1. AdTorrent: Delivering Location Cognizant Advertisements to Car Networks WONS 2006 Jan 2006, Les Menuires, France
Dr. Alok Nandan
Dr. Shirshanka Das
Saurabh Tewari
Dr. Mario Gerla
Dr. Leonard Klienrock

2. Design Space Communication Scenarios Applications
Cellular, Ad-Hoc Network Hybrid
Two-Three hop wireless extension to Infrastructure
802.11s Mesh Networks
Applications
Content Delivery
Centralized
P2P
Hybrid
Security/Road Safety
Cooperative Collision Warning/Avoidance
Payment: Parking Lot, Drive Thru, Toll.
Multiplayer Games?
11/20/2018
Thesis Defense Talk

3. CarTorrent: Basic Idea
Internet
Download a piece
Outside Range of Gateway
Transferring Piece of File from Gateway
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Thesis Defense Talk

4. Co-operative Download
Internet
Vehicle-Vehicle Communication
Exchanging Pieces of File Later
11/20/2018
Thesis Defense Talk

5. Service Capacity Model
Transient Phase: The number of servers in the P2P system grows exponentially and throughput seen by peers improves.
Who cares about transient phase?
Steady State: The number of servers become large enough to service the intensity of requests, the system enters the steady state.
Definition: Service Capacity in the transient regime can be defined as the Average Delay/Throughput performance as seen by a typical peer.
Capacity = File size/download time (we assume entire file is downloaded before the next WiFi access point
Again, why bother with transient?
11/20/2018
Thesis Defense Talk

6. Analytical Model n
Developed some models that demonstrate the efficacy of swarming for capacity constrained wireless networks √n
log n
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Thesis Defense Talk

7. Summary
We presented a P2P content delivery application for Vehicular Wireless Networks
Analytical bounds of cooperative download in wireless ad hoc networks.
As I recall, quite loose (too loose to be of practical value?)
Fundamental limitation of scale due to underlying capacity of wireless networks
Evaluated using simulation of various Content Selection and content Dissemination strategies.
Gossip incorporates location awareness into Peer Discovery and Selection and has low overhead.
11/20/2018
Thesis Defense Talk

8. Digital Billboard
Gateway disseminates Ads that are relevant to the proximity of the Gateway
Simple text-based Ads, previews of nearby movies, virtual tours of hotels.
Business owners in the vicinity subscribe to this digital billboard service for a fee.
Need a location-aware distributed application to search, rank and deliver content to the end-user (the vehicle)
11/20/2018
Thesis Defense Talk

9. AdTorrent : Search and Content Delivery
How is it different from CarTorrent?
Push model for data dissemination as opposed to pull in CarTorrent
More precisely, in Ad Torrent ALL nodes push the keywords; each node in turns pulls (via query) the keywords it needs
In Car Torrent, the members both pull new pieces (with the query) and push (their own pieces) at the same time
Search for relevant content in the vehicular network
Keyword Set Indexing for communication efficient search
Search query dissemination optimized for vehicular networks
Models for evaluating impact of search query hit w.r.t. Scope of epidemic query dissemination and of epidemic keyword dissemination..
These models are mostly of academic interest
11/20/2018
Thesis Defense Talk

10. The Ad Torrent architecture
2 - phase process
Phase 1: Server agents disseminate the keywords
Phase 2: Client submit query
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Thesis Defense Talk

11. Keyword Set Indexing note: it seems this is just an example of Keyword aggregate?
URL of Data
MetaData
Hash(AB)
Size = 10MB
Hash(BC)
Genre= 0xAB
Hash(AC) -
Hash(CD)
A, B, C and D are individual keywords
Why is it communication efficient?
Performs Remote “AND’ing” of index entries
11/20/2018
Thesis Defense Talk

12. Protocol Steps
Gateway “pushes” Ads continually to utilize unused bandwidth
search (“A B C”)
num_local_entries = lookup_local_index (hash(AB), hash(BC), hash(AC))
if (num_local_entries > k1) goto LookupDone
else /* found < k1 entries in 1 hop neighborhood */
num_remote_entries = scoped_flood( hash(XY) ,m)
/* XY Є AB,BC,AC , m is the scope of the flood */
After T1 seconds timeout.
LookupDone:
Now have k1 entries from local and/or remote indices
send_udp_ctrl( hash(XY), -> MetaData )
torrent_ranking ( MetaData, Params)
swarm(TorrentID)
11/20/2018
Thesis Defense Talk

13. Query Dissemination and Lookup
Each “client” agent searches own local cache for Ads/Torrents requests to submit (actually, the corresponding keywords)
Scoped flood
Scoping level is a critical design parameter
Tradeoff between reliability and communication overhead (naturally, but, not a big deal, can omit mention)
Bloom Filter of cached index entries exchanged
Actually, the Bloom Filters are disseminated by the Server Agents
This concept MUST be expanded; one of the key enablers of ad torrent!!!!
Finally, when the query propagation and response is done, the querying node has a list of index entries that match.
11/20/2018
Thesis Defense Talk

14. Torrent Ranking Algorithm
Which torrent/ads to pick if multiple query hits?
Proximity
Maximum number of pieces
“Stability” of neighbors
Relevance of keywords to MetaData queried
Add a few more things here….
11/20/2018
Thesis Defense Talk

15. Protocol Features
Keyword Set Indexing to reduce Communication Overhead
Epidemic Scoped Query Data Dissemination – optimized for vehicular ad hoc setting
Torrent Ranking Algorithm based on proximity
BitTorrent-like “Swarming” in actual content delivery
Mechanisms to discourage Selfishness
11/20/2018
Thesis Defense Talk

16. Simulation Environment
Implemented our protocol in Qualnet at the Application Layer
TCP, a MAC + ARF disabled, with longer radio transmission range.
Fading model was Rayleigh.
Mobility Model – Real Geographic map of LA.
Group Mobility Model
Routing- AODV
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Thesis Defense Talk

17. Simulation Results
/1000m2
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Thesis Defense Talk

18. Modeling Approach
What is the impact of scope of epidemic dissemination on query hit rates?
Model the network of caches, from the perspective of a single file i
LRU-managed caches
Model Local requests
Model Remote requests
r(i,j,k) : Rate at which file i is pushed from position j to j+1 when the hop limit for query flooding is k.
i = file id, k = Number of hops, B = cache size
11/20/2018
Thesis Defense Talk

19. Computing Push Down Rate, r(i,j,k)
plocal(i,j,k) ≈ r(i,j,k)/ΣNi=1 r(i,j,k)
Conservation of Flow Principle
Push Down Rate for file i from position j to j+1 = Rate of bringing file i to Top j positions
Use this to compute r(i,j,k)
File i brought into top j position
(1) LOCAL request for file i when it is not in top j
(a) From j+1 …B
(b) Or Remote
(2) REMOTE request for file i from j+1..B positions
11/20/2018
Thesis Defense Talk

20. Computing Overall Hit Rate
r(i,j,k) = rlocal(i,j,k) + (M(k) – 1) rremote(i,j,k)/M(k) plocal(i,B,k)
Given plocal(i,B,k) we can compute the hit rate for k-hop neighborhood as follows:
plocal(i,B,k) α B/N and plocal(i,1,k) α λi
p(i,B,k) = [1-(1 -plocal(i,B,k))M(k)] we used M(k) ~ k1.4 and M(k) ~ k2
11/20/2018
Thesis Defense Talk

21. Hop Count Sparse M(k) ~ k1.4
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Thesis Defense Talk

22. Hop Count Dense: M(k) ~ k2
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Thesis Defense Talk

23. Distribution of Optimal Hit Rates for M(k) ~ k2
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Thesis Defense Talk

24. Distribution of Optimal Cache Probability for M(k) ~ k2
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Thesis Defense Talk

25. Effect of Skew in File Request Rates
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Thesis Defense Talk

26. Effect of Spreading Factor
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Thesis Defense Talk

27. Summary
We presented two P2P applications for Vehicular Wireless Networks
Peer Discovery and Torrent Ranking uses proximity
Content Delivery
Push and Pull models
Swarming
Communication efficient search and gossip protocols
System Designers can use our analytical framework to estimate the required cache size and scope of query dissemination based on the user performance requirements
Hop limit of 4 gives an adequate hit rate and the incremental gain of increasing the scope of query dissemination was minimal in the mobility scenarios used.
11/20/2018
Thesis Defense Talk

28. Thanks, Questions?