1. Enhancing Interactive Web Applications in Hybrid Networks (“thedu”)
Authers
Aruna Balasubramanian, Brian Neil Levine, Arun Venkataramani
Department of Computer Science
University of Massachusetts Amherst
{arunab, brian,
Presenting
Ido Barkan, Kfir Damari
Department of Communication System Engineering
Ben Gurion University

2. Mobile Internet Users Options for mobile users: Comparison 3G Wifi
Price (one pay -> monthly)
Availability
“free” connectivity (for workers)

3. Application space

4. Questions
“1) How can we enable system support for interactive web applications to tolerate disruptions in connectivity from mobile nodes?”
“2) Can opportunistic mobile-to-mobile (m2m) transfers enhance application performance over only using APs, and if so, under what conditions and by how much?”

5. You’re sitting in the bus – overhearing two people talking about mobicom

10. Understanding the problem
Many user refresh
Tcp session creation overhead
More then one HTTP request (Springfield)
Bottom line – It will take time!

11. Thedu Goals & Design
Thedu is designed to enable quick and easy access to web search applications from moving vehicles.
Robustness:
Tolerate disruptions (interactive searches need persistent connectivity)
Low-cost deployability:
The system should be low-cost
minimal change to existing infrastructure or software
Extending access:
extend the Internet’s reach to rural or developing regions with limited access points to the internet

12. A few facts about searching
75% of users do not view more than the top 20 web pages
most users are interested in at most 5 results per query
IR - information retrieval (IR) techniques

13. Part 1 – m2i traffic Aggressive prefetching
Prioritization protocol to allocate limited bandwidth to the most useful web pages
Thedu proxy only returns the top few web pages (based on their relevance probability)

14. Aggressive prefetching

15. Prioritization
Query-type classification(homepage, content and service)
Prioritize web pages across different queries - normalization algorithm is based on the Kullback-Liebler divergence and Markov chains

16. relevance probability
We then estimate the relevance probability using Bayes’ rule.
P(score|rel) - denote the probability of score given the document is relevant
P(score|nonrel) the probability of score given the document is not relevant.

17. What about helping others?
Mostly top 5 queries needed

18. Part 2 - M2M ROUTING
m2m routing can leverage other mobile nodes needs.
m2m routing is DTN like. (DTN- delay & disruption tolerant network)
Question. If a mobile node has pending web pages download- should it still download web responses for others???
Apparently- YES. Why?
Most of the utility resides in the first few web pages.

19. Client prioritization
If node Y has a connection to X it is prioritizing pages to it by U(ri)=P(ri)Qx(ri) (page is relevant and will reach X in dead line).
Qx(ri) is estimated statistically (Poisson dist.).
Cache everything you route (popularity, aging).

20. M2M basics Assumptions:
Demand is infinite
Responses are of unit size
Experiment runs for unit time
Trying to compute the m2m benefit (noted G) to system in relation to
Searching for the maximum added m2m BW by searching for the amount of nodes that benefit from it.

21. Conclusion: m2m is beneficial. WHY? (intuition)
Concave utility function. It is better for nodes with good AP reception to download responses for others than downloading their own.
Workload skew- practically some nodes has lower demands from others and they may support other’s demand
m2m routing is only beneficial when mobile nodes meet each other in the same frequency they meet AP.

22. Test cases (from theorem to practice)
Deployment
Trace-Driven Simulation

23. Deployment – What? DieselNet in Amherst MA 40 buses total
~21 buses are on the road
bus is equipped with
linux computer
802.11b radio ,constantly scan for APs&buses
Server-side proxy (Thedu & Stateless)

24. Deployment – How? Why Indri? Some numbers
predefined user queries & data-set
human relevance judgments
assigns a relevance score
Some numbers
Queries per hour: 10 per bus
Deadline: 30 min
queryIDs: allows query repetitions

25. Deployment - results Thedu returned 4.5 times more pages
Number of relevant pages is 4 times larger
Thedu returned at least one relevant page for twice as many queries
With Thudu 90% of the time, a relevant page is received within 5 min
Mean delay receiving first relevant web page is 2.7 min
Mean delay receiving all relevant web pages is 2.3 min

26. Trace-Driven Simulation
Traces were collected from vehicles to:
Study affect of AP density on Thedu.
Evaluate the benefits of m2m routing.
Evaluate the perormance of Thedu for web browsing.
Buses scans for APs and other buses.
AP found- trying to connect.
Bus found- connect till radio is out of range.

27. Trace-Driven Simulation
Buses constantly exchange random data to measure capacity of connection (except when operational AP in range)
Pinging is done to measure connectivity time.
Logging:
m2i: SSID, location, duration.
m2m: bytes transferred
20 days of data logged.

28. Trace-Driven Simulation
Each node simulates queries (Poisson dist.)
Proxy retrieves top 20 web pages.
Compute number of relevant responses.
M2i BW is estimated to 205KBps.
Town was divided to grids

29. m2m routing
151 open AP.
In order to evaluate m2m benefit only 5 AP’s were chosen in random to fulfill a 1:1.3 m2m-to-m2i ratio.
3 variations:
(i) no m2m routing.
(ii) m2m routing.
(iii) routing + caching. Only 20% of queries repeats itself (conservative).

31. Results summary m2i improvement with Thedu dramaticlly m2m benefit
Queries received relevant result with a mean delay of 2.3 minutes (0.55 minutes in areas with high AP density)
m2m benefit
M2M with caching improves the number of relevant responses by up to 58%
But the mean delay is significantly high
Practicality for interactive applications is questionable

32. Consultations
“1) How can we enable system support for interactive web applications to tolerate disruptions in connectivity from mobile nodes?”
Proxy-based architecture (to tolerate disruptions)
Aggressive fetching (to maximize bandwidth utilization)
Smart prioritizing (reduce needed bandwidth)
“2) Can opportunistic mobile-to-mobile (m2m) transfers enhance application performance over only using APs, and if so, under what conditions and by how much?”
Mostly where there aren’t many APs.
Caching improves performance drastically
Result mean delay makes traffic irrelevant for human applications
m2m is not cost-effective in most Urban environments today

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