Modeling and simulation of the IEEE 802.11e wireless protocol with hidden nodes using Colored Petri Nets

Wireless technologies are continuously evolving, including features such as the extension to mid- and long-range communications and the support of an increasing number of devices. However, longer ranges increase the probability of suffering from hidden terminal issues. In the particular case of Wireless Local Area Networks (WLANs), the use of Quality of Service (QoS) mechanisms introduced in IEEE 802.11e compromises scalability, exacerbates the hidden node problem, and creates congestion as the number of users and the variety of services in the network grow. In this context, this paper presents a configurable Colored Petri Net (CPN) model for the IEEE 802.11e protocol with the aim of analyzing the QoS support in mid- and long-range WLANs The CPN model covers the behavior of the protocol in the presence of hidden nodes to examine the performance of the RTS/CTS exchange in scenarios where the QoS differentiation may involve massive collision chains and high delays. Our CPN model sets the basis for further exploring the performance of the various mechanisms defined by the IEEE 802.11 standard. We then use this CPN model to provide a comprehensive study of the effectiveness of this protocol by using the simulation and monitoring capabilities of CPN Tools.

[1]  Reinhard German,et al.  Performance evaluation of IEEE 802.11 wireless LANs with stochastic Petri nets , 1999, Proceedings 8th International Workshop on Petri Nets and Performance Models (Cat. No.PR00331).

[2]  Robin Milner,et al.  Definition of standard ML , 1990 .

[3]  Sandip Chakraborty Analyzing Peer Specific Power Saving in IEEE 802.11s Through Queuing Petri Nets: Some Insights and Future Research Directions , 2016, IEEE Transactions on Wireless Communications.

[4]  Jalel Ben-Othman,et al.  Performance evaluation tools for QoS MAC protocol for wireless sensor networks , 2014, Ad Hoc Networks.

[5]  Ignas G. Niemegeers,et al.  Outdoor Long-Range WLANs: A Lesson for IEEE 802.11ah , 2015, IEEE Communications Surveys & Tutorials.

[6]  Reinhard German,et al.  Performance modeling of IEEE 802.11 wireless LANs with stochastic Petri nets , 2001, Perform. Evaluation.

[7]  Tapani Ristaniemi,et al.  Performance Analysis of IEEE 802.11ac DCF with Hidden Nodes , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[8]  Weihua Zhuang,et al.  Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach , 2014, IEEE Transactions on Mobile Computing.

[9]  P. Chenna Reddy,et al.  Evaluation of starvation problem under saturated loads in IEEE 802.11e , 2016, 2016 International Conference on Emerging Technological Trends (ICETT).

[10]  Mark Davis,et al.  An Experimental Investigation of IEEE 802.11e TXOP Facility for Real-Time Video Streaming , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[11]  Cintia B. Margi,et al.  Behavioral Model of IEEE 802.15.4 Beacon-Enabled Mode Based on Colored Petri Net , 2017, ACM Trans. Model. Perform. Evaluation Comput. Syst..

[12]  Kent Inge Fagerland Simonsen,et al.  Model-based Development for MAC Protocols in Industrial Wireless Sensor Networks , 2016, PNSE @ Petri Nets.

[13]  James Lyle Peterson,et al.  Petri net theory and the modeling of systems , 1981 .

[14]  Andrea Fumagalli,et al.  An Analytical Model with Improved Accuracy of IEEE 802.11 Protocol Under Unsaturated Conditions , 2010, 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.

[15]  Ilenia Tinnirello,et al.  Experimental Assessment of the Backoff Behavior of Commercial IEEE 802.11b Network Cards , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[16]  Luis Orozco-Barbosa,et al.  Modeling and Analysis of the 1-Wire Communication Protocol Using Timed Colored Petri Nets , 2018, IEEE Access.

[17]  Ren Ping Liu,et al.  A channel access cycle based model for IEEE 802.11e EDCA in unsaturated traffic conditions , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[18]  Luis Orozco-Barbosa,et al.  Performance evaluation and tuning of an IEEE 802.11 audio video multicast collision prevention mechanism , 2020, Wirel. Networks.

[19]  Byeong-Hee Roh,et al.  Delay analysis of IEEE 802.11e EDCA with enhanced QoS for delay sensitive applications , 2016, 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC).

[20]  Ricardo Moraes,et al.  A Stochastic Petri Net Model for the Simulation Analysis of the IEEE 802.11e EDCA Communication Protocol , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[21]  Ayoub Bahnasse,et al.  Study and evaluation of voice over IP signaling protocols performances on MIPv6 protocol in mobile 802.11 network: SIP and H.323 , 2017, 2017 International Symposium on Networks, Computers and Communications (ISNCC).

[22]  Javier Gomez,et al.  RegionDCF: A Self-Adapting CSMA/Round-Robin MAC for WLAN , 2015, Wirel. Pers. Commun..

[23]  J. Campos,et al.  An evaluation of QoS for intensive video traffic over 802.11e WLANs , 2015, 2015 International Conference on Electronics, Communications and Computers (CONIELECOMP).

[24]  S. K. Sarma,et al.  QoS and Admission Controller in IEEE 802.11e WLAN , 2013, 2013 4th International Conference on Intelligent Systems, Modelling and Simulation.

[25]  Mythili Vutukuru,et al.  TCP Download Performance in Dense WiFi Scenarios: Analysis and Solution , 2017, IEEE Transactions on Mobile Computing.

[26]  David I. Laurenson,et al.  Insights into the hidden node problem , 2006, IWCMC '06.

[27]  Jean-Paul M. G. Linnartz,et al.  Dynamic Performance Analysis of IEEE 802.15.4 Networks under Intermittent Wi-Fi Interference , 2018, 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).

[28]  H. Facchini,et al.  Tuning Mechanism For IEEE 802.11e EDCA Optimization , 2013, IEEE Latin America Transactions.

[29]  E. Puschita,et al.  HCCA support in IEEE 802.11 networks QoS and QoE performance evaluation , 2012, 2012 10th International Symposium on Electronics and Telecommunications.

[30]  Belhassen Zouari,et al.  Formal Approach for Modeling, Verification and Performance Analysis of Wireless Sensors Network , 2015, WWIC.

[31]  Haitao Wu,et al.  WSN02-1: Analysis of IEEE 802.11 DCF with Hidden Terminals , 2006, IEEE Globecom 2006.

[32]  Guy Juanole,et al.  Revisiting the Markov Chain Model of IEEE 802.11E EDCA and Introducing the Virtual Collision Phenomenon , 2007, WINSYS.

[33]  Xiang Hu,et al.  Modelling and Performance Analysis of IEEE 802.11 DCF Using Coloured Petri Nets , 2016, Comput. J..

[34]  P. Thangaraj,et al.  Throughput analysis of IEEE 802.11e EDCA under non saturation condition , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[35]  Sanghyun Kim,et al.  Collision chain mitigation and hidden device-aware grouping in large-scale IEEE 802.11ah networks , 2016, Comput. Networks.

[36]  Xiang Hu,et al.  Efficient modeling and performance analysis for IEEE 802.15.4 with coloured Petri nets , 2017, 2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS).

[37]  Lars Michael Kristensen,et al.  Coloured Petri Nets - Modelling and Validation of Concurrent Systems , 2009 .

[38]  Belhassen Zouari,et al.  Global generic model for formal validation of the wireless sensor networks properties , 2011 .