Research Article
Towards Knowledge-Driven Mobility Support
@INPROCEEDINGS{10.1007/978-3-030-69066-3_18, author={Zhongda Xia and Yu Zhang}, title={Towards Knowledge-Driven Mobility Support}, proceedings={Artificial Intelligence for Communications and Networks. Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings}, proceedings_a={AICON}, year={2021}, month={7}, keywords={Mobility Mobility support approach Knowledge-driven networking Internet architecture}, doi={10.1007/978-3-030-69066-3_18} }- Zhongda Xia
Yu Zhang
Year: 2021
Towards Knowledge-Driven Mobility Support
AICON
Springer
DOI: 10.1007/978-3-030-69066-3_18
Abstract
Mobility refers to the ability to conduct “seamless” communication with network entities whose network location constantly changes. This paper examines the mobility support problem in IP and Named Data Networking (NDN), and identifies two dimensions in the mobility support solution space: the host dimension and data dimension. Existing host dimension solutions have exhausted the available design choices, and have not been able to achieve new breakthroughs in performance. Recognizing this limitation, this paper proposes a novel knowledge dimension. In the knowledge dimension, two knowledge-driven mobility support approaches, Topology-driven Intermediate Placement (TIP) and Trajectory-driven Reachability Update (TRU), are proposed. These approaches exploit knowledge such as network topology and movement trajectory to tweak the network and network services for better overall 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.