Minimizing age of information in vehicular networks

Emerging applications rely on wireless broadcast to disseminate time-critical information. For example, vehicular networks may exchange vehicle position and velocity information to enable safety applications. The number of nodes in one-hop communication range in such networks can be very large, leading to congestion and undesirable levels of packet collisions. Earlier work has examined such broadcasting protocols primarily from a MAC perspective and focused on selective aspects such as packet error rate. In this work, we propose a more comprehensive metric, the average system information age, which captures the requirement of such applications to maintain current state information from all other nearby nodes. We show that information age is minimized at an optimal operating point that lies between the extremes of maximum throughput and minimum delay. Further, while age can be minimized by saturating the MAC and setting the CW size to its throughput-optimal value, the same cannot be achieved without changes in existing hardware. Also, via simulations we show that simple contention window size adaptations like increasing or decreasing the window size are unsuitable for reducing age. This motivates our design of an application-layer broadcast rate adaptation algorithm. It uses local decisions at nodes in the network to adapt their messaging rate to keep the system age to a minimum. Our simulations and experiments with 300 ORBIT nodes show that the algorithm effectively adapts the messaging rates and minimizes the system age.

[1]  Qi Chen,et al.  Overhaul of ieee 802.11 modeling and simulation in ns-2 , 2007, MSWiM '07.

[2]  Augustin Iuoras,et al.  A broadcast congestion control scheme for OBP satellites , 2001, Space Commun..

[3]  Sumit Roy,et al.  Congestion Control to Achieve Optimal Broadcast Efficiency in VANETs , 2010, 2010 IEEE International Conference on Communications.

[4]  Seongkwan Kim,et al.  CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[5]  Bruce S. Davie,et al.  Computer Networks: A System Approach , 1998, IEEE Communications Magazine.

[6]  Panganamala Ramana Kumar,et al.  Efficient Message Composition and Coding for Cooperative Vehicular Safety Applications , 2007, IEEE Transactions on Vehicular Technology.

[7]  Hariharan Krishnan,et al.  Implementation and evaluation of scalable Vehicle-to-Vehicle transmission control protocol , 2010, 2010 IEEE Vehicular Networking Conference.

[8]  Aaron Weinfeld Methods to Reduce DSRC Channel Congestion and Improve V2V Communication Reliability , 2010 .

[9]  Tao Zhang,et al.  Dedicated Short‐Range Communications , 2012 .

[10]  Mario Gerla,et al.  Random access MAC for efficient broadcast support in ad hoc networks , 2000, 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).

[11]  Bruce S. Davie,et al.  Computer Networks: A Systems Approach , 1996 .

[12]  Martin Mauve,et al.  A survey on congestion control for mobile ad hoc networks , 2007, Wirel. Commun. Mob. Comput..

[13]  Sumit Roy,et al.  Contention Window and Transmission Opportunity Adaptation for Dense IEEE 802.11 WLAN Based on Loss Differentiation , 2008, 2008 IEEE International Conference on Communications.

[14]  Hariharan Krishnan,et al.  Intervehicle Transmission Rate Control for Cooperative Active Safety System , 2011, IEEE Transactions on Intelligent Transportation Systems.

[15]  Chieh-Yih Wan,et al.  CODA: congestion detection and avoidance in sensor networks , 2003, SenSys '03.

[16]  Chunming Qiao,et al.  Advances in internet congestion control , 2003, IEEE Communications Surveys & Tutorials.

[17]  Bhaskar Krishnamachari,et al.  Explicit and precise rate control for wireless sensor networks , 2009, SenSys '09.

[18]  Paolo Santi,et al.  Vehicle-to-Vehicle Communication: Fair Transmit Power Control for Safety-Critical Information , 2009, IEEE Transactions on Vehicular Technology.

[19]  Tim Leinmüller,et al.  Exploration of adaptive beaconing for efficient intervehicle safety communication , 2010, IEEE Network.

[20]  Sumit Roy,et al.  Stochastic modelling and analysis of 802.11 DCF with heterogeneous non-saturated nodes , 2007, Comput. Commun..

[21]  Martin Mauve,et al.  A survey on congestion control for mobile ad hoc networks: Research Articles , 2007 .

[22]  Mohamed Shawky,et al.  Verification and performance evaluation of a congestion control approach within vehicular ad hoc networks , 2009, PM2HW2N '09.

[23]  Ozan K. Tonguz,et al.  Adaptive beaconing for delay-sensitive and congestion-aware traffic information systems , 2010, 2010 IEEE Vehicular Networking Conference.

[24]  Robin Kravets,et al.  Achieving Delay Guarantees in Ad Hoc Networks through Dynamic Contention Window Adaptation , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.