Understanding the Understanding the Performance of Web Caching Performance of Web Caching

System with an Analysis System with an Analysis Model and SimulationModel and Simulation

Xiaosong Hu Xiaosong Hu Nur Zincir-HeywoodNur Zincir-Heywood

Sep 20 2003Sep 20 2003

OutlineOutline• Web Cache Background• Cooperating Web Caching System• The model of the Hierarchical System• Performance Analysis• Simulation• Comparison• Conclusion

Web Cache BackgroundWeb Cache Background• WWW becomes the dominant

application of the Internet• Demand for bandwidth outstrips the

supply• Congestion and server overloading• Web Caching---Storing some popular

pages somewhere close to the clients• Browser caching and proxy caching

Cooperating Web Caching SystemCooperating Web Caching System

• Can we configure the proxy cache server to visit each other at first before going to the source server?

• Based on research so far, the web caching system can be divided into

--- Hierarchical System --- Distributed System --- Hybrid System

Hierarchical SystemHierarchical System

Request

ClientThe router without associated cache server

The router with associated cache server

** The figure shows the network system with O = 2, h = 2.

Institutional cache

Regional cache

National cacheResponse

To Source Server

Performance AnalysisPerformance Analysis---Parameters------Parameters---

• Hit Ratio: The probability that a requested document can be retrieved from the system

• Latency: The average time to retrieve a document from the Internet

• Traffic: The average traffic at each link over a time unit

• Average Hop: The average distance for a request to be satisfied

Performance AnalysisPerformance Analysis ---Assuming--- ---Assuming---

Parameter nameParameter

value

1 Nodal outdegree of the tree (O) 3

2 Hops between two neighboring levels of cache (h) 2

3The hops from the national cache to the source

server (z)10 [10]

4 Average request rate from the clients ( βI) 2 requests/sec

5 Total document number 1 million

6 Average document update time (∆) 12h

7 Skew factor of Zipf distribution (α) 0.64 [9]

8 Cache Content updating function LFU

Performance AnalysisPerformance Analysis---Formula for Hit Ratio------Formula for Hit Ratio---

• the most popular Ci documents will be cached.

• A request is a hit only if it is for a document in Ci and its interval is less than ∆.

• Hit Ratio H = ---PN(i) is the probability that a request is for document i ---P(L) is the probability that the request for document i within ∆.

))()(((1

LPiPiC

iN

Performance AnalysisPerformance Analysis--- --- PPNN(i) & P(L) (i) & P(L) ------

• The probability of a request for document i is a Zipf-like distribution

PN(i) = ,

• The arriving requests are a Poisson distribution. Within a short time

e iILP ,1)|(

Ω =1

1

1

N

i ii

)1(1

1)( ,

,

iIeLPiI

dLPLP )|(1

)(0

Performance AnalysisPerformance Analysis--- average hit ratio ------ average hit ratio ---

Institutional cache (i)H(i)=H(ii)+H(ir)+H(in)

Regional cache (r) H(r)=H(rr)+H(rn)

National cache (n) H(n) =H(nn)

Client

Client

Client

Haverage = [H(i)•O2h + H(r)•Oh + H(n)]/(O2h+Oh+1)

SimulationSimulation• The web cache simulator

• Data Sets: ---half, one and two millions requests ---login file;

Input & Output Component

SimulationComponent

Network CacheSystem

ComparisonComparison

ConclusionConclusion• The hit ratio is a logarithmical

function or a function with a small power to the cache size

• The results from the model are compatible with those from the simulation

• The model can be used to further analyze the cache system mechanism