, M., and Bouazizi, I. 2003. Ant-routing-algorithm (ARA) for mobile multi-hop ad-hoc networks---new features and results. In Proceedings of the 2nd Mediterranean Workshop on Ad-Hoc Networks (Med-Hoc-Net'03). Mahdia, Tunisia.
 
42
 
43
Haas, Z. J. 1997. A new routing protocol for the reconfigurable wireless networks. In Proceedings of the IEEE International Conference on Universal Personal Communications.
 
44
 
45
 
46
Janeway, C. A., Travers, P., Walport, M., and Shlomchik, M. 2001. Immuno Biology: The Immune System in Health and Disease, 5th ed. Garland Publishing.
 
47
Jelasity, M. and Babaoglu, O. 2005. T-Man: Gossip-based overlay topology management. In 3rd International Workshop on Engineering Self-Organising Applications (ESOA'05).
 
48
 
49
Jelasity, M., Montresor, A., and Babaoglu, O. 2004. A modular paradigm for building self-organizing peer-to-peer applications. In Engineering Self-Organising Systems, G. Di Marzo Serugendo, A. Karageorgos, O. F. Rana, and F. Zambonelli, Eds. Lecture Notes in Artificial Intelligence, vol. 2977. Springer-Verlag, Berlin, Germany, 265--282.
50
 
51
Johnson, D. and Maltz, D. 1996. Mobile Computing. Kluwer (Chapter Dynamic Source Routing in Ad Hoc Wireless Networks). 153--181.
 
52
Keil, D. and Goldin, D. 2005. Adaptation and evolution in dynamic persistent environments. In Proceedings of the Workshop on the Foundations of Interactive Computation (FInCo'05). To appear in Electronic Notes in Theoretical Computer Science.
 
53
 
54
 
55
 
56
57
58
 
59
Mankin, R., Arbogast, R., Kendra, P., and Weaver, D. 1999. Active spaces of pheromone traps for Plodia Interpunctella in enclosed environments. Environmen. Entomol. 28, 4, 557--565.
 
60
 
61
Montemanni, R. and Gambardella, L. 2005b. Power-aware distributed protocol for a connectivity problem in wireless sensor networks. In Self-Star Properties in Complex Information Systems. Lecture Notes in Computer Science, vol. 3460.. Springer-Verlag, Berlin, Germany.
 
62
Montemanni, R. and Gambardella, L. 2005c. Swarm approach for a connectivity problem in wireless networks. In Proceedings of the IEEE Swarm Intelligence Symphosium. 265--272.
 
63
Montemanni, R., Gambardella, L., and Das, A. 2006. Models and algorithms for the MPSCP: An overview. In Handbook on Theoretical and Algorithmic Aspects of Sensor, Ad Hoc Wireless, and Peer-to-Peer Networks, J. Wu, Ed. Auerbach Publications, 133--146.
 
64
Murray, J. D. 1990. Mathematical Biology. Springer-Verlag, Berlin, Germany.
 
65
Ottino, J. M. 2004. Engineering complex systems. Nature 427, 399.
66
 
67
PeerSim. http://peersim.sourceforge.net/.
 
68
 
69
Păun, G. 2002. Computing with Membranes: an Introduction. Springer, Verlag, Berlin, Germany.
 
70
Păun, G., Rozenberg, G., and Salomaa, A. 2005. DNA Computing. Springer, Verlag, Berlin, Germany.
 
71
Risson, J. and Moors, T. 2004. Survey of research towards robust peer-to-peer networks: Search methods. Tech. rep. UNSW-EE-P2P-1-1, (Sept.). University of New South Wales, Sydney, Australia.
 
72
Royer, E. and Toh, C.-K. 1999. A review of current routing protocols for ad hoc mobile wireless networks. IEEE Person. Comm.
 
73
Scalable Network Technologies, Inc. 2005. QualNet Simulator, Version 3.8. Scalable Network Technologies, Inc., Culver City, CA, USA. http://www.scalable-networks.com.
74
 
75
 
76
Shen, C.-C., Jaikaeo, C., Srisathapornphat, C., Huang, Z., and Rajagopalan, S. 2004. Ad hoc networking with swarm intelligence. In Proceedings of 4th International Workshop on Ant Algorithms. Lecture Notes in Computer Science, Springer-Verlag, Berlin, Germany.
 
77
 
78
 
79
 
80
van Renesse, R. 2003. The importance of aggregation. Future Directions in Distributed Computing, A. Schiper, A. A. Shvartsman, H. Weatherspoon, and B. Y. Zhao, Eds. Lecture Notes in Computer Science, vol. 2584. Springer-Verlag, Berlin, Germany, 87--92.
81
 
82
Yuste, S. B. and Acedo, L. 2000. Number of distinct sites visited by N random walkers on a Euclidean lattice. Physical Review E 61, 6327--34.
 
83
Zipf, G. K. 1935. Psycho- Biology of Languages. Houghton-Mifflin, Boston, MA.

CITED BY  22

Collaborative Colleagues:
Ozalp Babaoglu: colleagues
Geoffrey Canright: colleagues
Andreas Deutsch: colleagues
Gianni A. Di Caro: colleagues
Frederick Ducatelle: colleagues
Luca M. Gambardella: colleagues
Niloy Ganguly: colleagues
Márk Jelasity: colleagues
Roberto Montemanni: colleagues
Alberto Montresor: colleagues
Tore Urnes: colleagues