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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Compression-based aggregation model for medical web services.

Dhiah Al-Shammary1, Ibrahim Khalil

  • 1School of Computer Science & IT, RMIT University, Melbourne, Australia. d.alshammary@student.rmit.edu.au

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 25, 2010
PubMed
Summary
This summary is machine-generated.

Hospitals use Cloud Web services for networking, but large XML data in SOAP messages cause congestion. This study proposes two XML-aware aggregation techniques to reduce medical message sizes and improve performance.

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Area of Science:

  • Computer Science
  • Health Informatics
  • Network Engineering

Background:

  • Hospitals utilize Cloud Web services to reduce infrastructure costs.
  • Simple Object Access Protocol (SOAP) is a key communication protocol for Cloud Web services, relying on XML.
  • Large XML overhead in SOAP messages contributes to network congestion and bottlenecks.

Purpose of the Study:

  • To address network congestion in Cloud Web services caused by large XML data.
  • To propose novel techniques for reducing the size of medical Web messages.
  • To enhance the efficiency of Cloud Web services in healthcare settings.

Main Methods:

  • Developed two XML-aware aggregation techniques.
  • Leveraged compression concepts for message size reduction.
  • Focused on aggregating medical Web messages.

Main Results:

  • Achieved significant reduction in medical Web message sizes.
  • Proposed techniques effectively mitigate network traffic issues.
  • Enhanced the performance of Cloud Web services for healthcare applications.

Conclusions:

  • The proposed XML-aware aggregation techniques offer a viable solution for reducing message sizes.
  • These methods can alleviate congestion and improve the efficiency of Cloud Web services in healthcare.
  • Optimizing medical Web message transmission is crucial for reliable healthcare informatics.