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XML Fragment Caching for Large-Scale Mobile Commerce Applications. Sebastian Obermeier, Stefan Böttcher University of Paderborn Germany ICEC 2008, Innsbruck, Austria. Agenda:. Large Event Scenarios. Use Case. Use Case. GPRS/UMTS. Ad-Hoc Network. Query Shipping. Query Q.

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xml fragment caching for large scale mobile commerce applications
XML Fragment Caching for Large-Scale Mobile Commerce Applications

Sebastian Obermeier,

Stefan Böttcher

University of PaderbornGermany

ICEC 2008, Innsbruck, Austria

Agenda:

caching for query shipping
Caching for Query Shipping
  • Intermediate node N checks whether it can answer Q

 Only Q's result is transferred

 Test can be complex and time consuming

Small missing parts of information lead to cache-misses:

    • Qcache = //restaurant[./@areaID<50]//description
    • Q = //restaurant[./@areaID<35]//description
data shipping
Data Shipping

Query Q: {1,3,4}

{

1

,

2

}

{

2

,

3

}

{

1

,

2

,

3

}

{7}

{1,3,4,7}

{

1

,

4

,

7

}

{

1

,

2

}

caching for data shipping
Caching forData Shipping
  • Request parts of the document

 Combination of cached content can answer Q

 Tests are fast

 Hugeamountofoverheadifread-setis large, e.g. if Q usescount()

application considerations
ApplicationConsiderations
  • No arbitrary queries
    • Query templates predefined
  • Mostly point and range queries including filters
  • Database can track queries
  • Focus on content, e.g. text, pictures, and videos
    • Database updates are rare
  • Egoistic node behavior
    • do not spend much energy to other node’s queries
solution overview
Solution Overview
  • Split XML document into disjoint fragments according to aSplit Schema Graph (SSG)
  • Querying node determines by SSG necessary fragments to answer query Q
  • Q isexecutedlocally on theread-setof Q (=mergedsegments)

S6

XML

S5

S4

S1

S2

S3

S6

XML

S5

S4

S1

S2

S3

S5

S3

split schema graph
Split Schema Graph
  • XML documentsplitintodisjointparts

Segment 1 /1/2/2/1

<restaurants>

<restaurant id = "25" areaID="15">

<name>Forester`s House</name>

<description>Traditional… </…> <style>German</style>

</restaurant> <restaurant id = "35" areaID="17">

<name>Garden of Sun</name>

<description>Large beer garden…</…> <style>Austrian</style>

</restaurant>

...

</restaurants>

determine required segments
DetermineRequired Segments
  • //restaurant[@areaID>13][@areaID<19]/name

Required Segments

1 /

*/*/2/*/

experimental evaluation
Experimental Evaluation
  • 1600 devices, logicalclock
  • 24MB Information Repository
    • Max. distance 5 hops
  • Individual query profiles
    • Eachwith 164 XPath queries
    • 80% requesthotspot data (5MB)
  • Hotspot changesduring evaluation
experimental results
Experimental Results

XPath Query Shipping

XPath Query Shipping 500kB Cache

XPath Query Shipping

XPath Query Shipping 500kB Cache

gzip compression
GZIP Compression

XPath Query Shipping

XPath Query Shipping 500kB Cache

XPath Query Shipping(GZIP)

XPath Query Shipping(GZIP) , 500kB Cache

varying cache sizes
Varying Cache Sizes

500kb Cache

1000kb Cache

2000kb Cache

XPath Query Shipping (GZIP) 1000kB Cache

XPath Query Shipping (GZIP) 500kB Cache

XPath Query Shipping (GZIP) 2000kB Cache

XPath Query Shipping (GZIP)

summary and conclusion
SummaryandConclusion

S6

XML

  • Querying and caching mechanism that allows clients to execute queries locally
  • Application based fragmentation schema
  • Simple cache contribution tests by IDs
    • Coupes with egoistic node behavior
  • Reduces network traffic up to 88%
  • Improves query response time up to factor 5
  • Reduces bottlenecks
  • Can be individually used for each query type

S5

S4

S1

S2

S3

2 /4/*/1 == 2 /4/2/1