Name
Abstract | ||
|---|---|---|
To improve the efficiency of peer-to-peer (P2P) systems while adapting to changing environmental conditions, static peer-to-peer protocols can be replaced by adaptive plans. The resulting systems are inherently complex, which makes their development and characterization a challenge for traditional methods. Here we propose the design and analysis of adaptive P2P systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. These measures allow the evaluation of adaptive P2P systems and thus can be used to guide their design. We evaluate the proposal with a P2P computing system provided with adaptation mechanisms. We show the evolution of the system with static and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, which correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less “aggressive”, the system may be more stable, but the optimal performance may not be achieved. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s12083-015-0385-4 | Peer-to-Peer Networking and Applications |
Keywords | Field | DocType |
Adaptive peer-to-peer system,Evolution,Complexity,Information theory | Information theory,Peer-to-peer,Computer science,Workload,Computing systems,Distributed computing | Journal |
Volume | Issue | ISSN |
9 | 6 | 1936-6442 |
Citations | PageRank | References |
3 | 0.44 | 22 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michele Amoretti | 1 | 320 | 43.35 |
| Carlos Gershenson | 2 | 392 | 42.34 |