Parallel implementations of individual-based models in biology: Bulletin- and non-bulletin-board approaches

BioSystems

Volumn 45, Issue 2, 1998, Pages 87-97

  Nugala, Vasudevarao ^a   Allan, Stephen J ^b   Haefner, James W ^c  

^a 4455 E Camelback St No 115A   (United States)

^b Utah State University ^*  (United States)

^c UTAH STATE UNIVERSITY   (United States)

Author keywords

Ants; Bulletin board; Computer networks; Granularity; Load balance; Parallel computer simulation; Particle based models; Tuple

Indexed keywords

ANT; ASSOCIATIVE MEMORY; BIOLOGICAL MODEL; COMPUTER MEMORY; COMPUTER NETWORK; COMPUTER SIMULATION; NONHUMAN; PRODUCTIVITY; REVIEW; TECHNIQUE;

EID: 0031911704     PISSN: 03032647     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0303-2647(97)00069-5     Document Type: Article

References (22)

1. Ahuja S., Carriero N., Gelernter D. Linda and friends. Computer. 19(8):1986;26-34.
2. Batschelet, E., 1981. Introduction to Mathematics for Life Scientists, Springer, Berlin.
3. Bossert W.H., Wilson E.O. The analysis of olfactory communication among animals. J. Theor. Biol. 5:1963;443-469.
4. Crist, T.O., 1990. Granivory in a shrub-steppe ecosystem: interactions of harvester ant foraging and native seeds. PhD Dissertation, Utah State University.
5. Drogoul, A., Ferber, J., 1993. From tom-thumb to the dockers: some experiments with foraging robots. In: Meyer, J.A., Roitblat, H.L., Wilson, S.W. (Eds.), From Animals to Animals 2, MIT Press, Cambridge, MA, pp. 451-459.
6. DeAngelis, D.L., Rose, K.A., 1992. Which individual-based approach is most appropriate for a given problem? In: DeAngelis, D.L., Gross, L.J. (Eds.), Individual-Based Models and Approaches in Ecology: Populations, Communities and Ecosystems, Chapman and Hall, New York, pp. 67-87.
7. Engelmore, R., Morgan,T., 1988. Blackboard Systems. Addison-Wesley, Reading, MA.
8. Fujimoto R.M. Parallel discrete event simulation. Commun. ACM. 33(10):1990;31-53.
9. Gordon D.M., Goodwin B.C., Trainor L.E.H. A parallel distributed model of the behavior of ant colonies. J. Theor. Biol. 156:1992;293-307.
10. Haefner, J.W., 1992. Parallel computers and individual-based models: an overview. In: DeAngelis, D.L., Gross, L.J. (Eds.), Individual-Based Models and Approaches in Ecology: Populations, Communities and Ecosystems. Chapman and Hall, New York, pp. 126-164.
11. Haefner, J.W., 1996. Modeling Biological Systems: Principles and Applications, Chapman and Hall, New York.
12. Haefner J.W., Crist T.O. Spatial model of movement and foraging in harvester ants (Pogonomyrmex occidentalis) (I): the roles of memory and communication. J. Theor. Biol. 166:1994;299-313.
13. Huston M., DeAngelis D., Post W. New computer models unify ecological theory. Bioscience. 38(10):1988;682-691.
14. Hillis W.D. Data parallel algorithms. Commun. ACM. 29(12):1986;1170-1183.
15. Holldobler B., Wilson E.O. Recruitment trails in the harvester ant Pogonomyrmex badius. Psyche. 77:1970;385-399.
16. Langton, C.G., 1989 (Ed.), Artificial Life. Addison-Wesley, Reading, MA.
17. Resnick, M., 1994. Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds. MIT Press, Cambridge, MA.
18. Smith M. Using massively-parallel supercomputers to model stochastic spatial predator-prey systems. Ecol. Model. 58:1991;347-367.
19. Stevens, R.W., 1990. Unix Network Programming. Prentice Hall, Reading, MA.
20. Smith, M., Wilson, G., 1991. Dynamic load-balancing on a one-dimensional mesh. Technical report, Edinburgh Parallel Computing Center, Edinburgh, UK.
21. Stumm M., Zhou S. Algorithms implementing distributed shared memory. Computer. 23(5):1990;54-64.
22. Travers, M., 1989. Animal construction kits. In: C. Langton (Ed.), Artificial Life, Addison-Wesley, Redwood City, CA, pp. 421-442.