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Effectively Delivering XML Information in Periodic
Broadcast Environments
TU Kaiserslautern, Gottlieb-Daimler-Strasse, Kaiserslautern 67663, Germany
Muntazir Mehdi
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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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