Name
Title | ||
|---|---|---|
A New Virtual Network Embedding Framework Based On Qos Satisfaction And Network Reconfiguration For Fiber-Wireless Access Network |
Abstract | ||
|---|---|---|
Fiber-Wireless (FiWi) access network, which could provide an anytime-anywhere access for end users with high bandwidth capacity and long distance, is facing the challenge of resource allocation and optimization due to the complexity and diversity of traffic demands. Though network virtualization becomes a promising solution, which allows heterogeneous virtual networks coexisting on the shared substrate network, previous works ignored both varied requirements of Quality of Service (QoS) satisfaction of virtual networks and the flexibility of reconfiguring the resource of substrate FiWi access network. In this paper, we propose a new Virtual Network Embedding (VNE) framework based on QoS satisfaction and network reconfiguration. By equipping each virtual network with a specific QoS satisfaction requirement, the characteristics of virtual network demands are formulated from a more practical point of view. Moreover, the adaptive bandwidth allocation of substrate network and virtual network reconfiguration are exploited to maximize the InP revenue. Simulation results demonstrate that our proposed VNE algorithm outperforms previous approaches with multifold increment of InP revenue. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICC.2016.7511480 | 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) |
Keywords | Field | DocType |
fiber-wireless, virtual network embedding, QoS satisfaction, network reconfiguration | Virtual network,Wireless network,Computer science,Computer network,Network architecture,Real-time computing,Wireless WAN,Heterogeneous network,Network virtualization,Network traffic control,Intelligent computer network,Distributed computing | Conference |
ISSN | Citations | PageRank |
1550-3607 | 3 | 0.44 |
References | Authors | |
8 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pengchao Han | 1 | 18 | 5.80 |
| Lei Guo | 2 | 564 | 82.56 |
| Yejun Liu | 3 | 90 | 18.35 |
| Xuetao Wei | 4 | 319 | 31.12 |
| Jian Hou | 5 | 3 | 0.44 |
| Xu Han | 6 | 3 | 0.44 |