Aruna Balasubramanian Brian Neil Levine Arun Venkataramani University of Massachusetts, Amherst...
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Transcript of Aruna Balasubramanian Brian Neil Levine Arun Venkataramani University of Massachusetts, Amherst...
Aruna BalasubramanianBrian Neil Levine
Arun VenkataramaniUniversity of Massachusetts,
Amherst
Enhancing Interactive Web Applications in Hybrid Networks
1
MotivationMobile users increasingly want to access network
applications on the go
Cost
Technologies
Application support
3G
Opportunistic WiFi
2
Our workHow can we support a broader class of interactive
applications using opportunistic WiFi access?
Internet
1. Mobile-to-Infrastructure contacts
2. Mobile-to-Mobile contacts
3
Application design space
Disconnection duration with AP
Conn
ectio
n du
ratio
n w
ith A
P
~1s ~60s ~3600s
~1s
~3600s
~60s
VoIP
Interactive Web?Web browsing,Web search
Delay TolerantEmail, bulk transfer m2m contacts
useful
m2i contacts useful
???
4
OutlineHow can opportunistic mobile-to-Infrastructure
(m2i) contacts be used to support web search?
Can performance be improved by simultaneously leveraging mobile-to-mobile (m2m) contacts?
What is the performance of web search using opportunistic WiFi access?
5
Web search process<your favorite search engine>
Retrieving….
Retrieving….
6
Challenges: Intermittent connectivity
<your favorite search engine>
Retrieving….
7
Thedu: Adapting Web search for intermittently connected networks1. Use aggressive prefetching web pages to convert
interactive process to transactional
2. Prioritize prefetched web pages during bandwidth limited connection
8
Internet
1. Aggressive prefetching
TheduProxy
9
1. Aggressive prefetching
Queries from mobile node
Store queryStore query Interface
Google, Yahoo, Live ,
Ask, ….
Google, Yahoo, Live ,
Ask, ….
SnippetsSnippets Prefetch Prioritized web pages
Prioritized web pages
Web pages returned to mobile node
Related work• Use prefetching to improve
availability[Coda91, Jiang98, Chandra01]
• Proxy-based to mask disconnections [Seth06,Ott06] 10
2. Prioritizing useful web pages
• How many of these web pages are useful?• How many web pages to prefetch?
• How to compare web pages from different queries?
<your favorite search engine>
11
How many to prefetch and how many web pages are useful? 80% users are interested in top 20 web pages
Thedu: Only prefetch webpages for top 20 url snippets
For some queries (homepage), there is only a single useful response
E.g., query “mobicom 2008” likely needs one response “http://www.sigmobile.org/mobicom/2008/”
Thedu: Identify homepage queries and send only one relevant web response
12
Homepage versus Non-homepage queries
Mobicom 2008<url> www.sigmobile.org/mobicom/2008 </url>
<snippet> MobiCom 2008, the 14th Annual International Conference on Mobile, </snippet>
<title> ACM Mobicom 2008 </title>
Mobicom 2008<url> www.sigmobile.org/mobicom/2008 </url>
<snippet> MobiCom 2008, the 14th Annual International Conference on Mobile, </snippet>
<title> ACM Mobicom 2008 </title>
Oil prices summer<url> www.eia.doe.gov/steo </url>
<snippet> Residential natural gas prices over the same period are projected to ,</snippet>
<title> EIA - Short-Term Energy Outlook </title>
Oil prices summer<url> www.eia.doe.gov/steo </url>
<snippet> Residential natural gas prices over the same period are projected to ,</snippet>
<title> EIA - Short-Term Energy Outlook </title>13
Thedu’s query-type classifier
Homepage Non Homepage
Query terms occur in URL Query is in question form
All query terms occur in title or snippet
Top URL is wikipedia
Less than 3 words Length greater than 3 words
URL is root
Thedu’s query-type classifier accuracy: 88%
14
How to compare web pages from different queries?
Today’s search engine rank web page for a single query using relevance scoresScores not comparable across queries
Queries q1, q2q1
q2
Thedu’s query normalization technique
Thedu’s query normalization technique
…
…
…
Thedu: Aggressive prefetching1.Prefetch top 20 URLs for each query2. Identify home page queries and return only 1 relevant web page in expectation3.Prioritize the remaining web pages across queries by normalizing relevance scores
Thedu: Aggressive prefetching1.Prefetch top 20 URLs for each query2. Identify home page queries and return only 1 relevant web page in expectation3.Prioritize the remaining web pages across queries by normalizing relevance scores
15
OutlineHow can intermittent mobile-to-Internet (m2i)
connectivity be used to support web search?
Can performance be improved by simultaneously leveraging mobile-to-mobile (m2m) contacts?
What is the performance of web search using opportunistic WiFi access?
16
Leveraging opportunistic m2m contacts
Internet
When useful?When meeting opportunities are skewed
Why useful? Because of decreasing marginal utility of web pages
17
Should nodes download their own web pages or route for others?
Thedu uses utility-based routing.
W
X
Y
y1y2…
x1x2…
w1w2…
w1w2… x1x2w3y1Sorted accordingto utility
18
Utility computation: IR meets networkingGoal: Maximize number of relevant responses delivered within a deadline
Utility of routing X or Y’s web pageP(web page is relevant) xP(W can deliver the web page to
destination within deadline)
Utility of downloading own web pageP(web page is relevant) xP(web page will NOT be delivered to W
within deadline if the opportunity is missed)
W
X
Y
19
m2m routing between mobile nodes
Deliver web pages destined to peer
Route other web pages using similar utility-based routing
Exploit query locality by caching popular web pages
W
X
Thedu leverages m2m contacts 1. Using a utility-driven routing protocol 2. Exploiting caching
Thedu leverages m2m contacts 1. Using a utility-driven routing protocol 2. Exploiting caching
20
OutlineCan intermittent mobile-to-Internet (m2i)
connectivity be used to support web search?
Can performance be improved by simultaneously leveraging mobile-to-mobile (m2m) contacts?
How does Thedu perform in practice?
21
Evaluation goalsDoes Thedu improve performance of web search
for opportunistic WiFi networks?
Is there a benefit for leveraging m2m contacts?
Evaluation based on deployment of Thedu on DieselNet testbed and trace-driven simulationsEvaluation based on deployment of Thedu on
DieselNet testbed and trace-driven simulations
22
Evaluation tools: Networking and IRDieselNet Testbed at UMass
Search engine10 GB web collection, Large user study
23
DieselNet: Both m2i and m2m contacts
m2m meeting
m2i meeting24
Web search deployment results
RelevantWeb pagesdelivered
25
Delay in receiving relevant web page
26
Effect of m2i meeting frequency on web search performance
Deployment: March, 2007
Trace-driven: Nov, 2007
27
Leveraging m2m contactsOn DieselNet, leveraging m2m contacts provide
little benefitRatio of m2i versus m2m contacts is 20:1
Our analytical model confirms resultLeveraging m2m routing is useful only if AP density is
low
28
Leveraging m2m contacts: Sparse AP
Leveraging m2m contactsprovides throughput benefit, but not delaydoes not improve performance of interactive applications,
even in sparse AP scenarios 29
ConclusionsThedu enables interactive web search application for
intermittently connected networks
Leveraging m2m contacts only provides throughput benefits and only when AP density is low
Deployment of Thedu on DieselNet shows 3 times improvement in number of relevant web pages
trace.cs.umass.edutrace.cs.umass.edu30