1. Dissemination of Dynamic Data on the Internet
Krithi Ramamritham
Pavan Deolasee
Amol Katkar
Ankur Panchbudhe
Prashant Shenoy
Dec 2000

2. Overview of Presentation.
Dynamic Data
Temporal Coherency
Cache Consistency
Push and Pull Approaches
Combining Push and Pull
Dynamically choosing Push or Pull
Conclusions

3. Dynamic Data Dissemination
Data which changes rapidly &
unpredictably.
e.g Sports scores, traffic or weather data.
Coherency requirements
Nature of the item
User tolerances

4. How dynamic data is dealt with?
Functions of a Proxy
Exploits user specified coherency.
Maintains desired temporal coherency.
Server
Proxy
User
Push
Push
Pull

5. Temporal Coherency Each cached item must be periodically refreshed.
For highly dynamic data
Difficult to maintain cache consistency.
Heavy network overload.
Server load.

6. How temporal coherency is achieved.
User is not interested in every change happening at the source.
User specifies a temporal coherency requirement c for each cached item.
Proxy depending on value of c can use push or pull approach to maintain coherency.

7. Cache Consistency. Fidelity of the data
Degree to which coherency needs of a user are met.
Normally, the problem of cache consistency is resolved by 2 approaches
Client-driven
Server-driven

8. Cache Consistency Client-driven Polling each time
Adaptive TTR(time to refresh)
Server-driven
Invalidates cache entries
Updates proxy cache
In case of dynamic data,
Cannot deliver fidelity with optimum resource utilization

9. The Pull Approach
Each data item is assigned a certain TTR & until that time all requests are satisfied from the cache.
Proxy issues a get request to the server.
Periodic
Server
Push
Proxy
User
Periodic
Pull
Server
Pull
Proxy
Push
User
Aperiodic

10. Pull Approach. Periodic Pull Proxy periodically polls the server
Obtains data with a high frequency
Disadvantages
Very high network overhead
User may miss some changes
Not suitable if rate of change is varying

11. Pull Approach(Contd..) Aperiodic pull
TTR decreases dynamically when a data item starts changing rapidly
Increases when a hot file becomes cold
Adaptive TTR takes into account
Rapid changes that have occurred so far
Recent changes to the polled data

12. Push Approach
Server can push data either periodically or aperiodically
Periodic Push
Disseminates data based on demand for
data item
All data items get divided into frequency
bands
Disadvantages
Low fidelity, Wastage of bandwidth

13. Push Approach(Contd..) Aperiodic Push Proxy registers with the server
Server uses tcr to determine if data item is to be
pushed.
Server maintains state information as list of
proxies,tcr and last update to each proxy
Combines requests with identical tcr into a single
request
Disadvantages
Limits scalability, not resilient to failures.

14. Push v/s Pull Communication Overhead Pull- Larger load on the network
Push-Large message overhead
Computational Overhead
High load due to too much polling or
monitoring
Space Overhead
Maintains c value, pushed value, state with
open connection

15. Push v/s Pull Resiliency
State of server is lost in case of server failures
In client failures, resources assigned must be
reclaimed
Scalability
With upper bound on the number of sockets and
state space available, servers become scalable
It arises due to excessive server computation and
resources allocated

16. Combining Push and Pull
Leases
Contracts given to a lease holder over some
property
Server informs the client about any
changes during the lease period
Adaptive Leases
Dynamically adjust the lease duration
Gives strong cache consistency

17. Combining Push and Pull
Server tries to predict when a client is going to poll next
If it knows that a client is going to miss some change it pushes the data to the client
In this approach the performance in terms of fidelity and resiliency can be controlled

18. Dynamically choosing Push v/s Pull
If resources are plentiful, every client is given a push connection
As clients increase, some clients are shifted to pull mode and scalability is ensured
Clients are assigned priorities by
Temporal coherency requirement
Fidelity requirement
Network bandwidth available

19. Conclusions
It is a priori difficult to determine whether a push or pull based approach is to be employed.
Combination of Push and Pull is used.
Currently work is going on in determining range of applicability of new algorithms for disseminating web data