Name
Abstract | ||
|---|---|---|
Pervasive computing calls for developing distributed infrastructures featuring large-scale distribution, opennes, context-awareness, self-organisation and self-adaptation. There, it is quite natural to see services (software functionality, data, knowledge, signals) as spatial concepts: they are naturally diffused in the network, and in each location they are sensitive to the context and compete with each other—as such, they can be active in one or multiple regions (niches) of the network. To support and engineer this scenario, we propose a natureinspired coordination model of chemical-inspired tuple spaces. They extend standard tuple spaces with the ability of evolving the “weight” of a tuple just as it represented the concentration of a chemical substance in a biochemical system, namely, in terms of reaction and diffusion rules that adaptively apply to tuples modulo semantic match. We show that this model can be used to enact self-* properties in pervasive systems, through typical spatial patterns involving computational fields, paths, and segregation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1968513.1968517 | ACM Transactions on Autonomous and Adaptive Systems (TAAS) |
Keywords | DocType | Volume |
chemical system,pervasive computing call,chemical substance,chemical-inspired model,computational field,standard tuple space,chemical-inspired tuple space,pervasive service,general-purpose chemical reaction,chemical-inspired tuple spaces,gradient-based interaction,pervasive systems,spatial computing pattern,pervasive application,diffusion rule,natureinspired coordination model,pervasive services,i. introduction,biochemical system,spatial concept,pervasive system,typical spatial pattern,spatial coordination,key result,chemicals,ubiquitous computing,tuple space,noise,spatial pattern,semantics,pervasive computing,computational modeling | Journal | 6 |
Issue | ISSN | Citations |
2 | 1556-4665 | 52 |
PageRank | References | Authors |
1.84 | 43 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mirko Viroli | 1 | 2278 | 156.77 |
| Matteo Casadei | 2 | 224 | 16.78 |
| Sara Montagna | 3 | 345 | 23.45 |
| Franco Zambonelli | 4 | 4662 | 330.78 |