Name
Abstract | ||
|---|---|---|
We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes. In this model, each node has bounded computation and storage capabilities that do not grow with the network size. Furthermore, each node only knows its neighbors, not the entire graph. Our goal is to characterize the class of functions that can be computed within this model. In our main result, we provide a necessary condition for computability which we show to be nearly sufficient, in the sense that every function that violates this condition can at least be approximated. The problem of computing (suitably rounded) averages in a distributed manner plays a central role in our development; we provide an algorithm that solves it in time that grows quadratically with the size of the network. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TAC.2011.2163874 | Automatic Control, IEEE Transactions |
Keywords | Field | DocType |
computability,computational complexity,distributed algorithms,storage management,anonymous nodes,bounded computation,deterministic distributed function computation,distributed anonymous discrete function computation,identical nodes,network size,storage capability,averaging algorithms,distributed computing,distributed control,satisfiability,distribution function,cluster computing | Approximation algorithm,Quadratic growth,Computer science,Algorithm,Computability,Distributed algorithm,Memory management,Computational complexity theory,Computation,Bounded function | Journal |
Volume | Issue | ISSN |
56 | 10 | 0018-9286 |
Citations | PageRank | References |
8 | 0.63 | 23 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien M. Hendrickx | 1 | 772 | 77.11 |
| Alex Olshevsky | 2 | 1227 | 87.77 |
| John N. Tsitsiklis | 3 | 712 | 101.13 |