1. Opportunistic Off-Path Content Discovery in Information-Centric Networks
Notes
Onur Ascigil, Vasilis Sourlas, Ioannis Psaras, and George Pavlou
Department of Electronic and Electrical Engineering,
University College London, UK

2. Outline Content discovery in Information-centric Networks (ICN)
Opportunistic Content Discovery
Evaluation
Future Work & Conclusions

3. Content Discovery in ICN

4. Content Discovery in ICN: ICN Features
Information-centric Networking (ICN) features
Naming of content
e.g., /ucl/ee/onur/lanman_presentation2016.ppt
Network Storage
Ubiquitous caching
Stateful Forwarding
Request (i.e, Interest) leaves breadcrumbs, which the data follows
Routing on names:
Mostly focused on locating the content on-path, at origin or a designated cache
Disclaimer: ignoring scalability issues in this talk
Goal: integrate content delivery as a native network feature
Is it achieved?
Content can be transparently delivered from any cache enabled node or router. Routing and forwarding are based on content names.

5. Content Discovery in ICN
Find a nearby (ideally nearest!) copy of the content
Difficult to achieve without significant ``overhead’’ in practice
Why?
Volatile nature of content in the caches:
Contents of caches may change at very short time-scales
Request-to-cache routing
Mostly focused on routing requests to the content origin
Search content on-path (i.e., along the shortest or default path)
Existing Solutions for Content Discovery:
Opportunistic on-path
Coordinated off-path

6. Content Discovery in ICN: Request Routing
Opportunistic on-path: limited gain
Caching: Content is cached on-path as it travels to the user from the content origin
Request routing: Route requests to content origin & retrieve content opportunistically from on-path caches
E.g., Barebones NDN
with default forwarding strategy
Coordinated off-path: coordination and communication overhead
Caching: content is assigned to off-path caches according to predefined rules
Request routing: adheres to the same rules in order to retrieve contents from caches in a coordinated manner
E.g., Hash routing:
a hash function determines both the placement of content and routing of requests by mapping content identifiers to cache nodes
E.g., Coordinate content placement and routing with the control plane:
advertise cache contents in the control plane and direct requests to caches

7. Opportunistic Content Discovery

8. Opportunistic Content Discovery
Stateful forwarding of data packets: data packets leave breadcrumbs
Downstream FIB table (D-FIB)
FIB
Prefix
Next-hop
/facebook T
D-FIB
D-FIB R
Name
Next-hop
/…./x.mpg S
Name
Next-hop
/…./x.mpg T
Data: … H2 T U
Request:
/facebook/user/x.mpg
Request:
/facebook/user/x.mpg
Request:
/facebook/user/x.mpg
Upstream & downstream. Store state to keep track of the direction (i.e., next hop) in which the Data packets were sent in the past. Multiple copies of the data …
Request:
/facebook/user/x.mpg
Request:
/facebook/user/x.mpg
Request:
/facebook/user/x.mpg
FIB S
Prefix
Next-hop
/facebook U
FIB
Prefix
Next-hop
/facebook T H1

9. Opportunistic Content Discovery: Downstream FIB Table
Caches trails of data packets towards users
LRU policy
An exact match table

10. Opportunistic Content Discovery: Routing using D-FIB & FIB
Goal:
improve cache hits
Reduce latency in obtaining content
limit overhead and reduce the number of requests reaching the content origin
Each request is associated with a Total Forwarding Counter (TFC) value
spend it on sending a copy of a request downstream
spend it on following the FIB table towards the content origin (upstream)
spend it on both (multicast)
TFC is initially set by the access router
New Forwarding Strategies based on D-FIB
Determines how TFC quota is spent at each router

11. Opportunistic Content Discovery: Downstream FIB Table
Multicast requests using FIB and D-FIB Z Q L
Name
Next-hop
/x/y/z
Q, Y
FIB
Prefix
Next-hop
Distance /x S 4
Request: /x/y/z
Off-path T R S
Request: /x/y/z
Quota = 4
Request: /x/y/z
Off-path
Once a request is forwarded downstream, it only follows the D-FIB tables. They don’t travel back towards the content origin, following the FIB table N
Request: /x/y/z
Quota = 4 + 3
Request: /x/y/z
Quota = 3
Request: /x/y/z K Y M

12. Opportunistic Content Discovery: Forwarding Strategies
Check Content Store, if no matching content, then:
Lookup FIB and D-FIB
If D-FIB returns no entries, follow FIB (forward upstream)
If D-FIB returns one or more entries, then the forwarding strategy decides what action to perform
Two simple strategies:
ALL strategy: Send a copy of the request to all the next-hops in the D-FIB entry
the cache is closer (number of hops) than the content origin
ONE strategy: Send a copy of the request to only one next-hop in the D-FIB entry
Freshest entry which is closer than the content origin

13. Performance Evaluation

14. Evaluation
Implemented our approach in ndnSIM — an ns-3 based simulator
Performance metrics:
Cache hit ratio: percentage of the interests that have been satisfied
Off-path/on-path
The minimum hop distance: number of hops traveled by the (first) data arriving at the user from a responding router or the content origin for each successful request
The mean traffic overhead: the mean number of hops that the initiated Data packets travel in the network
Variables:
Cache size at each node
D-FIB size w.r.t. content population size
Initial Quota

15. Evaluation: Scenario Using a RocketFuel topology: AS 4755 VSNL (India)
191 nodes: 148 edge, 39 gateway, and 4 backbone routers
242 bi-directional links
Request rate: 100 requests/sec
Randomly select an edge router
Content Population: 10,000
One chunk per item
One content server
attached to a randomly chosen edge router
our results comparing performance of on-path/off-path is best-case scenario
Popularity of the items determined by a Zipf law of exponents
Zipf parameter z: 0.7
Quota: Shortest path length + 3
Duration: 1 hour (following an hour of warm-up phase)

16. Evaluation: Impact of Router’s Cache Size
Impact of D-FIB size w.r.t. content population on the performance

17. Evaluation: Impact of Router’s Cache Size
Hop distance is slightly better with ALL strategy

18. Evaluation: Impact of Router’s Cache Size
Overhead difference is negligible between ALL and ONE

19. Evaluation: Impact of D-FIB size

20. Evaluation: Impact of Initial Quota

21. Evaluation: Impact of Initial Quota
What percentage of the first requests manage to fetch the content?

22. Future Work Augment the strategies with additional information
Thresholds for freshness of state in the D-FIB
On-path (i.e., upstream) hints to steer requests along a particular (fresh) downstream trail along the path to the content origin. L T S Z
Data: /x/y/z …
Name
Next-hop
Age
Distance
x/y/z K
T sec. 2 N Y K M

23. Conclusions
Opportunistic scheme to discover content using two simple yet effective strategies
Reduces load on the content origin
Improves cache hits
Adds little overhead
Basic framework with opportunities to augment with more sophisticated forwarding strategies

24. Thank you for listening! Questions?

25. Backup slides

26. Zipf Distribution
Requests are generated in the network with rate r = {r1,...,rM}, where rm denotes the aggregate incoming request rate (in requests per second) for content item m 2 M. The request rate for each item is determined by its popularity. Here we approximate the popularity of the items by a Zipf law of exponents z [20]. In that way the aggregate incoming request rate (in requests per second) for an information item m 2 M is given by: rm=z· 1/kz ,