1. Dissertation Proposal Aruna Balasubramanian Department of Computer Science, University of Massachusetts, Amherst Architecting Protocols To Enable Mobile Application in Wireless Networks

2. Vision: Universal network access Mostly connected Intermittently connected Mostly disconnected 2 Traditional wireless network protocols are not well-suited for disruption-prone environments

3. Thesis goal Understanding the principles underlying the design and implementation of a robust protocol stack to enable mobile applications in heterogeneous network environments. 3

4. Research questions 1.What are the challenges in the diverse network environments taken in isolation? 1.How can we design decentralized mechanisms and algorithms to overcome challenges in each environment? 1.How can the algorithms adapt as a user moves between different environments? 4

5. Diverse network environments Email, bulk transfer Web search, Web browsing VoIP 5

6. Evaluation methodology  Deployment DieseNet, VanLAN  Trace-driven simulations Traces collected from testbeds  Analysis Competitive analysis, Linear Programming and Modeling 6 VanLAN DieselNet

7. Roadmap  Fundamental challenge: Tolerating disruption under uncertainty 7  Mechanism: Opportunistic resource usage  Replication  Aggressive Prefetching  Opportunistic forwarding  Decentralized algorithm: Utility-driven prioritization  Packet prioritization  Information prioritization  Sender prioritization  Proposed work: Adapt as a user moves to different network environments or has access to multiple networks

8. Disruptions  Mobile wireless networks are disruption prone  Coverage holes  Mobility  Channel fading  …  Disruption results in a unique challenge in each environment  Tolerating disruptions challenging because of uncertain network conditions 8

9. Mostly disconnected networks No connectivity to infrastructure Uncertain network conditions i i i 9

10. Intermittently connected networks Frequent disruptions due to coverage holes 10 Internet

11. Mostly connected networks Packet level disruptions occur even when the mobile node is in range of an AP 11

12. Roadmap  Fundamental challenge: Tolerating disruption under uncertainty 12  Mechanism: Opportunistic resource usage  Replication  Aggressive Prefetching  Opportunistic forwarding  Decentralized algorithm: Utility-driven prioritization  Packet prioritization  Information prioritization  Sender prioritization  Proposed work: Adapt as a user moves to different network environments or has access to multiple networks

13. RAPID: Replication to improve performance of disruption tolerant applications [Sigcomm 07] Mostly connected Intermittently connected Mostly disconnected 13

14. Why replication?  Find paths under uncertainty 14 i i i ii i

15. How to replicate under resource constraints?  Existing replication-based DTN routing protocols Use a maximum replication count Replicate to nodes with better delivery probability … Metrics desired in practice Minimize average delay Maximize packets meeting their deadlines … Incidental Routing Effect of mechanism on routing metric unclear Idea: Translate desired metrics to per packet utilities and replicate packets to intentionally improve utility 15

16. Utilities  Utility: expected contribution of packet to the metric. For example Minimize average delay, U(i) = negative expected delay of i  What is the improvement in utility by replicating a packet If expected meeting times are exponentially distributed with mean λ Expected delay of a packet is λ Replicating the packet will reduce delay to λ/2  Use these utilities to design RAPID Resource Allocation Protocol for Intentional DTN Routing 16

17. RAPID Protocol: Utility driven prioritization RAPID Protocol (X,Y): 1. Control channel: Exchange metadata 2. Direct Delivery: Deliver packets destined to each other 3. Replication: Replicate by prioritizing in decreasing order of marginal utility 4. Termination: Until all packets replicated or nodes out of range YX Change in utility Packet size 17

18. A case for a heuristic solution  Problem: Given a set of transfer opportunities and packet workload, what allocation of packets will minimize delay?  With complete knowledge of workload and transfer opportunities  Solving the DTN routing problem is NP Hard  With only knowledge of workload or transfer opportunities  An online DTN routing problem can be arbitrarily far from an offline adversary 18

19. Deployment on DieselNet Deployed RAPID on DieselNet for 58 days and validated simulator results with deployment results 19

20. Trace-driven simulation results 20

21. Roadmap  Fundamental challenge: Tolerating disruption under uncertainty 21  Mechanism: Opportunistic resource usage  Replication  Aggressive Prefetching  Opportunistic forwarding  Decentralized algorithm: Utility-driven prioritization  Packet prioritization  Information prioritization  Sender prioritization  Proposed work: Adapt as a user moves to different network environments or has access to multiple networks

22. Thedu: Prefetching to improve web search performance [Mobicom 08, Chants 07] Mostly connected Intermittently connected Mostly disconnected 22

23. Web search challenge 23 Retrieving….

24. Prefetching and utility-driven prioritization Internet Prefetch web pages Developed two information retrieval techniques to prioritize web pages so that the most useful web pages are downloaded Web queries Web responses Google, Yahoo, Live, Ask, …. Google, Yahoo, Live, Ask, …. 24

25. Deployment and results  Deployed Thedu on DieselNet  Results from one week deployment The number of useful web pages delivered to the user using Thedu is 4 times greater than an existing protocol 25

26. Roadmap  Fundamental challenge: Tolerating disruption under uncertainty 26  Mechanism: Opportunistic resource usage  Replication  Aggressive Prefetching  Opportunistic forwarding  Decentralized algorithm: Utility-driven prioritization  Packet prioritization  Information prioritization  Sender prioritization  Proposed work: Adapt as a user moves to different network environments or has access to multiple networks

27. ViFi: Opportunistic forwarding to improve performance of interactive applications Mostly connected Intermittently connected Mostly disconnected 27

28. Opportunistic forwarding  Tolerate packet-level disruptions Internet  Problem: Coordinating among APs to forward the packet 28

29. Probabilistic coordination Guidelines 1.Redundant relays should be minimized 2.The intended next hop should receive the packet with high probability 3.Should avoid per-packet coordination Solution: APs relay an overheard packet probabilistically, such that the guidelines are satisfied 29

30. ViFi deployment and results  Deployed ViFi on VanLAN BSes and vehicles  Currently 2 vans, 11 Bses  2 months deployment  Deployment results  ViFi doubled the duration of a VoIP call compared to 802.11 by improving packet reception

31. Roadmap  Fundamental challenge: Tolerating disruption under uncertainty 31  Mechanism: Opportunistic resource usage  Replication  Aggressive Prefetching  Opportunistic forwarding  Decentralized algorithm: Utility-driven prioritization  Packet prioritization  Information prioritization  Sender prioritization  Proposed work: Adapt as a user moves to different network environments or has access to multiple networks

32. Proposed work  Adapting to different networks  Leveraging simultaneous access to multiple networks  Designing a self adapting protocol stack 32

33. Adapting to changing network environment ReplicationAggressive prefetching Opportunistic forwarding 33

34. Adapt replication to diverse network environments 34 Mostly connected networks Mostly disconnected networks Replication improves performance Does replication improve performance?

35. When is replication useful?  Hypothesis: Replication is useful when (1) delay estimates have high variance and (2) metric is delay 35

36. Experimentally validating hypothesis  Mesh testbed at UMass – increase uncertainty by removing/delaying links  DTN DieselNet testbed – decrease uncertainty using bus schedules 36

37. How should packets be replicated?  RAPID cannot be used as is In our DTN model, transfer opportunities occur one after the other In other environments, node can have simultaneous transfer opportunities  Adapting RAPID for mostly connected networks Which node to replicate to? How to take interference into account? Can we exploit opportunistic forwarding? 37

38. Proposed work  Adapting to diverse networks  Leveraging simultaneous access to multiple networks  Self adapting protocol stack 38

39. Simultaneous access  If a node has both 3G and WiFi access 3G networks have limited capacity Opportunistic WiFi access can be used to augment 3G capacity 39 Research problem Empirically quantify the connectivity and throughput of a WiFi network, to determine the extent of augmentation

40. Why quantify the connectivity and throughput?  Opportunity: WiFi can be used, to send background traffic, such as prefetched web responses to aggregate available bandwidth to send data to send forward error correction bits and reduce losses …  Challenge: WiFi networks are disruption prone and unpredictable  Approach: Quantifying will help determine how to use WiFi access 40

41. Empirical quantification  Given a network, what is the average connectivity and throughput that can be supported? Connectivity – Fraction of times the source can connect to the destination Throughput – Total traffic that can be sent between a source and destination  Challenge: Connectivity and throughput of a network depends on the network protocols  Example: A routing protocol can provide close to optimal connectivity in one network, but perform poorly in another 41

42. Performance of routing on different traces  Three network traces – DieselNet, Muni San Francisco bus network, ETH traffic simulator  Three routing policies: Optimal, AODV, and GPSR 42

43. Proposed methodology: Measurement and Analysis  Understand how network characteristics affect protocols What network characteristics affect performance of a routing policy? How does the wireless range affect connectivity of a network?  How should opportunistic WiFi be used to augment 3G networks? 43

44. Proposed work  Adapting to diverse networks  Leveraging simultaneous access to multiple networks  Self adapting protocol stack 44

45. What are the protocol layers?  Traditional wireless stack not well-suited for disruption-prone networks Link layer: 802.11 Routing using contemporaneous path: MANET, Mesh End-to-End transport: TCP, UDP Traditional Wireless stack 45 Link Routing Transport Application Forwarding Supporting applications under disruptions Opportunistic forwarding Replication based Hop-by-Hop transport Prefetching DTN 2

46. Interface design 802.11, Opportunistic forwarding Routing Link Pre- fetching Application Estimate environment 46 Research questions  What information is exchanged between layers?  What environment estimates are needed for the protocol layers to be self adapting? End-to- End, Hop- by-Hop Forwarding Contempor aneous, Replication DTN 2 TCP

47. Timeline  Measurement, Design, Implementation and Evaluation  Adapting replication – 5 months  Leveraging simultaneous access – 5 months  Self adapting protocol stack – 2 months  Writing – 2 months 47

48. Conclusions  The vision is to provide universal network access  Proposed three algorithms to tolerate disruptions and enable applications RAPID -- mostly disconnected Thedu -- intermittently connected ViFi -- mostly connected networks  Proposed a protocol stack that adapts to changing network conditions 48

49. Using backpressure algorithms for routing in uncertain networks  No contemporaneous end-to-end path  Send packets to a peer, if the peer has a smaller queue to the destination  Algorithm is throughput optimal  Can backpressure be adapted for minimizing delays? 49

50. How does wireless range affect connectivity?  Should we use smaller number of long hops, or larger number of short hops  Short hops Higher throughput Lower SNR  Long hops Routing overhead Path instability 50

51. Availability of WiFi vs 3G on DieselNet 75% of grids that have 3G connectivity, also has WiFi connectivity 51

52. Why WiFi?  Urban areas -Cheaper alternative -Can augment capacity of existing technologies  Rural areas -Easy and cheap to deploy -The deployment can grow organically  Operates in the unlicensed spectrum, higher peak bandwidth, does not need expensive infrastructure 52 Today’s WiFi protocols are not well suited to enable applications for mobile users

53. Completed work Understand challenges + Design mechanisms and algorithms = Sigcomm 08 Sigcomm 07 Chants 07, Mobicom 08 53 Routing protocol for delay tolerant applications Application layer protocol for web applications Link layer protocol for interactive applications

54. Related work: Prefetching  Prefetching has been used To improve availability in file systems [Coda91, Chandra01] To improve performance of the web in wired networks, when the Internet was slow [Google Accelerator, Jiang98] In an email-based web browser [TEK]  Resource allocation was not the challenge in these environments 54

55. Related work: Opportunistic forwarding Opportunistic protocols for WiFi mesh (ExOR, MORE) Uses batching: Not suitable for interactive applications Path diversity protocols for enterprise WLANs (Divert ) Assumes APs 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 55