Vehicular Network Applications

1. Vehicular Network Applications • VoIP • Web • Email • Cab scheduling • Congestion detection • Vehicle platooning • Road hazard warning • Collision alert • Stoplight assistant • Toll collection • Deceleration warning • Emergency vehicle warning • Border clearance • Traction updates • Flat tire warning • Merge assistance

2. Congestion Detection • Vehicles detect congestion when: • # Vehicles > Threshold 1 • Speed < Threshold 2 • Relay congestion information • Hop-by-hop message forwarding • Other vehicles can choose alternate routes

3. Deceleration Warning • Prevent pile-ups when a vehicle decelerates rapidly

4. Wireless Technologies for Vehicular Networks • Cellular networks • High coverage, low bandwidth, expensive • WiFi networks • Moderate coverage, high bandwidth, free • Combine all of them to achieve low cost, high bandwidth, and high coverage

5. InteractiveWiFi Connectivity from Moving Vehicles Aruna Balasubramanian, Ratul Mahajan Arun Venkataramani, Brian N Levine, John Zahorjan University of Massachusetts Amherst Microsoft Research University of Washington

6. Target Scenarios • A car is within the range of multiple APs • How common? • Low data rate but low delay • Alternatives?

7. Overview Given enough coverage, can WiFi technology be used to access mainstream applications from vehicles? • Existing work shows • the feasibility of WiFi access at vehicular speeds • focus on non-interactive applications. e.g., road monitoring Internet

8. Outline • Can popular applications be supported using vehicular WiFi today? • Performance is poor due to frequent disruptions • How can we improve application performance? • ViFi, a new handoff protocol that significantly reduces disruptions • Does ViFi really improve application performance? • VoIP, short TCP transfers

9. VanLAN: Vehicular Testbed Uses MS campus vans Base stations(BSes) are deployed on roadside buildings Currently 2 vans, 11 BSes

10. Measurement study • Study application performance in vehicular WiFi setting • Focus on basic connectivity • Study performance of different handoff policies • Trace-driven analysis • Nodes send periodic packets and log receptions

11. Handoff policies studied • Practical hard handoff • Associate with one BS • Current 802.11 • Ideal hard handoff • Use future knowledge • Impractical

12. Handoff policies studied • Practical hard handoff • Associate with one BS • Current 802.11 • Ideal hard handoff • Use future knowledge • Impractical • Ideal soft handoff • Use all BSes in range • Performance upper bound

13. Comparison of handoff policies Disruption • Summary • Performance of interactive applications poor when using existing handoff policies • Soft handoff policy can decrease disruptions and improve performance of interactive applications Practical hard handoff Ideal hard handoff Ideal soft handoff

14. Outline • Can popular applications be accessed using vehicular WiFi? • How can we improve application performance? • ViFi, a practical diversity-based handoff protocol • Does ViFi really improve application performance? • VoIP, short TCP transfers

15. Design a practical soft handoff policy • Goal: Leverage multiple BSes in range • How often do we have multiple BSes? • Not straightforward • Constraints in Vehicular WiFi • 1. Inter-BS backplane often bandwidth-constrained • 2. Interactive applications require timely delivery • 3. Fine-grained scheduling of packets difficult Internet

16. Why are existing solutions inadequate? • Opportunistic protocols for WiFi mesh (ExOR, MORE) • Uses batching: Not suitable for interactive applications • Path diversity protocols for enterprise WLANs (Divert) • Assumes BSes are connected through a high speed back plane • Soft handoff protocols for cellular (CDMA-based) • Packet scheduling at fine time scales • Signals can be combined

17. ViFi protocol set up • Vehicle chooses anchor BS • Anchor responsible for vehicle’s packets • Vehicle chooses a set of BSes in range to be auxiliaries • e.g., B, C and D can be chosen as auxiliaries • ViFi leverages packets overheard by the auxiliary A Internet B C D

18. ViFi protocol • Source transmits a packet • If destination receives, it transmits an ack • If auxiliary overhears packet but not ack, it probabilistically relays to destination • If destination received relay, it transmits an ack • If no ack within retransmission interval, source retransmits Source Dest Downstream: Anchor to vehicle A A Dest B B D C D Source C Upstream: Vehicle to anchor

19. Why relaying is effective?

20. Why relaying is effective? • Losses are bursty • Independence • Losses from different senders independent • Losses at different receivers independent A A Upstream B B Downstream D C C D 20

21. Guidelines for probability computation 1. Make a collective relaying decision and limit the total number of relays 2. Give preference to auxiliary with good connectivity with destination • How to make a collective decision without per-packet coordination overhead?

22. Determine the relaying probability Goal: Compute relaying probability RB of auxiliary B Step 1: The probability that auxiliary B is considering relaying • CB = P(B heard the packet) . P(B did not hear ack) Step 2: The expected number of relays by B is • E(B) = CB¢RB Step 3: Formulate ViFi probability equation,  E(x) = 1 • to solve uniquely, set RB proportional to P(destination hears B) Step 4: B estimates P(auxiliary considering relaying) and P(destination heard auxiliary) for each auxiliary • ViFi: Practical soft handoff protocol uses probabilistic relaying for coordination without per-packet coordination cost

23. ViFi Implementation • Implemented ViFi in windows operating system • Use broadcast transmission at the MAC layer • No rate adaptation • Deployed ViFi on VanLAN BSes and vehicles

24. Outline • Can popular applications be accessed using vehicular WiFi? • Due to frequent disruptions, performance is poor • How can we improve application performance? • ViFi, a practical diversity-based soft handoff protocol • Does ViFi really improve application performance?

25. Evaluation • Evaluation based on VanLAN deployment • ViFi reduces disruptions • ViFi improves application performance • ViFi’s probabilistic relaying is efficient • Also in the paper: Trace-driven evaluation on DieselNet testbed at UMass, Amherst • Results qualitatively consistent

26. ViFi reduces disruptions in our deployment ViFi Practical hard handoff

27. ViFi improves VoIP performance • Use G.729 codec > 100% ViFi seconds Practical hard handoff Length of voice call before disruption Disruption = When mean opinion score (mos) is lower than a threshold

28. ViFi improves performance of short TCP transfers • Workload: repeatedly download/upload 10KB files > 50% > 100% ViFi Practical hard handoff Number of transfers before disruption Median transfer time (sec) Disruption = lack of progress for 10 seconds

29. ViFi uses medium efficiently • Efficiency: Number of unique packets delivered/ Number of packets sent • It’s efficient for their testbed, but may not be the case in general. Why? efficiency ViFi Practical hard handoff

30. Conclusions • Improves performance of interactive applications for vehicular WiFi networks • Interactive applications perform poorly in vehicular settings due to frequent disruptions • ViFi, a diversity-based handoff protocol significantly reduces disruptions • Experiments on VanLAN shows that ViFi significantly improves performance of VoIP and short TCP transfers

31. Comments • Interesting problem domain • Target low-bandwidth applications, for which cellular networks are sufficient • Have multiple APs within range tuned into the same channel • May not be common and lose spatial diversity • Use the lowest data rate • Common to have multiple or fewer than 1 relay(s) for each tx • Relay is not compelling • Uplink: sufficient to relay data to one AP • Downlink: if best AP is selected, the need for relay is low • If relay has to be used, MORE like opportunistic routing may be more efficient • They dismissed opportunistic routing due to its potential large delay due to batch • But their delay can be high since retx timeout is generally large in order to account for variable contention delay

32. Modulation Rate Adaptation in Vehicular Environments:Cross-Layer Implementation and Experimental Evaluation Joseph Camp Edward Knightly ACM MobiCom 2008

33. Background: Link Characteristics • Time-varying link quality – Mobility of sender, receiver, or obstacles - Multiple paths existing • Ideal modulation rate for channel condition • Modulation rate with highest throughputfor channel condition Ideal Rate

34. Goal of Protocol Designer • Use available information (loss, SNR, …) to track ideal modulation rate • Many protocols have been invented • ARF, RBAR, OAR, RRAA, CARA, ONOE, … Rate selection Protocol Rate Choice SNR Loss Real System Ground Truth

35. Problem • Existing rate adaptation algorithms failto track the ideal rate – Urban propagation environment – Even with non-mobile sender and receiver– Result = loss and under-utilization Ideal Rate Selected Rate

36. Objective • Understand the origins of the failure to track link variation • Identify core mechanisms needed to succeed in urban channels

37. Methodology • Unified Implementation Platform – Implement multiple algorithms on a common platform – First implementation of SNR-based protocols • Extract General Rate Adaptation Principles • Evaluate rate selection accuracy packet-by-packet • Compare against ideal rate found via exhaustive search • Use repeatable controlled channels • Accurately measured outdoor channels • Design core mechanisms to track real-world link variation

38. Wireless Open-Access Research Platform (WARP) • Limits of Off-the-shelf platforms – Programmability and observability • WARP is clean-slate MAC and PHYneeded to implement: – CSMA/CA (802.11-like MAC) • Cross-layer rate adaptation framework – Core mechanisms for rate selection protocols – Channel measurements – Evaluation of selected rate versus ideal rate Virtex-II Pro FPGA

39. Rate Adaptation Schemes Studied • Consecutive packet decision • 10 success  increase rate • 2 failures  decrease rate • Historical decision • Compute pkt loss rate using a window and select the rate that gives the highest throughput • SNR based • RTS/CTS/DATA/ACK, where CTS reports channel quality • Equal air-time assuration • Measure SNR per data packet • Opportunistic better channel • Send back-to-back pkts (without backoff) whenever the rate is above the base rate • Is it a good idea?

40. Rate Adaptation Accuracy • Ideal rate found via exhaustive search of channel condition • Consider case where at least one modulation rate succeeds • Rate Selection Accuracy Categories • Over-selection (loss) • Accurate (achieving optimal rate) • Under-selection (under-utilization)

41. Experimental Design • Repeatable channels – Mean channel quality – Channel fading/coherence time – Multipath effect and interference • Accurately measure urban channels – Residential and downtown scenarios – Measure coherence time – Static and vehicular Topologies • Competing links (in paper) – Indoor, controlled environment – Urban environment

42. Impact of Coherence Time • Issue: Increase fading of the channel to evaluate if rate adaptation can track • Similar performance with long coherence of channel • SNR: high overhead penalty (contrasts result of protocol designer) • Opportunistic: overcomes RTS/CTS overhead penalty • Dissimilar performance at short coherence of channel High Mean Channel Quality (-45 dBm), Single Rayleigh Fading Channel

43. Opposite Rate Choice Inaccuracies • Issue: Packet-by-packet accuracy to reveal why throughput is low • Average vs. consecutive mechanisms – Consecutive low due to underselection • SNR: extremely low throughput – Due to overselection (loss) • Per-packet analysis needed to show poor rate adaptation behavior

44. SNR-based Coherence Time Sensitivity • Issue: SNR rate selection is per-packet (should track fading), why inaccurate? • Fast to slow channel fading • Accurate at long coherence • Overselect at <1ms • Overselection caused by coherence time sensitivity of SNR-rate relationship

45. Joint Consideration of SNR andCoherence Time • Consider different SNR thresholds according to coherence time • Ideal rate = f(SNR, CT) SNR Coherence Time

46. Joint Consideration of SNR andCoherence Time • Consider different SNR thresholds according to coherence time • Ideal rate = f(SNR, CT) • Retrain SNR-based decision (for the same protocol) • Joint consideration of SNR and coherence time provides large gains

47. Scenarios and Channel Measurements • Residential Urban (TFA) • Single-family residential, dense foliage • Coherence Time: 100 ms on average • Driven to 15 ms with mobility of scatterers (in static topology) • Downtown Houston • Both sides of street lined with tall buildings (strong multipath) • Coherence Time: 80 ms on average • Driven to 300 usec with mobility of scatterers (in static topology)

48. Outdoor Static Topologies • Issue: Evaluate rate adaptation accuracy in outdoor scenarios • Consecutive and average: inaccurate in outdoor settings • Downtown (strong multipath) • Force loss-based to underselect • SNR: over and underselect with low coherence time

49. Static Sender to Mobile Receiver (Urban) • Issue: Evaluate rate adaptation ability to track with mobility • SNR protocols are able to plateau for >4 sec • Per-packet decision • Loss-based protocols only able to spike to suboptimal rate choices • Loss sensitivity prevents protocol from tracking • Loss-based protocols unable to track with mobility

50. Heterogeneous Competing Links • Lack of loss distinction • Causes underselection • Collision/fading differentiation able to overcome with equal links • Large imbalances for slight differences in competing links • Residential Urban Scenario • Competing links with vehicular mobility