(2016). A component-based cross-layer framework for software defined wireless networks. In 2016 8th IFIP International Conference on New Technologies, Mobility and Security (NTMS) (pp. 1–6). https://doi.org/10.1109/NTMS.2016.7792426
Περίληψη
Network architectures that exhibit cognitive behavior, such as self-adaptation and reconfiguration, are becoming extremely popular paradigms for the future heterogeneous wireless networks. Towards this direction, in this paper, we leverage on the component-based approach to achieve modular cross-layer design and propose a protocol stack with adaptive features that allows autonomous decision-making using local ambient information. The proposed framework allows segregating control from the data plane and combining different techniques, such as backpressure and Markov Random Fields (MRFs), for more efficient adaptation and flexibility against network variations. We demonstrate the effectiveness of the proposed approach and the component-based features of the architecture by presenting hybrid control plane mechanisms that combine the aforementioned techniques in a modular fashion. Finally, we provide directions for practically exploiting the proposed architecture. © 2016 IEEE.
- DOI
- 10.1109/NTMS.2016.7792426
- ISBN
- 9781509029143
- Τύπος
- Άρθρο σε Πρακτικά Συνεδρίου
- Έτος
- 2016
Σύνδεσμοι
BibTeX
@inproceedings{karyotis2016component,
title = {A component-based cross-layer framework for software defined wireless networks},
author = {Vasileios Karyotis and Eleni Stai and Symeon Papavassiliou},
url = {https://doi.org/10.1109/NTMS.2016.7792426},
doi = {10.1109/NTMS.2016.7792426},
isbn = {9781509029143},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {2016 8th IFIP International Conference on New Technologies, Mobility and Security (NTMS)},
pages = {1--6},
organization = {IEEE},
abstract = {Network architectures that exhibit cognitive behavior, such as self-adaptation and reconfiguration, are becoming extremely popular paradigms for the future heterogeneous wireless networks. Towards this direction, in this paper, we leverage on the component-based approach to achieve modular cross-layer design and propose a protocol stack with adaptive features that allows autonomous decision-making using local ambient information. The proposed framework allows segregating control from the data plane and combining different techniques, such as backpressure and Markov Random Fields (MRFs), for more efficient adaptation and flexibility against network variations. We demonstrate the effectiveness of the proposed approach and the component-based features of the architecture by presenting hybrid control plane mechanisms that combine the aforementioned techniques in a modular fashion. Finally, we provide directions for practically exploiting the proposed architecture. © 2016 IEEE.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}