CS411 Dynamic Web-Based Systems

1. CS411 Dynamic Web-Based Systems Adaptive Web Caching Flying Pig Fei Teng/Long Zhao/Pallavi Shinde Computer Science Department

2. ADAPTIVE WEB CACHING Contents Introduction Related Research Main Findings An Ideal Adaptive Web Caching System Multicast Request Forwarding Page Retrieval Hierarchy and Scalability Auto-configuration of Cache Groups Group Creation and Maintenance Conclusions Future Scope

3. ADAPTIVE WEB CACHING Introduction The World Wide Web has seen an exponential growth in: • the user population • the total host count • the amount of total traffic volume Popular web pages create ‘hot-spots’ of network load due to the same data transmitted over the same network links repeatedly to different users. The solution is obviously Caching

4. ADAPTIVE WEB CACHING Introduction • The solution to data dissemination to a multitude of users is to create a multicast delivery system – i.e. data should be fetched only once and forwarded via a multicast tree to different users • As requests on the web are asynchronous – web multicasting is done via caching • The challenge in building a caching system is not knowing beforehand which pages the users will be requesting • This is where an Adaptive Web Caching System comes in...

5. ADAPTIVE WEB CACHING Related Research The Harvest/SQUID Object Cache is a Web caching infrastructure currently being deployed in the Internet. All cache servers in the SQUID system are connected in a manually configured hierarchical tree This project has helped reduce unnecessary network load through caching

6. ADAPTIVE WEB CACHING Related Research However, there are limitations due to manual configuration of such large systems: • the burden on system administrators to configure the cache hierarchy and to coordinate with each other • the inevitable human errors • misunderstanding of issues concerning the overall system performance • the desire for local optimization • And the lack of adaptivity to network changes

7. ADAPTIVE WEB CACHING Main Findings An Adaptive Web Caching System has the following characteristics • An overlapping mesh, with each page having its own cache tree • Auto-configuring • Routes requests to the nearest cache likely to have the data • Adaptive to changes in topology, load, user demands, etc. • Scalable

8. ADAPTIVE WEB CACHING An Ideal Adaptive Web Caching System Ideally the more a page is requested by users, the page would automatically walk down the distribution tree (i.e. it is proportional to the intensity of the requests). This way the most popular pages would be the closest to the end user and more cached copies of these pages would exist. While pages that have been rarely requested for will either not leave the origin server of be very high up in the distribution tree. An ‘adaptive’ system will load itself according to the demand

9. ADAPTIVE WEB CACHING Multicast IP multicast can be used as a basic building block to build this system. The adaptive caching system makes use of both features of IP multicasting: • Multicast page requests to locate nearest cache copy available • Multicast page responses in order to efficiently disseminate pages with common interests

10. Request Forwarding ADAPTIVE WEB CACHING • Cache servers join more than one multicast group, this way all cache groups heavily overlap each other. • If there is a cache miss in one group, each cache checks if its other cache groups lie in the direction towards the origin server of the requested page.

11. ADAPTIVE WEB CACHING Page Retrieval • Once a request reaches a group of servers that have requested it, the node holding the page multicasts the response to the group. • This also loads the neighbouring caches in the same group with the page.

12. ADAPTIVE WEB CACHING Hierarchy and Scalability • On a base of overlapping mesh, each popular page grows its own cache tree. • Cache pages based on the popularity of the page allows the design of this system to scale well with large user populations. • Cache tree for each page may grow dynamically, but the cache groups remain relatively stable.

13. ADAPTIVE WEB CACHING Auto-configuration of Cache Groups For the Cache Group infrastructure to be scalable and robust, they need to be self-configuring for the following reasons: • Manual configuration does not scale (For ex. SQUID system) • Manual configuration tend to be error-prune • Self-configuring capabilities allow cache groups to adapt according to changing conditions in network topology, traffic load, user demand etc.

14. ADAPTIVE WEB CACHING Group Creation and Maintenance The basic functionality for cache group managements concerns group creation and maintenance. This includes: • regrouping according to the observed group load • the group cache hit ratio • the tolerance of group overhead • the change in topology and caches

15. ADAPTIVE WEB CACHING Group Creation and Maintenance • An open membership policy for cache groups • No authentication step required • Cache consistency and data authentication must be properties that reside in the data

16. ADAPTIVE WEB CACHING Conclusions With this Adaptive Web Caching System: • no manual configuration required, it is auto-configuring Higher the demand for a page Page further down the distribution tree and closer to the end user =

17. ADAPTIVE WEB CACHING Conclusions • is adaptive to changes in topology, load, user demands, etc. Cache trees can automatically build themselves as popular pages are pulled down towards their clients. With time the trees should also automatically vanish as the pages become a past interest.

18. ADAPTIVE WEB CACHING Future Scope Collaboration with the Harvest/SQUID Caching team to explore transition strategies to convert the current manually configured caching infrastructure into an auto-configured adaptive caching system. • incremental deployment into the current unicast caching infrastructure of dynamic mechanisms for forwarding requests to neighbouring caches • incremental deployment of a multicast-based cache architecture into the existing architecture of unicast communications between clients, web caches, and servers

19. ADAPTIVE WEB CACHING Thank you for listening! Questions?