MDP-based-MAC-Design_pdf.pdf (293.56 kB)
MDP-based MAC design with deterministic backoffs in virtualized 802.11 WLANs
journal contributionposted on 2016-05-13, 13:57 authored by Atoosa Dalili Shoaei, Mahsa DerakhshaniMahsa Derakhshani, Saeedeh Parsaeefard, Tho Le-Ngoc
This paper presents MAC protocols for a virtualized 802.11 network aiming to improve network performance and isolation among service providers (SPs). Taking into account the statistical properties of arrival traffic, a Markov Decision Process (MDP) is formulated to maximize the network throughput subject to SP reservations. By introducing the policy tree of the MDP, we present an optimal access policy. Each user can track this policy tree by carrier sensing and learn its transmission opportunity. As computational complexity of the policy tree grows exponentially with the total number of users, an efficient heuristic algorithm is proposed based on the MDP formulation where each user is assigned a deterministic backoff value. Numerical results show that performance of the proposed heuristic algorithm closely matches to the optimal policy. Moreover, both optimal and heuristic algorithms significantly improve TDMA and CSMA in terms of packet delivery ratio and isolation in unsaturated networks.
- Mechanical, Electrical and Manufacturing Engineering
Published inIEEE Transactions on Vehicular Technology
Pages1 - 1
CitationDALILI SHOAEI, A.D. ...et al., 2015. MDP-based MAC design with deterministic backoffs in virtualized 802.11 WLANs. IEEE Transactions on Vehicular Technology, In Press.
- AM (Accepted Manuscript)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Notes(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works