Name
Abstract | ||
|---|---|---|
Fog computing has emerged as a strong distributed computation paradigm to support applications with stringent latency requirements. It offers almost ubiquitous computation capacities over a large geographical area. However, Fog systems are highly heterogeneous and dynamic which makes services placement decision quite challenging considering nodes mobility that may decrease the placement decision quality over time. This paper proposes a Mobility-aware Genetic Algorithm (MGA) for services placement in the Fog which aims at supporting nodes’ mobility while ensuring both infrastructures energy-efficiency and applications Quality of Service (QoS) requirements. We have compared this approach with two variants of Shortest Access Point migration strategy (SAP) from the literature, a proposed Mobility Greedy Heuristic (MGH) and a baseline Simple Genetic Algorithm (SGA). Experiments conducted with MyiFogSim simulator have shown that MGA ensures good performances in terms of energy and delay violations minimization compared to other methods. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/SoftCOM50211.2020.9238236 | 2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) |
Keywords | DocType | ISSN |
Internet of Things,optimization,Mobility,Fog Computing,Smart Campus,QoS,Energy | Conference | 1848-1744 |
ISBN | Citations | PageRank |
978-1-7281-7538-6 | 0 | 0.34 |
References | Authors | |
16 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tanissia Djemai | 1 | 0 | 0.34 |
| Patricia Stolf | 2 | 125 | 17.37 |
| Thierry Monteil | 3 | 167 | 26.54 |
| Jean-Marc Pierson | 4 | 623 | 59.06 |