Insect sensory systems inspired computing and communications

Ad Hoc Networks

Volumn 7, Issue 4, 2009, Pages 742-755

 

^a Sam)   (United States)

Author keywords

Grid computing; Insect chemosensory networks; Insect sensory systems; Insect inspired communications; Insect inspired computing; Micro aerial vehicle (MAV); Pervasive computing; Robots; Wireless sensory networks

Indexed keywords

ARTS COMPUTING; BIOCHEMISTRY; BIOMASS; COMMUNICATION; COMMUNICATION SYSTEMS; FAULT TOLERANT COMPUTER SYSTEMS; GRID COMPUTING; INTEGRATED CIRCUITS; METROPOLITAN AREA NETWORKS; RENEWABLE ENERGY RESOURCES; ROBOTICS; SENSORS; UBIQUITOUS COMPUTING;

INSECT CHEMOSENSORY NETWORKS; INSECT SENSORY SYSTEMS; INSECT-INSPIRED COMMUNICATIONS; INSECT-INSPIRED COMPUTING; MICRO-AERIAL VEHICLE (MAV); PERVASIVE COMPUTING; WIRELESS SENSORY NETWORKS;

WIRELESS SENSOR NETWORKS;

EID: 58149203592     PISSN: 15708705     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.adhoc.2008.03.003     Document Type: Article

References (71)

1. In: Amos M. (Ed). Cellular Computing (2004), Oxford University Press 217
2. Alpern S., and Gal S. The Theory of Search Games and Rendezvous (2003), Kluwer Academic Publisher p. 317
3. Babaoglu O., Canright G., et al. Design patterns from biology for distributed computing. ACM Trans. Auto. Adapt. Syst. 1 1 (2006) 26-66
4. Bernays A.E. Neural limitations in phytophagous insects: implications diet breadth and evolution of host affiliation. Annu. Rev. Entomol. 46 (2001) 703-727
5. Blanchard M., Rind F.C., and Vershure P.F.M. Collision avoidance using a model of the locust LGMD neuron. J. Robot. Auto. Syst. 30 (2000) 16-38
6. Boonma P., and Suzuki J. BiSNET: a biologically-inspired middleware architecture for self-managing wireless sensor networks. Comp. Networks 51 (2007) 4599-4616
7. Borghoff U.M., and Schlichter J.H. Computer-supported Cooperative Work: Introduction to Distributed Applications vol. 529 (2000), Springer pp. 200-203
8. Bonabeau E., Dorigo M., and Theraulaz G. SwarmIntelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity Proceedings) (1999), Oxford University Press 320pp
9. Casas J., and Magal C. Mutual eavesdropping through vibration in a host-parasitoid interaction: from plant biomechanics to behavioral ecology. In: Drosopoulos S., and Claridge M.F. (Eds). Insect Sounds and Communication: Physiology, Behavior, Ecology and Evolution (2006), Taylor & Francis 263-274
10. Chahl J., Thakoor S., Bouffant N.L., Stange G., and Srinivasan M.V. Bioinspired engineering of exploration systems: a horizon sensor/attitude reference system based on the dragonfly ocelli for mars exploration applications. J. Robot. Syst. 20 1 (2003) 35-42
11. Christensen T.A., and White J. Representation of Olfactory Information in the Brain. Neurobiology of Taste and Smell (2000), Wiley 201-232
12. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 435
13. Claridge M. Insect sounds and communication - an introduction. In: Drosopoulos S., and Claridge M.F. (Eds). Insect Sounds and Communication: Physiology, Behavior, Ecology and Evolution (2006), Taylor & Francis 3-10
14. In: Detrain C., Deneubourg J.L., and Pasteels J.M. (Eds). Information Processing in Social Insects (1999), Birkhauser Verlag 415
15. M.H. Dickinson, Wing rotation and the aerodynamic basis of insect flight science, 18 June, 1999, p. 1954.
16. Djemai I., Meyhöfer R., and Casas J. Geometrical games between a host and a parasitoid. Am. Nat. 156 3 (2000) 257-265
17. I. Djemai, J. Casas, C. Magal, Matching host reactions to parasitoid wasp vibrations, in: Proceedings of the Royal Society of London Series B: Biological Sciences, vol. 268, No. 1484, December 7, 2001, pp. 2403-2408.
18. Dogaru R. Universality and Emergent Computation in Cellular Neural Networks (2003), World Scientific Publishing
19. Dorigo M., and Stützle T. Ant Colony Optimization (2004), The MIT Press
20. Dressler F., and Carreras I. Advances in Biologically Inspired Information Systems: Models, Methods, and Tools (2007), Springer 302pp
21. In: Drosopoulos S., and Claridge M.F. (Eds). Insect Sounds and Communication: Physiology, Behavior, Ecology and Evolution (2006), Taylor & Francis 532
22. Egelhaaf M., Grewe J., et al. Novel approaches to visual information processing in insects: case studies on neural computations in the blowfly. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 185-212
23. Endler J.A. Some general comments on the evolution and design of animal communication systems. Phil. Trans. Roy. Soc. Lond. B 340 (1993) 215-225
24. Fittkau E.J., and Klinge H. On biomass and trophic structure of the central American rain forest ecosystem. Biotropica 5 1 (1973) 2-14
25. Franceschini N., Pichon J.M., and Blanes C. From insect vision to robot vision. Phil. Trans. Roy. Soc. Lond. B 337 (1992) 283-294
26. Greenfield M.D., and Karandinos M.G. Resource partitioning of the sex communication channel in clearwing moths (Lepidoptera: Sesiidae) of Wisconsin. Ecol. Monog. 49 4 (1979) 403-426
27. Gullan P.J., and Cranston P.S. The Insects: An Outline of Entomology. third ed. (2005), Blackwell Publishing
28. Hallem E.A., Dahanukar A., and Carlson J.R. Insect Odors and Taste Receptors. Ann. Rev. Entomol. 51 (2006) 113-135
29. R.R. Harrison, An analog VLSI motion sensor based on the fly visual system, Ph.D. Dissertation, California Institute of Technology, Pasadena, CA, 2000.
30. Herz A.V.M., Benda J., et al. Auditory processing of acoustic communication signals: sensory biophysics, neural coding, and discrimination of con-specific songs. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 130-156
31. Homberg U. Multisensory processing in the insect brain. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 3-26
32. Huotari M.J. Biosensing by insect olfactory receptor neurons. Sensor. Actuator. B 71 (2000) 212-222
33. M.J. Huotari, Odor sensing by insect olfactory receptor neurons: measurements of odors based on action potential analysis, Ph.D. Dissertation, University of Oulu, Finland, 2004, 76pp.
34. Ignell R., and Hansson B. Insect olfactory neuroethology - an electrophysiological perspective. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 320-347
35. S. Jafar, A.W. Krings, T. Gautier, Flexible rollback recovery in dynamic heterogeneous grid computing, IEEE Trans. Depend. Secure Comput., in press.
36. Klowden M.J. Physiological Systems in Insects (2002), Academic Press
37. Klowden M.J. Physiological Systems in Insects. second ed. (2007), Academic Press
38. Larsson M.C., and Svensson G.P. Methods in insect sensory ecology. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 28-58
39. Labella T.H., Dorigo M., and Deneubourg J. Division of labor in a group of robots inspired by ants' foraging behavior. ACM Trans. Autonom. Adapt. Syst. 1 1 (2006) 4-25
40. Liu S.C. A neuromorphic VLSI model of global motion processing in the fly. IEEE Trans. Circ. Syst. II 47 (2000) 1458-1467
41. Liu S.C., and Usseglio-Viretta A. Fly-like visuomotor response of a robot using VLSI motion-sensitive chips. Biol. Cybern. 85 (2001) 449-457
42. N. Lobontui, M. Goldfarb, E. Garcia, Design and analysis of an elastodynamic inch-worm robotic insect, in: IEEE Conference on Robotics and Automation, May 1999, pp. 2120-2125.
43. Lodding K.N. Hitchhiker's guide to biomorphic software. Queue (2004) 68-75
44. London M., and Häusser M. Dendritic computation. Annu. Rev. Neurosci. 28 (2005) 503-532
45. Lubbock J. On the Senses, Instincts, and Intelligence of Animals, with Special Reference to Insects. The International Scientific Series (1902), D. Appleton and Company, New York 272pp
46. Z.S. Ma, A.W. Krings, Spatial distribution patterns, power law, and the agent-based directed diffusion sensor networks, in: Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), March 17-21, Hong Kong, 2008.
47. Machens C.K. Adaptive sampling by information maximization. Phys. Rev. Lett. 88 22 (2002) 228104
48. Marder E. From biophysics to models of network function. Annu. Rev. Neurosci. 21 (1998) 25-45
49. Michelson R. The Entomopter. Neurotechnology for Biomimetic Robots (2002), The MIT Press 481-509
50. M. Motamed, J. Yan, A review of biological, biomimetic and miniature force sensing for micro-flight, in: International Conference on Intelligent Robots and Systems, 2005 IEEE IROS, 2-6 August 2005, pp. 3939-3946.
51. National Research Council of National Academies. In: Wooley J.C., and Lin H.S. (Eds). Catalyzing Inquiry at the Interface of Computing and Biology (2005), The National Academy Press
52. Newland P.L. Taste processing in the insect nervous system. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 289-318
53. Perry J.J., Dahanukar A., and Carlson J.R. Analysis of taste receptors in Drosophila. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 239-264
54. Oregon State University (2008, January 4). Insect attack may have finished off dinosaurs. ScienceDaily. (retrieved March 18, 2008).
55. Peters T.M. Insects and Human Society (1988), Van Nostrand Reinhold Company
56. Prodan R., and Fahringer T. Grid Computing (2007), Springer-Verlag
57. Rind F.C. Bioinspired sensors: from insect eyes to robot vision. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 213-235
58. Pawlowski V.M., Christensen T.A., et al. In: Christensen T.A. (Ed). Methods in Insect Sensory Neuroscience (2005), CRC Press 394-415
59. Poethke H., and Kaiser H. A Simulation approach to evolutionary game theory: the evolution of time-sharing behavior in a dragonfly mating system. Behav. Ecol. Sociobiol. 18 (1985) 155-163
60. Pornsin-sirirak T.N., Taia Y.C., Nassefb H., and Hob C.M. Titanium-alloy MEMS wing technology for a micro-aerial vehicle application. Sensor. Actuator. A 89 (2001) 95-103
61. Rich R.L., and Myszka D.G. Survey of the year 2004 commercial optical biosensor literature. J. Mol. Recognit. 18 (2005) 431-478
62. Richards O.W., and Davies R.G. Imms' Outlines of Entomology (1978), Chapman & Hall
63. Selvakennedy S., Sinnappan S., and Shang Y. A biologically-inspired clustering protocol for wireless sensor networks. Comp. Commun. 30 (2007) 2786-2801
64. Smith C.M. Biology of Sensory Systems (2000), Wiley 445pp
65. Srinivasan M.V., Chahl J.S., Weber K., Venkatesh S., Nagle M.G., and Zhang S.W. Robot navigation inspired by principles of insect vision (review). Robot. Autonom. Syst. 26 (1999) 203-216
66. Srinivasan M.V., Zhang S.W., et al. Landing strategies in honey bees and possible applications to autonomous airborne vehicles. Biol. Bull. 200 (2001) 216-221
67. E. Steltz, S. Avadhanula, R.J. Wood, R.S. Fearing, Characterization of the micromechanical flying insect by optical position sensing, in: IEEE International Conference on Robotics and Automation, Barcelona, April 2005.
68. Thakoor S., Cabrol N., et al. Review: the benefits and applications of bioinspired flight capabilities. J. Robot. Syst. 20 12 (2003) 687-706
69. Vogels T.P., Rajan K., and Abbott L.F. Neural network dynamics. Annu. Rev. Neurosci. 28 (2005) 357-376
70. Wyatt T.D. Pheromones and Animal Behavior: Communication by Smell and Taste (2003), Cambridge University Press
71. E.O. Wilson, Excellence in Ecology: Success and Dominance in Ecosystems, the Case of the Social Insects, Ecology Institute of Germany, 1990, p. 104.