1. Chapter 12.6 Consistency and Replication
Berkay Aydin & Zhuoli Lin
November 11th, 2015

2. Consistency and Replication
Web-Proxy Caching
Replication for Web Hosting Systems
Metric Estimation
Adaptation Triggering
Adjustment Measures
Replication of Web Applications
Consistency
and
Replication
Part I
Perhaps one of the most important systems-oriented developments in Web-
based distributed systems is ensuring that access to Web documents meets
stringent performance and availability requirements. These requirements have led
to numerous proposals for caching and replicating Web content, of which various
ones will be discussed in this section. Where the original schemes (which are still
largely deployed) have been targeted toward supporting static content, much
effort is also being put into support dynamic content, that is, supporting docu-
ments that are generated as the result of a request, as well as those containing
scripts and such. An excellent and complete picture of Web caching and replica-
tion is provided by Rabinovich and Spatscheck (2002).

3. Web Proxy Caching Client-side caching
Browsers - simple caching facility (local cache)
Store documents in the client’s browser cache
Web proxy on client side (shared cache)
Client-side proxy can cache the documents
Sends the document to the client if another response comes in
Hierarchical caching (regions, countries etc.)
Reduce network traffic
Possible to have higher latency, multiple cache checks

4. Web Proxy Caching Cooperative (distributed) caching
When a cache-miss occurs, check neighboring proxies
If neighbor has it, it sends the document. Else request is forwarded to web server
Trade-offs between hierarchical and cooperative caching
Cooperative -> lower transmission time, storage requirements are less strict
Hierarchical -> expected latency is lower
Image taken from [1]

5. Web Proxy Caching Cache-consistency
Conditional HTTP request (if-modified-since header)
If the document is modified since the associated header value, server returns
Else web proxy returns
Proxy contacts the server each time
Squid Web proxy
Expiration time (shows how long ago the document was last modified)
Until Texpire the document is considered as valid (practically α can be set to 0.2)

6. Web proxy caching Problems with Squid Alternatives
Less consistency
Proxy may return an invalid document
There is no way to detect
Alternatives
Server notifies proxies by sending an invalidation
Downside -> scalability
It can outperform in terms of bandwidth and perceived latency
Web-proxy is for static content
Cache replacement strategy -> LRU

7. Replication for Web Hosting Systems
Content Delivery Network (CDN)
Maintaining the content of Web
Ensuring that the site is accessible
CDNs act as web hosting service
replicate the content in different sites
self-managing system -> automatic distribution and replication
Three aspects of CDNs
Metric estimation
Adaptation triggering
Taking appropriate measures
{Replica replacement, consistency enforcement, client-request routing}

8. Replication for Web Hosting Systems
Content Delivery Network (CDN)
Maintaining the content of Web
Ensuring that the site is accessible
CDNs act as web hosting service
replicate the content in different sites
self-managing system -> automatic distribution and replication
Three aspects of CDNs
Metric estimation
Adaptation triggering
Taking appropriate measures
{Replica replacement, consistency enforcement, client-request routing}

9. Replication - Metric Estimation
Trade-offs (access time vs. cost)
Latency metrics
Time spent for fetching a document
Available bandwidth (bandwidth between two nodes)
Important for large document transfers
Spatial metrics
Distance between nodes (number of network level routing-hops)
Network usage metrics
Consumed bandwidth, number of bytes to transfer
Consistency metrics
To what extent a replica is deviating from its master copy
Financial metrics
Financial performance

10. Replication - Adaptation Triggering
When and how adaptations are triggered
Simple Approach: Periodically estimate metrics and take measures as needed
Responding to a flash crowd
Flash crowd predicting
Use a window
Linear regression
Warn when # of requests passes a pre-determined period
Hard to get threshold, and windows size

11. Replication - Adjustment Measures
Deciding how and when to redirect client requests
Embedded documents
Get base document
DNS lookup from regular DNS system
DNS lookup from CDN DNS system
Get embedded documents from CDN server
If cached - use cache
Else - use origin server
Perceived performance

12. Replication of Web Applications
Edge-server stores replicated data
Replication can be
Partial
Full
Full replication - works well when
low update ratio, frequent joins
Partial replication
which data to be stored?
content-aware caches
well with repeated queries
consistency problem
content-blind caching
caching the query results

13. Consistency and Replication
Introduction
Related Work
Techniques to Scale Web Application
Consistency
and
Replication
Part II

14. Introduction
Developers often use relocation and caching mechanisms to enhance Web application performance.
This paper present a qualitative and quantitative analysis of state–of–the-art replication and caching techniques used to host Web application.

15. Related Work
Web sites can be slow for many reasons, but the most prevalent one is the dynamic generation of Web documents.
Dynamic generation of a Web page typically requires issuing one or more queries to a database, so access time to the database can easily get out of hand when the request load is high.
There are several techniques to overcome this problem.
The most straightforward one is Web page caching.
This technique works well if the same cached HTML page can answer many requests to a particular Web site.
With the growing drive toward personalized Web content, generated pages tend to be unique for each user, thereby reducing the benefits of page – caching techniques.

16. Techniques to Scale Web Application
Instead of caching the dynamic pages generated by a central web server, various techniques aim to replicate the means of generating pages over multiple edge servers.
They typically provide “read–your–writes” consistency, which guarantees an application at an edge server performs an update, any subsequent reads from the same edge server will return that update’s effect.

17. Techniques to Scale Web Application Edge Computing
The simplest way to generate user–specific pages is to replicate the application code at multiple edge servers and keep the data centralized
Drawbacks
If the edge servers are located worldwide, each data access incurs wide – area network latency.
The central database quickly becomes a performance bottleneck because it needs to serve the entire system’s database requests.

18. Techniques to Scale Web Application Data Replication
To solve the database bottleneck problem, data replication places the data at each edge server so that generating a page requires only local computation and data access.
This technique helps maintain identical copies of the database at multiple locations.
Drawbacks
If a Web application generates many database updates, each update must be propagated to all the other replicas to maintain the consistency.
Potentially introduce a huge network traffic and performance overhead.

19. Techniques to Scale Web Application Content-Aware Data Caching
Instead of maintaining full copies of the database at each edge server, content – aware caching systems cache database query results as the application code issues them.
Each edge server maintains a partial copy of the database, and each time the application running at the edge issues a query, the edge – server database checks of it contains enough data locally to answer the query correctly.
Drawbacks
This method can reduce the cache hit rate.
The update queries always execute at the origin server.

20. Techniques to Scale Web Application Blind Data-Caching
Edge servers do not need to run a database at all.
Servers store the results of remote database queries independently, so the cache replacement is simple.
Can apply many popular replacement algorithms.

21. Comparison
RUBBos benchmark
TPC – W brosing
TPC – W ordering

22. Consistency and Replication
Future Work
Consistency
and
Replication
Part III

23. Future Work
Plan to build and evaluate a prototype system that enables dynamic provisioning and reconfiguration of multitier Web applications.
A combination of end–to–end analytical model and virtual caches will determine the optimal resource configuration for a given application.

24. References
[1] Tanenbaum, A., & Steen, M. (2007). Distributed systems: Principles and paradigms (2nd ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
[2] Sivasubramanian, S., Pierre, G., van Steen, M., & Alonso, G. (2007). Analysis of caching and replication strategies for web applications. Internet Computing, IEEE, 11(1),
[3] Sivasubramanian, S., Pierre, G., Van Steen, M., & Alonso, G. (2006).GlobeCBC: Content-blind result caching for dynamic web applications. Technical Report IR-CS-022, Vrije Universiteit, Amsterdam, The Netherlands.