Name
Abstract | ||
|---|---|---|
Discrete event simulations are a powerful technique for modeling stochastic systems with multiple components where interactions between these components are governed by the probability distribution functions associated with them. Complex discrete event simulations are often computationally intensive with long completion times. This paper describes our solution to the problem of orchestrating the execution of a stochastic, discrete event simulation where computational hot spots evolve spatially over time. Our performance benchmarks report on our ability to balance computational loads in these settings. Copyright © 2013 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1002/cpe.3121 | Concurrency and Computation: Practice & Experience |
Keywords | DocType | Volume |
discrete event simulations,distributed systems,stream processing systems,epidemiological simulations | Journal | 26 |
Issue | ISSN | Citations |
11 | 1532-0626 | 4 |
PageRank | References | Authors |
0.41 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiquan Sui | 1 | 9 | 1.51 |
| Neil Harvey | 2 | 19 | 2.86 |
| Shrideep Pallickara | 3 | 837 | 92.72 |