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A study of an adaptive replication framework for orchestrated composite web services.

Marwa F Mohamed1, Hany F Elyamany, Hamed M Nassar

  • 1Computer Science Department, Faculty of Computers and Informatics, Suez Canal University, 41522 Ismailia, Egypt.

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|November 21, 2013
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Summary
This summary is machine-generated.

Adaptive replication frameworks enhance web service quality of service (QoS). This study introduces a predictive model to optimize replica placement, significantly improving performance in dynamic business environments.

Keywords:
Composite web serviceLoad balancingOrchestrationQoSReplicationService-Oriented Architecture (SOA)

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Web Services

Background:

  • Web service replication is crucial for enhancing Quality of Service (QoS) and managing IT energy consumption.
  • Replication processes are often time-consuming and complex, especially for orchestrated composite web services.
  • Existing methods struggle with the dynamic nature and potential failures/overloads of web services.

Purpose of the Study:

  • To present an adaptive replication framework for regular and orchestrated composite web services.
  • To address challenges in replication timing, host selection, and performance enhancement.
  • To reduce the time and complexity associated with outsourcing new replicas.

Main Methods:

  • Developed an adaptive replication framework with components for event detection (failures, overloads).
  • Implemented a replication controller for optimal host selection.
  • Integrated a load prediction component to anticipate incoming traffic.
  • Utilized a simulation environment to evaluate framework performance.

Main Results:

  • The adaptive replication framework effectively detects and manages unexpected events.
  • Load prediction significantly decreases the time required for outsourcing new replicas.
  • The framework demonstrates substantial performance enhancements in simulated scenarios.
  • The adaptive replication with prediction scenario proved most effective.

Conclusions:

  • The proposed adaptive replication framework enhances the performance and reliability of web services.
  • Predictive load management is key to overcoming the time constraints of replication.
  • This approach offers a robust solution for improving QoS in online business environments.