Name
Abstract | ||
|---|---|---|
In previous works we have proposed to use of self- organization based on emergent design as a model for the programming of very large aggregates of heterogeneous computing resources. In our approach, a large scale com- putation is divided into small independent units of compu- tation, each provided with its own uniform, autonomousbe- havior; only local information is used by each unit of com- putation to take all the decisions needed to carry out the computation. One of the challenges of this novel approach is to provide some theoretical foundation that can assist in the rational design of new systems. In this paper is to demonstrate the use of combinato- rial techniques for obtaining quantitativeanalytical models of the organization pattern emerging from a specific type of self-organizing computation. Specifically, in a previous experiment we have demonstrated a computation in which mobile agents organize themselves around an overlay tree, that constantly restructures itself in response to changing node availability and performance levels. In this paper we derive an analytical expression describing how nodes dis- tribute themselves over the tree based on their performance, in a simplified version of the above problem. This result represents an instance of a theoretical tool that can be used to predict global patterns emerging as a result of a self- organizing design, and to establish a direct connection be- tween global features and local behavior parameters. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IPDPS.2007.370674 | IPDPS |
Keywords | Field | DocType |
grid computing,mobile agents,trees (mathematics),combinatorial model,mobile agent,quantitative analytical model,self-organizing network | Grid computing,Emergent Design,Computer science,Mobile agent,Parallel computing,Symmetric multiprocessor system,Theoretical computer science,Self-organizing network,Overlay,Combinatorial model,Distributed computing,Computation | Conference |
Citations | PageRank | References |
2 | 0.41 | 22 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuri Dimitrov | 1 | 2 | 0.75 |
| Carlo Giovine | 2 | 2 | 0.41 |
| Gennaro Mango | 3 | 2 | 0.41 |
| Mario Lauria | 4 | 628 | 95.12 |