Name
Abstract | ||
|---|---|---|
The ever-increasing mobile traffic calls for efficient mobility support at a global scale. Supporting “seamless” communication with network entities whose network location constantly changes, i.e., the mobility support problem, is extremely challenging for IP networking due to its host-centric communication model. Information-centric networking (ICN), as exemplified by the Named Data Networking (NDN) network architecture, offers new opportunities for mobility support. We identify a common design space for providing IP and NDN mobility support where solutions track the changing network locations of mobile network endpoints, and find that available design choices have been exhausted in this design space, leaving no room for substantial performance improvement. Recognizing this limitation, this paper proposes two novel knowledge-driven mobility support approaches to comprehensively improve mobility support performance. Such approaches exploit knowledge such as network topology and movement trajectory to tweak the network for better mobility support performance. A cross-architectural quantitative evaluation framework covering two communication scenarios and 5 quantifiable metrics is proposed to evaluate mobility support performance. Experiment results show that the knowledge-driven approaches significantly improve mobility support performance, demonstrating the potential of the knowledge-driven vision for providing better mobility support. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s11036-021-01866-7 | Mobile Networks and Applications |
Keywords | DocType | Volume |
Mobility support, Named data networking, Knowledge-driven networking, Quantitative evaluation framework | Journal | 27 |
Issue | ISSN | Citations |
4 | 1383-469X | 0 |
PageRank | References | Authors |
0.34 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xia Zhongda | 1 | 0 | 0.34 |
| Yu Zhang | 2 | 188 | 31.14 |
| Binxing Fang | 3 | 380 | 88.26 |