Cooperative Multimedia Proxy Servers

1. Cooperative Multimedia Proxy Servers Dr.Philip Tse The University of Hong Kong

2. Introduction • Taxonomy • Our design • Simulation results • Summary and Work to continue

3. … … … Cooperative Multimedia Proxy Servers B A objects C Server Storage System Proxy servers A, B, C pass their cached objects to each other

4. Taxonomy of Cooperative Multimedia Proxy Caching • Object partitioning and transformation • Proxy cooperation mechanisms • Proxy cache admission and replacement policies

5. Object Transformation and Partitioning • How to partition or transform objects for caching in the proxy servers? • Partitioning: The leader blocks to reduce response time • Hotspot: The selected hotspot blocks to provide object preview • Staging: The blocks at peak data rates to reduce maximum WAN bandwidth • Segment: Partial object according to popularity • Transcoding: transform to low resolution object to reduce repeated processing time

6. Web Caching Cooperation • Which proxy has the required object part? • Hierarchical tree • Parent proxy cache all objects in its children • Large parent cache • Directory based • Each proxy keeps directory of cache contents in other cooperative proxy • Update overheads • Hash based • Proxy no. = Hash(object) • Reorganize after proxy leaves P C C C

7. Cache Admission/Replacement Policies • Which object parts should be kept in the caches? • LRU removes the least recently accessed objects first. • LFU removes the cold objects first. • LRU-min, GD-size and LUV remove the large and least recently accessed objects first. • Interval caching caches the short intervals in large video to guarantee continuous delivery for multimedia streams • …

8. Our new design • Object partitioning • Multiple different hotspots created at server • different blocks from different cooperative proxy • Fullcoverage of all blocks from cooperative proxy • An object preview from each hotspot • Cache Admission • To maintain all blocks accessible from cooperative proxy servers • Cooperation mechanism • Message based • Server control to maintain data security • Proxy keeps full autonomy on its own cache content • Limited number of cooperative proxy to maintain scalability

9. Multiple Hotspots • E.g. Divide into low temporal resolution segments • Group the blocks together to form multiple hotspots • Every block belongs to at least one hotspot 1 2 3 4 5 6 7 8 9 10 11 12 Leader blocks 1 2 3 4 5 6 7 8 9 10 11 12 multiple hotspots 1 2 3 7 11 1 2 4 8 12 1 2 5 9 1 2 6 10

10. Cache Admission • The hotspots are admitted to cache in priority • uncached hotspots • hotspots not cached in the regional network A S C B D

11. Message Based Cooperation Algorithm • Client sends request via local proxy to server S. • Local proxy (LP) sends object request to server. • Server S returns the decryption key and the list of coop proxy (CP) caching hotspots recently. • LP sends request for a block to the nearest CP. • CP returns a block or reject message to LP. If rejected, LP sends missing block request to server and server returns block to LP. • LP returns the block to client and selects one hotspot to cache • LP informs the server about which hotspot is cached. • Server updates the list of coop proxy with hotspots.

12. Simulation Parameters • 5 servers, 1000 video titles per server • Video length: uniformly distributed with mean 125 blocks • 10 hotspots per video • Zipf-like popularity = c/i(1-), =0.271 • 50 proxy servers • proxy cache size 25,000 blocks • Cache replacement function = 1/((T-T’)*log(blockno*16)) • Server returns list of4 coop proxy per hotspots • Network latency: exponentially distributed with different mean value: local, regional & remote

13. Simulation • Comparing methods • cooperative hotspot, • non-cooperative hotspot and • variable length segment based • Compare • Byte hit ratio • Stream service time • Number of server streams • Number of proxy streams • Stream response time

14. Increase the byte hit ratioby 70% using coop proxy cache Best when all hotspots can be found in regional coop proxy

15. Reduce service time with more cooperative proxy returned per hotspot

16. The lowest server load. Number of server streams increases with number of requesting proxy servers at the lowest rate

17. Limited increase in proxy load for cooperation. Smallest increase when the no. of proxy in region = no. of hotspots

18. Reduce service time, more efficient under light load condition Only lightly loaded proxy should participate.

19. Low response time similar to non-cooperative hotspot under light load. Reject cooperative requests under heavy load.

20. Summary • Cooperative proxy with multiple hotspots • Provide byte hits for 70% of data from previous compulsory cache misses • Reduce service time of streams • Dynamically balance loads from hot servers to lightly loaded cooperative proxy servers • The method is best when • All hotspots are cached in regional coop proxy • Number of hotspots = number of proxy in the region • The server returns more cooperative proxy

21. Work to continue • Scalability issue: increase in both number of servers and proxy servers • Region based cooperation • Detailed performance model • Enhancements: • Variable length hotspots • Content discovery using hints • Guarantee server streams without reservation