Effectively Delivering XML Information in Periodic

Broadcast Environments

TU Kaiserslautern, Gottlieb-Daimler-Strasse, Kaiserslautern 67663, Germany

Muntazir Mehdi

1

Outline

• Data Broadcast Context

• Problem in This Work

• Our Approach

• Experimental Results

• Conclusions

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Data Broadcast Context

• Rapid growth of wireless applications

– Wireless devices (smart phones, pads, etc.)

– Wireless networks

– Information Services(news, stock quotes, airline schedules, weather and traffic information)

Access Information Anywhere Anytime

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Data Broadcast Context

• Information delivery methods

– Point-to-point access

• Logical channel/link between client and server

– Broadcast

• Data sent to all clients in broadcast area

• Clients select data that they need

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Data Broadcast Context

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Data Broadcast Context

• Why broadcast is attractive?

– Scalability: Single broadcast can satisfy all outstanding requests from clients

– Energy efficiency: Mobile clients can switch to doze mode when waiting for interesting data to be broadcasted

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Data Broadcast Context

• Performance metric

– Access latency: the wait time.

– Energy consumption: the amount of data that clients need to download

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Data Broadcast Context

• Main Research problems in Data Broadcast

– Scheduling

• To reduce access latency

– Indexing

• To reduce energy consumption

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Problem in This Work

• How to effectively schedule semi-structured information such as XML data on wireless channels is still a challenge

• We mainly study the scheduling problem of XML data broadcast in periodic environments

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Related Work

Traditional flat data broadcasts:

– Assume that we know clients' access patterns in advance

– face difficulty when generating data broadcast program based only on flat data itself

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Our Approach

• Place XML documents on the broadcast channel based only on information at the server side

• Utilize Structural similarity to predict or approximate clients' access patterns

– path sets are used to calculate similarity

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Our Approach

Path Set PS(d) – { /player/name, /player/position, /player/nationality,

/player/college, /player, /name, /position, /nationality, /college }

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Our Approach

• Similarity measures

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Our Approach

•Similarity Measure based on probability

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Our Approach

•Similarity Measure based on probability suppose D = {d1 , d2 , . . . , dn } on the server, matched probability of any document d in D for a given query q is approximate to:

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Our Approach

•Similarity Measure based on probability we define Cohesion C(di , dj) of XML documents di and dj as follows:

which can be normalised as

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Our Approach

• Greedy Data Placement Algorithm (GDPA)

– Places XML documents with most structural sharing together first as an initial broadcast program.

– Progressively appends other XML documents to the broadcast program in a descendant order of structural sharing to the initial documents.

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Experimental Results

• Workload parameters

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Experimental Results

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Experimental Results

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Experimental Results

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Conclusions

• We propose to take advantage of the structured characteristics of XML data to generate effective broadcast programs

• Our algorithm is based only on XML data on the server without any knowledge of the clients' access patterns

• Experiments show that our approach can place XML data on air effectively

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