Name
Abstract | ||
|---|---|---|
With the expansion of cloud computing, virtual network (VN) migration becomes the very perspective technology for saving energy, ensuring Service Level Agreements or improving the survivability of virtual networks in cloud networks. At present, the majority of research on the VN migration, however, are for saving energy or improving resource utilizations, and few of them for the entire virtual network migration for guaranteeing QoS or improving the survivability of virtual networks. Since the regional failure, network maintenance or QoS violation, the service provider generally needs to migrate the VN for guaranteeing the QoS or improving the survivability of virtual networks. In the paper, we research the live migration problem of the virtual network to optimize the virtual network migration performance. To efficient migrate virtual network, we present an effective VN migration method, VNM. To control the cost of migration or migration traffic, based on the VNM algorithm, we present an effective VN migration method with migration traffic control, VNM-MTC. We use two networks as substrate networks to simulate the performances of our presented algorithms. From the experiment, we can see that the total VN reconfiguration cost, total VN redeployment cost, total VN migration cost and blocking ratio of our presented algorithms are better than that of the contrast algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s11107-017-0739-3 | Photonic Network Communications |
Keywords | Field | DocType |
Cloud computing,Virtual networks,Live migration | Virtual network,Survivability,Service level,Live migration,Computer science,Quality of service,Computer network,Service provider,Control reconfiguration,Cloud computing,Distributed computing | Journal |
Volume | Issue | ISSN |
35 | 2 | 1572-8188(Series Online ISSN)1387-974X(Series Print ISSN) |
Citations | PageRank | References |
0 | 0.34 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| San-mei Zhang | 1 | 0 | 0.34 |
| Gang Sun | 2 | 463 | 36.98 |
| Victor Chang | 3 | 1202 | 107.48 |