2016
Karyotis, V.; Stai, E.; Papavassiliou, S.
A component-based cross-layer framework for software defined wireless networks Conference
Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781509029143, (cited By 3; Conference of 8th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2016 ; Conference Date: 21 November 2016 Through 23 November 2016; Conference Code:125557).
Abstract | Links | BibTeX | Tags: Autonomous decision; Component based approach; Component-based architecture; Cross-layer design; Cross-layer framework; Heterogeneous wireless network; Network optimization; Proposed architectures, Decision making; Heterogeneous networks; Markov processes; Network layers; Resource allocation; Structural frames; Wireless networks, Network architecture
@conference{Karyotis2016,
title = {A component-based cross-layer framework for software defined wireless networks},
author = {V. Karyotis and E. Stai and S. Papavassiliou},
editor = {Vassiliou V. Pau G. Badra M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011284151&doi=10.1109%2fNTMS.2016.7792426&partnerID=40&md5=20e00845b790f63c4550f376c4bbc308},
doi = {10.1109/NTMS.2016.7792426},
isbn = {9781509029143},
year = {2016},
date = {2016-01-01},
journal = {2016 8th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2016},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
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.},
note = {cited By 3; Conference of 8th IFIP International Conference on New Technologies, Mobility and Security, NTMS 2016 ; Conference Date: 21 November 2016 Through 23 November 2016; Conference Code:125557},
keywords = {Autonomous decision; Component based approach; Component-based architecture; Cross-layer design; Cross-layer framework; Heterogeneous wireless network; Network optimization; Proposed architectures, Decision making; Heterogeneous networks; Markov processes; Network layers; Resource allocation; Structural frames; Wireless networks, Network architecture},
pubstate = {published},
tppubtype = {conference}
}
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.