Name
Abstract | ||
|---|---|---|
Systems of \"building block\" algorithms can guarantee that self-organizing systems eventually converge to a predictable state, but what of their dynamical behavior in environments with ongoing changes? To begin to address this challenge, we analyze a commonly used distributed distance estimation algorithm from a stability theory perspective, identifying key properties of monotonicity and dynamical behavior envelope. This allows standard stability theory analysis to be applied to predict the behavior of the algorithm in response to persistent perturbation, both in isolation and as part of a composite system, as demonstrated both analytically and in simulation. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/SASOW.2015.16 | SASO Workshops |
Keywords | Field | DocType |
control theory,aggregate programming,predictable composition | Convergence (routing),Monotonic function,Mathematical optimization,Algorithm design,Computer science,Probabilistic analysis of algorithms,Prediction algorithms,Distributed algorithm,Perturbation (astronomy),Stability theory,Distributed computing | Conference |
Citations | PageRank | References |
3 | 0.40 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| amy kumar | 1 | 7 | 1.49 |
| Jacob Beal | 2 | 93 | 12.12 |
| Soura Dasgupta | 3 | 679 | 96.96 |
| Raghu Mudumbai | 4 | 7 | 1.13 |