Conflict graph-based model for IEEE 802.11 networks: A Divide-and-Conquer approach

Abstract WLANs (Wireless Local Area Networks) based on the IEEE 802.11 standard have become ubiquitous in our daily lives. We typically augment the number of APs (Access Points) within a WLAN to extend its coverage and transmission capacity. This leads to network densification, which in turn demands some form of coordination between APs so as to avoid potential misconfigurations. In this paper, we describe a performance modeling method that can provide guidance for configuring WLANs and be used as a decision-support tool by a network architect or as an algorithm embedded within a WLAN controller. The proposed approach estimates the attained throughput of each AP, as a function of the WLAN’s conflict graph, the AP loads, the frame sizes, and the link transmission rates. Our modeling approach employs a Divide-and-Conquer strategy which breaks down the original problem into multiple sub-problems, whose solutions are then combined to provide the solution to the original problem. We conducted extensive simulation experiments using the ns-3 simulator that show the model’s accuracy is generally good with relative errors typically less than 10%. We then explore two issues of WLAN configuration: choosing a channel allocation for the APs and enabling frame aggregation on APs.

[1]  Leonard Kleinrock,et al.  The Capacity of Wireless CSMA/CA Networks , 2016, IEEE/ACM Transactions on Networking.

[2]  Koushik Kar,et al.  Throughput modelling and fairness issues in CSMA/CA based ad-hoc networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[4]  Shengli Zhang,et al.  Throughput analysis of CSMA wireless networks with finite offered-load , 2013, 2013 IEEE International Conference on Communications (ICC).

[5]  F. Cail,et al.  IEEE 802.11 wireless LAN : Capacity analysis and protocol enhancement , 1998, INFOCOM 1998.

[6]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[7]  Ekram Hossain,et al.  Channel assignment schemes for infrastructure-based 802.11 WLANs: A survey , 2010, IEEE Communications Surveys & Tutorials.

[8]  Björn Landfeldt,et al.  An analytic model for Throughput Optimal Distributed Coordination Function (TO-DCF) , 2017, Telecommun. Syst..

[9]  Cory C. Beard,et al.  Analytical models for understanding space, backoff, and flow correlation in CSMA wireless networks , 2012, Wireless Networks.

[10]  Thomas Bonald,et al.  Performance of CSMA in multi-channel wireless networks , 2010, Queueing Systems.

[11]  Jinsung Lee,et al.  Making 802.11 DCF Near-Optimal: Design, Implementation, and Evaluation , 2016, IEEE/ACM Transactions on Networking.

[12]  Nj Piscataway,et al.  Wireless LAN medium access control (MAC) and physical layer (PHY) specifications , 1996 .

[13]  Michele Garetto,et al.  Modeling Per-Flow Throughput and Capturing Starvation in CSMA Multi-Hop Wireless Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[14]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[15]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[16]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[17]  Ben Y. Zhao,et al.  Utilization and fairness in spectrum assignment for opportunistic spectrum access , 2006, Mob. Networks Appl..

[18]  Lochan Verma,et al.  Wifi on steroids: 802.11AC and 802.11AD , 2013, IEEE Wireless Communications.

[19]  Patrick Thiran,et al.  Self-Organization Properties of CSMA/CA Systems and Their Consequences on Fairness , 2009, IEEE Transactions on Information Theory.

[20]  Bertrand Ducourthial,et al.  Improving fairness between close Wi-Fi access points , 2017, J. Netw. Comput. Appl..

[21]  Shaoen Wu,et al.  Rate adaptation algorithms for IEEE 802.11 networks: A survey and comparison , 2008, 2008 IEEE Symposium on Computers and Communications.

[22]  Edward W. Knightly,et al.  Closed-form throughput expressions for CSMA networks with collisions and hidden terminals , 2012, 2012 Proceedings IEEE INFOCOM.

[23]  Lili Qiu,et al.  Estimation of link interference in static multi-hop wireless networks , 2005, IMC '05.

[24]  Basil S. Maglaris,et al.  Throughput Analysis in Multihop CSMA Packet Radio Networks , 1987, IEEE Trans. Commun..

[25]  Bruno Baynat,et al.  Performance analysis of multi-hop flows in IEEE 802.11 networks: A flexible and accurate modeling framework , 2016, Perform. Evaluation.

[26]  A. M. Abdullah,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1997 .

[27]  Neeraj Gupta,et al.  New Analytical Model for Non-Saturation Throughput Analysis of IEEE 802 . 11 DCF , 2014 .

[28]  Bruno Gaujal,et al.  Study of the impact of asymmetry and carrier sense mechanism in IEEE 802.11 multi-hops networks through a basic case , 2004, PE-WASUN '04.

[29]  Katarzyna Kosek-Szott,et al.  A comprehensive analysis of IEEE 802.11 DCF heterogeneous traffic sources , 2014, Ad Hoc Networks.

[30]  Jean C. Walrand,et al.  A Distributed CSMA Algorithm for Throughput and Utility Maximization in Wireless Networks , 2010, IEEE/ACM Transactions on Networking.

[31]  Eylem Ekici,et al.  Single Hop IEEE 802.11 DCF Analysis Revisited: Accurate Modeling of Channel Access Delay and Throughput for Saturated and Unsaturated Traffic Cases , 2011, IEEE Transactions on Wireless Communications.

[32]  Thomas Begin,et al.  Conflict graph-based Markovian model to estimate throughput in unsaturated IEEE 802.11 networks , 2017, 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[33]  Mor Harchol-Balter,et al.  Performance Modeling and Design of Computer Systems: Queueing Theory in Action , 2013 .