A Novel Predictive Handover Protocol for Mobile IP in Vehicular Networks
Vehicular networking is an emerging technology that offers the potential of providing a variety of new services. However, extending vehicular networks to include internet protocol (IP) connections is still problematic, due in part to the incompatibility of mobile IP handovers with the increased mobility of vehicles. The handover process, consisting of discovery, registration, and packet forwarding, has a large overhead and disrupts connectivity. With increased handover frequency and smaller access-point (AP) dwell times in vehicular networks, the handover causes a large degradation in performance. This paper proposes a predictive handover protocol, using a combination of a Kalman filter (KF) and an online hidden Markov model (HMM), to minimize the effects of prediction errors and to capitalize on advanced handover registration. Extensive simulated experiments were carried out in the network simulator ns-2 to study the performance of the proposed protocol within a variety of traffic and network topology scenarios. Results show a significant improvement to both prediction accuracy and network performance when compared with recent proposed approaches.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
-
Supplemental Notes:
- Copyright © 2016, IEEE.
-
Authors:
- Magnano, Alexander
- Fei, Xin
- Boukerche, Azzedine
- Loureiro, Antonio A F
- Publication Date: 2016-10
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 8476-8495
-
Serial:
- IEEE Transactions on Vehicular Technology
- Volume: 65
- Issue Number: 10
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 0018-9545
- Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25
Subject/Index Terms
- TRT Terms: Kalman filtering; Markov processes; Mobile communication systems; Vehicular ad hoc networks
- Identifier Terms: Internet Protocol
- Subject Areas: Data and Information Technology; Highways;
Filing Info
- Accession Number: 01617533
- Record Type: Publication
- Files: TRIS
- Created Date: Nov 21 2016 1:44PM