Reliable and Efficient Routing Protocols for Vehicular Communication Networks

1. Reliable and Efficient Routing Protocols for Vehicular Communication Networks Transfer Presentation Katsaros Konstantinos PhD Student Supervisor: Dr. M. Dianati Co-supervisor: Prof. R. Tafazolli

2. Outline • Introduction • Scope, Objectives, Challenges • Routing in VANETs • Taxonomy, Forwarding techniques, Recovery strategies, Cross-layering • Achievements so far • Proposed CLWPR (System model, design characteristics) • Performance evaluation • Future plan 2 Konstantinos Katsaros

3. Scope • Intelligent Transportation Systems (ITS) • Application of Information and Communication Technologies for future transport systems • In order to: • Improve safety and traffic management • Provide infotainment services. • Vehicular Communications is an important part of ITS. • Cellular (3G, LTE) and Dedicated Short Range Communications (IEEE 802.11p / WAVE) 3 Konstantinos Katsaros

4. VANETs: Challenges & Opportunities • Are a category of Mobile Ad-hoc Networks (MANETs) with specific characteristics: • Less strict energy and computational constraints • Highly dynamic • Predictable mobility patterns • High density of nodes 4 Konstantinos Katsaros

5. Objectives of this work • To design reliable and efficient routing protocols by exploiting: • Position and mobility information in order to increase efficiency • PHY and MAC information in order to increase reliability • To design a Location Service • that can provide position information for the routing protocols 5 Konstantinos Katsaros

6. BACKGROUND Overview of routing and forwarding protocols for MANETs and VANETs 6 Konstantinos Katsaros

7. Routing Taxonomy 7 Konstantinos Katsaros

8. Position-based Forwarding without Navigation 6 1 7 5 2 S D 3 4 8 Random Positive Progress Compass Greedy Forwarding Most Forward in Radius Nearest Forwarding Progress 8 Konstantinos Katsaros

9. Local Maximum Problem & Recovery Techniques • Recovery strategies: • Drop packet • Enhanced Greedy (random retransmission once) • Carry-n-Forward • Coloring • Left hand rule • Perimeter routing S D 9 Konstantinos Katsaros

10. Position-based Forwarding with Navigation “Anchor” points at junctions with coordinator nodes Enhanced beacon messages with velocity/heading Position prediction policy (dead reckoning) Estimation of link lifetime Vehicle traffic information (max velocity, traffic density) Recovery From Local Maximum Re-route using different anchor points (with or without deletion) 10 Konstantinos Katsaros

11. Cross-Layer Optimization of Routing Protocols • Network layer with PHY and MAC: Use channel/link quality information for routing decision • Network layer with Transport and Application: Provide different levels of priorities on packets 11 Konstantinos Katsaros

12. CROSS-LAYER POSITION BASED ROUTING (CLWPR) Proposed routing protocol: system model and design characteristics 12 Konstantinos Katsaros

13. System Model • Important Assumptions: • Position and navigation information are available (e.g., using GPS) • Nodes are equipped with the IEEE 802.11p based communication facility 13 Konstantinos Katsaros

14. Main Features of CLWPR • Unicast, multi-hop, cross-layer, opportunistic routing • Neighbor discovery based on periodic 1-hop “HELLO” messages • “HELLO” message content: position, velocity, heading, road id, node utilization, MAC information, number of cached packets total size 52bytes • Use of position prediction and “curvemetric” distance • Use of SNIR information from “HELLO” messages • Employ carry-n-forward strategy for local-maximum • Combine metrics in a weighting function used for forwarding decisions 14 Konstantinos Katsaros

15. Weighting Function for Next Hop Selection • The node with the least weight will be selected • Currently fiweights are fixed – open issue to optimize them or use adaptive values 15 Konstantinos Katsaros

16. PERFORMANCE EVALUATION Simulation setup, initial results, performance analysis and comparison 16 Konstantinos Katsaros

17. Simulations Setup • Performance metrics • Packet Deliver Ratio (PDR), • End-to-End Delay, • network overhead. • Use ns-3 for simulations • 5x5 grid network, • 200 and 100 vehicles scenarios • 10 concurrent vehicle-to-vehicle connections • UDP packets (512 Bytes) with 2 sec interval • IEEE 802.11p, 3Mbps, RTS/CTS enabled • Two-Ray-Ground model 17 Konstantinos Katsaros

18. Comparison with GPSR • Increased PDR • Reduced end-to-end delay • Increased overhead due to larger HELLO messages 18 Konstantinos Katsaros

19. Impact of HELLO interval and prediction • Prediction improves PDR • More frequent HELLO increases PDR • Network overhead could be reduced by increasing HELLO interval for the same PDR threshold. 19 Konstantinos Katsaros

20. Influence of navigation • Navigation improves PDR • Increasing weight of navigation information has positive effect in higher vehicle speeds 20 Konstantinos Katsaros

21. Influence of SNIR • SNIR information reduces end-to-end delay • Due to propagation model used, not big improvements • Expect more when shadowing is included 21 Konstantinos Katsaros

22. Influence of Carry-n-Forward • Increased PDR with time of caching • Increased end-to-end delay with time of caching 22 Konstantinos Katsaros

23. FUTURE WORK CWPR optimization, proposed location service, impact assessment and security issues 23 Konstantinos Katsaros

24. Future Work (1) • CLWPR Optimization • Use realistic propagation model • Optimize all weighting parameters • Location Service (a) • RSUs as distributed database • Co-operation between nodes • Reduce number and latency of queries 24 Konstantinos Katsaros

25. Future Work (2) • Location Service (b) – heterogeneous network • Use of UMTS technologies for control and signaling to provide location service • Impact Assessment • Asses impact of ITS applications on network reliability • Security Issues • Analyze potential threats on reliability of vehicular networks, specially for Location services 25 Konstantinos Katsaros

26. Work Plan 26 Konstantinos Katsaros

27. Publications • Current: • K. Katsaros, et al. “CLWPR - A novel cross-layer optimized position based routing protocol for VANETs", in IEEE Vehicular Networking Conference, pp. 200-207, 2011 • K. Katsaros, et al. “Application of Vehicular Communications for Improving the Efficiency of Traffic in Urban Areas", accepted in Wireless Communications and Mobile Computing, 2011. • K. Katsaros, et al. ”Performance Analysis of a Green Light Optimized Speed Advisory (GLOSA) application using an integrated cooperative ITS simulation platform", in Proceedings of IEEE International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 918 - 923, 2011 • Planned: • Survey Paper on routing protocols for VANETs • Conf. paper @ NS-3 Workshop in SIMUTools 2012, regarding the architecture and implementation (Nov. ‘11) • Journal article @ JSAC on Vehicular Communications extending CLWPR paper (Feb. ‘12) 27 Konstantinos Katsaros

28. Questions Email: K.Katsaros@surrey.ac.uk www: info.ee.surrey.ac.uk/Personal/K.Katsaros/ 28 Konstantinos Katsaros

29. Current work Propagation Loss Model for urban environment, initial results 29 Konstantinos Katsaros

30. Winner B1 model for urban V2V Use propagation models from [1] taking into account buildings and shadowing with LOS and NLOS components [1] IST-WINNER D1.1.2 P. Kyösti, et al., "WINNER II Channel Models", September 2007. Available at: https://www.ist-winner.org/WINNER2-Deliverables/D1.1.2v1.1.pdf 30 Konstantinos Katsaros

31. TwoRayGround Vs. Winner in network graph / connections 31 Konstantinos Katsaros

32. TwoRayGround Vs. Winner in PDR 32 Konstantinos Katsaros

33. Cross-Layer Designs (1) • Network layer with PHY and MAC: Use channel/link quality information for routing decision • Link Residual Time • SNR info for MuiltiPoint Relay selection • MAC layer position information for prediction • MAC retransmissions • DeReHQ [1]: Delay, Reliability and Hop count • PROMPT [2]: Delay aware routing and robust MAC • MAC collaboration for heterogeneous networks [1] Z. Niu, W. Yao, Q. Ni, and Y. Song, “Study on QoS Support in 802.11e-based Multi-hop Vehicular Wireless Ad Hoc Networks,” in IEEE International Conference on Networking, Sensing and Control, pp. 705 –710, 2007. [2] B. Jarupan and E. Ekici, “PROMPT: A cross-layer position-based communication protocol for delay-aware vehicular access networks,” Ad Hoc Networks, vol. 8, pp. 489–505, July 2010. 33 Konstantinos Katsaros

34. Cross-Layer Designs (2) • Network layer with transport and Application: Provide different levels of priorities on packets • VTP (Vehicular Transport Protocol) • Optimization of TCP and GPSR with vehicle mobility (adaptive beacon interval) • Network layer with multiple layers • Joint MAC, Network and Transport [1] [1] L. Zhou, B. Zheng, B. Geller, a. Wei, S. Xu, and Y. Li, “Cross-layer rate control, medium access control and routing design in cooperative VANET”, Computer Communications, vol. 31, pp. 2870–2882, July 2008 34 Konstantinos Katsaros

35. Location Services • Flooding based: All nodes host it • Proactive: DREAM • Reactive: LAR, MALM (mobility assisted) • Rendezvous based: Some nodes host it • Quorum: divide node set into two subsets (update and query) • Hashing (according to node ID or location): define server nodes using a hash function • RLSMP (Region-based Location Service Management Protocol) and MG-LSM (Mobile Group Location Service Management) designed for VANETs utilizing mobility information 35 Konstantinos Katsaros