Controlled matching game for user association and resource allocation in multi-rate WLANs?

The deployment of IEEE 802.11 based WLANs in populated areas is such that many mobile terminals are covered by several Access Points (APs). These mobiles have the possibility to associate to the AP with the strongest signal (best-RSSI association scheme).This can lead to poor performances and overloaded APs. Moreover, the well known anomaly in the protocol at the MAC layer may also lead to very unpredictable performances and affect the system throughput due to the presence of heterogeneous data rate nodes and the shared nature of the 802.11 medium. The goal of this paper is to propose an alternative approach for the association. We model the joint resource allocation and mobile user association as a matching game with complementarities, peer effects and selfish players. We focus on the throughput fairness allocation induced by the saturated regime with equal packet sizes. We propose a novel three-stages mechanism for the modeling and control of load balancing, resource allocation and user association. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as the anomaly in IEEE 802.11.

[1]  Walid Saad,et al.  Matching with externalities for context-aware user-cell association in small cell networks , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[2]  J. Nash.  Two-Person Cooperative Games , 1953 .

[3]  J. Nash.  THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[4]  Thomas Bonald,et al.  The impact of association on the capacity of WLANs , 2009, 2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.

[5]  Rachid El Azouzi,et al.  Core Stable Algorithms for Coalition Games with Complementarities and Peer Effects , 2015, PERV.

[6]  Nicolas Treich,et al.  Fear of Ruin , 2005 .

[7]  Eitan Altman,et al.  Generalized Nash Bargaining Solution for bandwidth allocation , 2006, Comput. Networks.

[8]  Lin Chen,et al.  A Game Theoretic Framework of Distributed Power and Rate Control in IEEE 802.11 WLANs , 2008, 2007 IEEE International Conference on Network Protocols.

[9]  P. Samundiswary,et al.  Performance Analysis of IEEE 802 , 2013 .

[10]  LiLi,et al.  Fairness and load balancing in wireless LANs using association control , 2007 .

[11]  L. S. Shapley,et al.  College Admissions and the Stability of Marriage , 2013, Am. Math. Mon..

[12]  Walid Saad,et al.  Many-to-many matching games for proactive social-caching in wireless small cell networks , 2014, 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[13]  Seung-Jae Han,et al.  Fairness and Load Balancing in Wireless LANs Using Association Control , 2004, IEEE/ACM Transactions on Networking.

[14]  Mznah Al-Rodhaan,et al.  Achieving Proportional Fairness via AP Power Control in Multi-Rate WLANs , 2011, IEEE Transactions on Wireless Communications.

[15]  Federico Echenique,et al.  A Solution to Matching with Preferences Over Colleagues , 2005, Games Econ. Behav..

[16]  Eitan Altman,et al.  Generalized α-fair resource allocation in wireless networks , 2008, 2008 47th IEEE Conference on Decision and Control.

[17]  John V. Guttag,et al.  Time-based Fairness Improves Performance in Multi-Rate WLANs , 2004, USENIX Annual Technical Conference, General Track.

[18]  Helena Keinänen,et al.  Algorithms for coalitional games , 2011 .

[19]  JongWon Kim,et al.  Distributed Fair Access Point Selection for Multi-Rate IEEE 802.11 WLANs , 2008, CCNC.

[20]  John C. Harsanyi,et al.  A Simplified Bargaining Model for the n-Person Cooperative Game , 1963 .

[21]  M. Pycia.  Stability and Preference Alignment in Matching and Coalition Formation , 2010 .

[22]  J. Pratt.  RISK AVERSION IN THE SMALL AND IN THE LARGE11This research was supported by the National Science Foundation (grant NSF-G24035). Reproduction in whole or in part is permitted for any purpose of the United States Government. , 1964 .

[23]  J. Gabszewicz,et al.  On Gale and Shapley "college admissions and the stability of marriage" , 2012 .

[24]  Eitan Altman,et al.  New Insights From a Fixed-Point Analysis of Single Cell IEEE 802.11 WLANs , 2007, IEEE/ACM Transactions on Networking.

[25]  JongWon Kim,et al.  Distributed Fair Access Point Selection for Multi-Rate IEEE 802.11 WLANs , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[26]  Jie Wu,et al.  Designing a Practical Access Point Association Protocol , 2010, 2010 Proceedings IEEE INFOCOM.

[27]  Jérôme Lang,et al.  Single-peaked consistency and its complexity , 2008, ECAI.

[28]  Alvin E. Roth,et al.  Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis , 1990 .

[29]  A.V. Babu,et al.  Performance analysis of IEEE 802.11 multirate WLANs: time based fairness vs throughput based fairness , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[30]  Huw Oliver,et al.  Proportional fair throughput allocation in multirate IEEE 802.11e wireless LANs , 2007, Wirel. Networks.

[31]  Satish K. Tripathi,et al.  Link quality based association mechanism in IEEE 802.11 h compliant wireless LANs , 2005 .

[32]  Anurag Kumar,et al.  Optimal Association of Stations and APs in an IEEE 802 . 11 WLAN , .

[33]  Walid Saad,et al.  A college admissions game for uplink user association in wireless small cell networks , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.