A survey on bio-inspired networking

Computer Networks

Volumn 54, Issue 6, 2010, Pages 881-900

  Dressler, Falko ^a   Akan, Ozgur B ^b  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Activator inhibitor systems; Bio inspired networking; Molecular communication; Nanonetworks; Swarm intelligence

Indexed keywords

ACTIVATOR-INHIBITOR SYSTEMS; BIO-INSPIRED NETWORKING; MOLECULAR COMMUNICATION; NANO-NETWORKS; SWARM INTELLIGENCE;

BIOLOGICAL SYSTEMS; CELLULAR AUTOMATA; DESIGN; INFORMATION SERVICES; INTERNET; INTERNET PROTOCOLS; OPTICAL COMMUNICATION; RESEARCH; SURVEYS;

COMMUNICATION;

EID: 77949577760     PISSN: 13891286     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.comnet.2009.10.024     Document Type: Article

References (105)

1. Cirac J.I., van Enk S.J., Zoller P., Kimble H.J., and Mabuchi H. Quantum communication in a quantum network. Physica Scripta T76 (1998) 223-232
2. Akyildiz I.F., Akan O.B., Chen C., Fang J., and Su W. The state of the art in interplanetary Internet. IEEE Communications Magazine 42 7 (2004) 108-118
3. Dobson S., Denazis S., Fernandez A., Gaiti D., Gelenbe E., Massacci F., Nixon P., Saffre F., Schmidt N., and Zambonelli F. A survey of autonomic communications. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 1 2 (2006) 223-259
4. Ashok R.L., and Agrawal D.P. Next-generation wearable networks. IEEE Computer 36 11 (2003) 31-39. http://doi.ieeecomputersociety.org/10.1109/MC.2003.1244532
5. B. Atakan, O.B. Akan, An information theoretical approach for molecular communication, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007.
6. Akyildiz I.F., Pompili D., and Melodia T. Underwater acoustic sensor networks: research challenges. Elsevier Ad Hoc Networks 3 3 (2005) 257-279
7. Akyildiz I.F., and Kasimoglu I.H. Wireless sensor and actor networks: research challenges. Elsevier Ad Hoc Networks 2 (2004) 351-367
8. Dressler F. A study of self-organization mechanisms in ad hoc and sensor networks. Elsevier Computer Communications 31 13 (2008) 3018-3029. http://dx.doi.org/10.1016/j.comcom.2008.02.001
9. Akyildiz I.F., Lee W.-Y., Vuran M.C., and Mohanty S. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Elsevier Computer Networks 50 13 (2006) 2127-2159. http://dx.doi.org/10.1016/j.comnet.2006.05.001
10. Dressler F. Self-Organization in Sensor and Actor Networks (2007), John Wiley & Sons. http://doi.wiley.com/10.1002/9780470724460
11. Timmis J., Neal M., and Hunt J. An artificial immune system for data analysis. Biosystems 55 (2000) 143-150
12. Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraula G., and Bonabeau E. Self-Organization in Biological Systems (2003), Princeton University Press
13. Bonabeau E., Dorigo M., and Theraulaz G. Swarm Intelligence: From Natural to Artificial Systems (1999), Oxford University Press
14. Welbourne E., Battle L., Cole G., Gould K., Rector K., Raymer S., Balazinska M., and Borriello G. Building the internet of things using RFID. IEEE Internet Computing 33 3 (2009) 48-55 10.1109/MIC.2009.52
15. Akyildiz I.F., Su W., Sankarasubramaniam Y., and Cayirci E. Wireless sensor networks: a survey. Elsevier Computer Networks 38 (2002) 393-422
16. Akyildiz I.F., Wang X., and Wang W. Wireless mesh networks: a survey. Elsevier Computer Networks 47 4 (2005) 445-487
17. Akan O.B., and Akyildiz I.F. Event-to-sink reliable transport in wireless sensor networks. IEEE/ACM Transactions on Networking (TON) 13 5 (2005) 1003-1016
18. B. Atakan, O.B. Akan, Immune system based distributed node and rate selection in wireless sensor networks, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
19. Dorigo M., Maniezzo V., and Colorni A. The ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics 26 1 (1996) 1-13
20. Di Caro G., Ducatelle F., and Gambardella L.M. AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications, Special Issue on Self-organization in Mobile Networking 16 (2005) 443-455
21. Vogels W., van Renesse R., and Briman K. The power of epidemics: robust communication for large-scale distributed systems. ACM SIGCOMM Computer Communication Review 33 1 (2003) 131-135
22. T. Tsuchiya, T. Kikuno, An adaptive mechanism for epidemic communication, in: 1st International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT2004), LNCS 3141, Springer, Lausanne, Switzerland, 2004.
23. I. Carreras, D. Miorandi, G.S. Canright, K. Engo-Monsen, Understanding the spread of epidemics in highly mobile networks, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
24. Chlamtac I., Conti M., and Liu J.J. Mobile ad hoc networking: imperatives and challenges. Elsevier Ad Hoc Networks 1 1 (2003) 13-64. http://dx.doi.org/10.1016/S1570-8705(03)00013-1
25. Hofmeyr S.A., and Forrest S. Architecture for an artificial immune system. Evolutionary Computation 8 4 (2000) 443-473
26. T.C. Henderson, R. Venkataraman, G. Choikim, G. Choikim, Reaction-diffusion patterns in smart sensor networks, in: IEEE International Conference on Robotics and Automation (ICRA 2004), IEEE, New Orleans, LA, 2004, pp. 654-658.
27. A. Yoshida, K. Aoki, S. Araki, Cooperative control based on reaction-diffusion equation for surveillance system, in: 9th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2005), LNCS 3684, Melbourne, Australia, 2005.
28. Atakan B., and Akan O.B. Immune system-based energy efficient and reliable communication in wireless sensor networks. In: Dressler F., and Carreras I. (Eds). Advances in Biologically Inspired Information Systems - Models Methods and Tools. Studies in Computational Intelligence (SCI) vol. 69 (2007), Springer, Berlin, Heidelberg, New York 187-208
29. Metcalfe B. The next-generation Internet. IEEE Internet Computing 4 1 (2000) 58-59
30. Dorigo M., Di Caro G., and Gambardella L.M. Ant algorithms for discrete optimization. Artificial Life 5 2 (1999) 137-172
31. B. Atakan, O.B. Akan, Biologically-inspired Spectrum Sharing in cognitive radio networks, in: IEEE Wireless Communications and Networking Conference (IEEE WCNC 2007), Hong Kong, China, 2007.
32. Richmond C.A. Fireflies flashing in unison. Science 71 1847 (1930) 537-538
33. F. Dressler, Self-organized event detection in sensor networks using bio-inspired promoters and inhibitors, in: 3rd ACM/ICST International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2008), ACM, Hyogo, Japan, 2008, .
34. 22.
35. Boukerche A., Oliveira H., Nakamura E., and Loureiro A. Vehicular ad hoc networks: a new challenge for localization-based systems. Elsevier Computer Communications 31 12 (2008) 2838-2849. http://dx.doi.org/10.1016/j.comcom.2007.12.004
36. M. Neal, J. Timmis, Once more unto the breach: towards artificial homeostasis? in: L.N. De Castro, F.J. Von Zuben (Eds.), Recent Developments in Biologically Inspired Computing, Idea Group, 2005, pp. 340-365.
37. T.H. Labella, M. Dorigo, J.-L. Deneubourg, Self-organised task allocation in a group of robots, in: 7th International Symposium on Distributed Autonomous Robotic Systems (DARS04), Toulouse, France, 2004.
38. 11.
39. Leibnitz K., Wakamiya N., and Murata M. Resilient multi-path routing based on a biological attractor selection scheme. 2nd International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT 2006) LNCS 3853 (2006), Springer, Osaka, Japan 48-63
40. Leibnitz K., Wakamiya N., and Murata M. Biologically-inspired self-adaptive multi-path routing in overlay networks. Communications of the ACM, Special Issue on Self-Managed Systems and Services 49 3 (2006) 63-67
41. Akyildiz I.F., Brunetti F., and Blázquez C. Nanonetworks: a new communication paradigm. Elsevier Computer Networks 52 (2008) 2260-2279
42. Alberts B., Bray D., Lewis J., Raff M., Roberts K., and Watson J.D. Molecular Biology of the Cell. third ed. (1994), Garland Publishing, Inc.
43. T. Nakano, T. Suda, M. Moore, R. Egashira, A. Enomoto, K. Arima, Molecular communication for nanomachines using intercellular calcium signaling, in: 5th IEEE Conference on Nanotechnology (IEEE NANO 2005), Nagoya, Japan, 2005, pp. 478-481.
44. Eigen M., and Schuster P. The Hypercycle: A Principle of Natural Self Organization (1979), Springer
45. Ashby W.R. Principles of the self-organizing system. In: von Foerster H., and Zopf G.W. (Eds). Principles of Self-Organization (1962), Pergamon Press 255-278
46. M. Wang, T. Suda, The bio-networking architecture: a biologically inspired approach to the design of scalable, adaptive, and survivable/available network applications, in: 1st IEEE Symposium on Applications and the Internet (SAINT), San Diego, CA, 2001.
47. J. Suzuki, T. Suda, Adaptive behavior selection of autonomous objects in the bio-networking architecture, in: 1st Annual Symposium on Autonomous Intelligent Networks and Systems, Los Angeles, CA, 2002.
48. Lee C., Wada H., and Suzuki J. Towards a biologically-inspired architecture for self-regulatory and evolvable network applications. In: Dressler F., and Carreras I. (Eds). Advances in Biologically Inspired Information Systems - Models Methods and Tools. Studies in Computational Intelligence (SCI) vol. 69 (2007), Springer, Berlin, Heidelberg, New York 21-46
49. Webb B. What does robotics offer animal behaviour?. Animal Behavior 60 5 (2000) 545-558
50. Ma Z.S., and Krings A.W. Insect sensory systems inspired computing and communications. Elsevier Ad Hoc Networks 7 4 (2009) 742-755. http://dx.doi.org/10.1016/j.adhoc.2008.03.003
51. Farooq M. Bee-Inspired Protocol Engineering: From Nature to Networks, Natural Computing (2009), Springer
52. U. Lee, E. Magistretti, M. Gerla, P. Bellavista, P. Lió, K.-W. Lee, Bio-inspired Multi-Agent Data Harvesting in a Proactive Urban Monitoring Environment, Elsevier Ad Hoc Networks, 10.1016/j.adhoc.2008.03.009, .
53. Di Caro G., and Dorigo M. AntNet: distributed stigmergetic control for communication networks. Journal of Artificial Intelligence Research 9 (1998) 317-365
54. J. Wang, E. Osagie, P. Thulasiraman, R.K. Thulasiram, HOPNET: A Hybrid ant colony OPtimization routing algorithm for Mobile ad hoc NETwork, Elsevier Ad Hoc Networks, .
55. Michlmayr E. Self-organization for search in peer-to-peer networks. In: Dressler F., and Carreras I. (Eds). Advances in Biologically Inspired Information Systems - Models, Methods, and Tools. Studies in Computational Intelligence (SCI) vol. 69 (2007), Springer, Berlin, Heidelberg, New York 247-266
56. A. Forestiero, C. Mastroianni, G. Spezzano, Antares: an ant-inspired P2P information system for a self-structured grid, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007.
57. Mirollo R.E., and Strogatz S.H. Synchronization of pulse-coupled biological oscillators. SIAM Journal on Applied Mathematics 50 6 (1990) 1645-1662
58. A. Tyrrell, G. Auer, C. Bettstetter, Fireflies as role models for sychronization in ad hoc networks, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
59. Tyrrell A., Auer G., and Bettstetter C. Biologically inspired synchronization for wireless networks. In: Dressler F., and Carreras I. (Eds). Advances in Biologically Inspired Information Systems - Models, Methods, and Tools. Studies in Computational Intelligence (SCI) vol. 69 (2007), Springer, Berlin Heidelberg, New York 47-62
60. Tyrrell A., and Auer G. Imposing a reference timing onto firefly synchronization in wireless networks. 65th IEEE Vehicular Technology Conference (VTC2007-Spring) (2007), IEEE, Dublin, Ireland 222-226
61. Wakamiya N., and Murata M. Synchronization-based data gathering scheme for sensor networks. IEICE Transactions on Communications, Special Issue on Ubiquitous Networks E88-B 3 (2005) 873-881
62. O. Babaoglu, T. Binci, M. Jelasity, A. Montresor, Firefly-inspired heartbeat synchronization in overlay networks, in: 1st IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), IEEE, Boston, MA, 2007, pp. 77-86, .
63. Turing A.M. The chemical basis for morphogenesis. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 237 641 (1952) 37-72
64. Hyodo K., Wakamiya N., Nakaguchi E., Murata M., Kubo Y., and Yanagihara K. Experiments and Considerations on Reaction-Diffusion based Pattern Generation in a Wireless Sensor Network. IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2007) (2007), IEEE, Helsinki, Finland 1-6
65. G. Neglia, G. Reina, Evaluating activator-inhibitor mechanisms for sensors coordination, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007.
66. de Castro L.N., and Timmis J. Artificial Immune Systems: A New Computational Intelligence Approach (2002), Springer
67. Kephart J.O. A biologically inspired immune system for computers. 4th International Workshop on Synthesis and Simulation of Living Systems (1994), MIT Press, Cambridge, MA 130-139
68. S.A. Hofmeyr, An Immunological Model of Distributed Detection and Its Application to Computer Security, Ph.D. Thesis, University of New Mexico, 1999.
69. Stepney S., Smith R.E., Timmis J., Tyrrell A.M., Neal M.J., and Hone A.N.W. Conceptual frameworks for artificial immune systems. International Journal of Unconventional Computing 1 3 (2005) 315-338
70. Le Boudec J.-Y., and Sarafijanovic S. An artificial immune system approach to misbehavior detection in mobile ad-hoc networks. 1st International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT2004) LNCS 3141 (2004), Springer, Lausanne, Switzerland 96-111
71. Zou C.C., Gong W., Towsley D., and Gao L. The monitoring and early detection of internet worms. IEEE/ACM Transactions on Networking (TON) 13 5 (2005) 961-974. http://dx.doi.org/10.1109/TNET.2005.857113
72. Vojnovic M., and Ganesh A.J. On the race of worms, alerts, and patches. IEEE/ACM Transactions on Networking (TON) 16 5 (2008) 1066-1079. http://dx.doi.org/10.1109/TNET.2007.909678
73. Kleinberg J. Computing: the wireless epidemic. Nature 449 (2007) 287-288 10.1038/449287a
74. A. Khelil, C. Becker, J. Tian, K. Rothermel, An epidemic model for information diffusion in MANETs, in: 5th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (ACM MSWiM 2002), ACM, Atlanta, GA, 2002, pp. 54-60.
75. R.C. Shah, S. Wiethölter, A. Wolisz, When does opportunistic routing make sense, in: 1st international workshop on sensor networks and systems for pervasive computing (PerSeNS 2005), Kauai Island, HI, 2005.
76. Hayashi H., Hara T., and Nishio S. On updated data dissemination exploiting an epidemic model in ad hoc networks. 2nd International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT 2006) LNCS 3853 (2006), Springer, Osaka, Japan 306-321
77. E. Ahi, M. Caglar, Ö. Özkasap, Stepwise probabilistic buffering for epidemic information dissemination, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
78. Zhang X., Neglia G., Kurose J., and Towsley D. Performance modeling of epidemic routing. Elsevier Computer Networks 51 10 (2007) 2867-2891. http://dx.doi.org/10.1016/j.comnet.2006.11.028
79. Okuyama T., Tsuchiya T., and Kikuno T. Improving the robustness of epidemic communication in scale-free networks. 2nd International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT 2006) LNCS 3853 (2006), Springer, Osaka, Japan 294-305
80. V. Pappas, D. Verma, B.-J. Ko, A. Swami, A Circulatory System Approach for Wireless Sensor Networks, Elsevier Ad Hoc Networks, 10.1016/j.adhoc.2008.04.009, .
81. Kesidis G., Hamadeh I., Jin Y., Jiwasurat S., and Vojnovic M. A model of the spread of randomly scanning internet worms that saturate access links. ACM Transactions on Modeling and Computer Simulation (TOMACS) 18 2 (2008) 1-14. http://doi.acm.org/10.1145/1346325.1346327
82. Weng G., Bhalla U.S., and Iyengar R. Complexity in biological signaling systems. Science 284 5411 (1999) 92-96
83. Pawson T. Protein modules and signalling networks. Nature 373 6515 (1995) 573-580
84. Krüger B., and Dressler F. Molecular processes as a basis for autonomous networking. IPSI Transactions on Advances Research: Issues in Computer Science and Engineering 1 1 (2005) 43-50
85. Milo R., Shen-Orr S., Itzkovitz S., Kashtan N., Chklovskii D., and Alon U. Network motifs: simple building blocks of complex networks. Nature 298 (2002) 824-827
86. J. Decraene, G. Mitchell, B. McMullin, Evolving artificial cell signaling networks using molecular classifier systems, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
87. F. Dressler, I. Dietrich, R. German, B. Krüger, Efficient operation in sensor and actor networks inspired by cellular signaling cascades, in: 1st ACM/ICST International Conference on Autonomic Computing and Communication Systems (Autonomics 2007), ACM, Rome, Italy, 2007, .
88. Dressler F., Dietrich I., German R., and Krüger B. A rule-based system for programming self-organized sensor and actor networks. Elsevier Computer Networks 53 10 (2009) 1737-1750. http://dx.doi.org/10.1016/j.comnet.2008.09.007
89. C. Tschudin, Fraglets - a metabolistic execution model for communication protocols, in: 2nd Symposium on Autonomous Intelligent Networks and Systems (AINS), Menlo Park, CA, 2003.
90. Tschudin C., and Yamamoto L. A metabolic approach to protocol resilience. 1st IFIP International Workshop on Autonomic Communication (WAC 2004) LNCS 3457 (2004), Springer, Berlin, Germany 191-206
91. L. Yamamoto, D. Schreckling, T. Meyer, Self-replicating and self-modifying programs in fraglets, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007.
92. M. Petrocchi, Crypto-fraglets: networking, biology and security, in: 1st IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2006), IEEE, Cavalese, Italy, 2006.
93. 13
94. Leibnitz K., Wakamiya N., and Murata M. Biologically inspired networking. In: Mahmoud Q. (Ed). Cognitive Networks: Towards Self-Aware Networks (2007), John Wiley & Sons 1-21
95. F. Dressler, I. Carreras (Eds.), Advances in Biologically Inspired Information Systems - Models, Methods, and Tools, Studies in Computational Intelligence (SCI), vol. 69, Springer, 2007, .
96. Dietrich I., and Dressler F. On the lifetime of wireless sensor networks. ACM Transactions on Sensor Networks (TOSN) 5 1 (2009) 1-39. http://doi.acm.org/10.1145/1464420.1464425
97. Bustamante C., Chelma Y., Forde N., and Izhaky D. Mechanical processes in biochemistry. Annual Review of Biochemistry 73 (2004) 705-748
98. T. Suda, M. Moore, T. Nakano, R. Egashira, A. Enomoto, Exploratory research on molecular communication between nanomachines, in: Conference on Genetic and Evolutionary Computation (GECCO 2005), ACM, 2005.
99. S. Hiyama, Y. Moritani, T. Suda, R. Egashira, A. Enomoto, M. Moore, T. Nakano, Molecular communication, in: NSTI Nanotech 2005, NSTI, 2005.
100. M. Moore, A. Enomoto, T. Nakano, R. Egashira, T. Suda, A. Kayasuga, H. Kojima, H. Sakakibara, K. Oiwa, A design of a molecular communication system for nanomachines using molecular motors, in: 4th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06), IEEE, Washington, DC, 2006, p. 554, .
101. B. Atakan, O.B. Akan, On channel capacity and error compensation in molecular communication, Springer Transactions on Computational Systems Biology (TCSB), vol. LNBI 5410, December 2008, pp. 59-80.
102. B. Atakan, O.B. Akan, On molecular multiple-access, broadcast, and relay channel in nanonetworks, in: 3rd ACM/ICST International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2008), ACM, Hyogo, Japan, 2008.
103. Y. Moritani, S. Hiyama, T. Suda, R. Egashira, A. Enomoto, M. Moore, T. Nakano, Molecular communications between nanomachines, in: 24th IEEE Conference on Computer Communications (IEEE INFOCOM 2005), Miami, FL, 2005.
104. Y. Moritani, S. Hiyama, S. Nomura, K. Akiyoshi, T. Suda, A communication interface using vesicles embedded with channel forming proteins in molecular communication, in: 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information and Computing Systems (IEEE/ACM BIONETICS 2007), Budapest, Hungary, 2007, pp. 147-149.
105. Y. Moritani, S.X.S. Hiyama, T. Suda, Molecular communication for health care applications, in: 4th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06), IEEE, Washington, DC, 2006, p. 549, .