Coexistence of Decentralized Congestion Control Algorithms for V2V Communication

Channel congestion is one of the most critical issues in IEEE 802.11p-based vehicular communications as it leads to the unreliability of safety applications. As a countermeasure, many Decentralized Congestion Control (DCC) algorithms have been proposed. One of the most prominent DCC algorithms is the message-rate based LIMERIC. Recently, algorithms have also been proposed to support higher vehicle density (better scalability). One of such algorithms is the combined message-rate and data-rate based congestion control algorithm (MD-DCC). MD-DCC can support around 2.7 times higher vehicular density than LIMERIC. However, if LIMERIC has been deployed, can MD-DCC be introduced and coexist well with LIMERIC. The objective of this paper is to investigate how MD-DCC coexists with LIMERIC. Given a scenario where vehicles may use either LIMERIC or MD-DCC, we study the impact of coexistence on channel load, fairness and reliability of vehicles at different densities. Simulation studies show that there is no significant degradation of reliability both for LIMERIC and MD-DCC at different densities. On the contrary, coexistence can improve the reliability of LIMERIC vehicles. Furthermore, MD-DCC can support vehicles at large densities even when it coexists with LIMERIC retaining its scalability. However, fair allocation of resources is not guaranteed when LIMERIC and MD-DCC coexist.

[1]  Torsten Lorenzen Performance Analysis of the Functional Interaction of Awareness Control and DCC in VANETs , 2016, 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall).

[2]  Hong Li,et al.  Data Rate based Congestion Control in V2V communication for traffic safety applications , 2015, 2015 IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT).

[3]  Mate Boban,et al.  ECPR: Environment-and context-aware combined power and rate distributed congestion control for vehicular communications , 2015, Comput. Commun..

[4]  Hannes Hartenstein,et al.  Design methodology and evaluation of rate adaptation based congestion control for Vehicle Safety Communications , 2011, 2011 IEEE Vehicular Networking Conference (VNC).

[5]  Daniel Krajzewicz,et al.  Recent Development and Applications of SUMO - Simulation of Urban MObility , 2012 .

[6]  Hannes Hartenstein,et al.  Joint power/rate congestion control optimizing packet reception in vehicle safety communications , 2013, Vehicular Ad Hoc Networks.

[7]  Charles E. Rohrs,et al.  LIMERIC: a linear message rate control algorithm for vehicular DSRC systems , 2011, VANET '11.

[8]  Fan Bai,et al.  Reliability Analysis of DSRC Wireless Communication for Vehicle Safety Applications , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[9]  Marco Gruteser,et al.  Performance evaluation of a mixed vehicular network with CAM-DCC and LIMERIC vehicles , 2015, 2015 IEEE 16th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[10]  Ignas G. Niemegeers,et al.  V2X Application-Reliability Analysis of Data-Rate and Message-Rate Congestion Control Algorithms , 2017, IEEE Communications Letters.

[11]  Ignas G. Niemegeers,et al.  A combined fair decentralized message-rate and data-rate congestion control for V2V communication , 2017, 2017 IEEE Vehicular Networking Conference (VNC).

[12]  Ignas Niemegeers,et al.  Fair decentralized data-rate congestion control for V2V communications , 2017, 2017 24th International Conference on Telecommunications (ICT).

[13]  Hong Li,et al.  Risk Assessment for Traffic Safety Applications with V2V Communications , 2016, 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall).