Name
Abstract | ||
|---|---|---|
Fog computing brings the convenience of cloud computing closer to the edge of the Internet and even further into local area networks. A central aspect of fog computing in an industrial scenario concerns the orchestration of applications to be executed on an existing automation system network. This paper studies the problem of mapping distributed applications onto an industrial fog network so as to minimize data transfer cost while adhering to resource constraints. The resulting fog application allocation problem is NP-complete and can be described as an integer linear program. We present and evaluate three polynomial-time heuristics, which exploit the problem structure of a typical fog application and are shown to find high quality allocations efficiently. Through extensive simulations on practically relevant scenarios, we show that the best performing heuristic has performance comparable to the optimal solution across most tested problem instances. The experiments with a real industrial fog application show that the best performing heuristic has an optimality gap of only 3.6%. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICFC.2019.00021 | 2019 IEEE International Conference on Fog Computing (ICFC) |
Keywords | Field | DocType |
fog computing,allocation,automation systems | Heuristic,Process automation system,Computer science,Automation,Heuristics,Linear programming,Local area network,Orchestration (computing),Distributed computing,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-7281-3237-2 | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Suter | 1 | 0 | 0.34 |
| Raphael Eidenbenz | 2 | 0 | 0.34 |
| Yvonne Anne Pignolet | 3 | 0 | 0.34 |
| Ankit Singla | 4 | 12 | 2.63 |