Cloud Retrieval System Model Notes

Abstract

  • Rapid internet growth necessitates information retrieval technology development.
  • Introduction of the cloud retrieval system model composed of:
    • Cloud Information Layer
    • Cloud Retrieval Cluster System (includes various functional layers)
    • User Query Box
  • Testing shows system performance is stable and effective.

I. Model Elicitation

  • Reference to IDC report indicating the massive scale of digital content (500 billion GB estimate).
  • Data growth necessitates advances in retrieval technologies.
  • Cloud computing introduced by Google in 2006 is integral for data management and retrieval.
  • Cloud retrieval merges services based on cloud computing, enhancing user information access.

II. Framework of Cloud Retrieval Model

  • Components:
    • Cloud Retrieval Cluster System: Includes several functional layers, each serving specific roles.
  • Cloud Acquisition Layer: Collects data using network robots with a focus on parallel processing to enhance performance.
  • Cloud Processing Layer: Filters, classifies, and processes collected information for efficient retrieval.
    • Uses algorithms for data redundancy removal and information organization.
  • Cloud Index Layer: Implements inverted index technology for rapid information retrieval:
    • Uses multi-level indexing for large data volumes.
  • Cloud Query Layer: Facilitates user queries through a structured interface:
    • Index scanning, sorting, and result delivery to users.

III. Core Layer Realization

  • Built using Vim + Linux, C++ and Ruby on Rails, with AutoTools for compiling.
  • Cloud Collection Layer Functions:
    • Simulating HTTP protocol, encoding conversion, and maintaining crawling robot states.
    • Multi-threaded robots enhance the efficiency of web data collection.
  • Cloud Processing Layer Functions:
    • Processes original data for segmentation, handles various textual formats.
    • Utilizes maximum matching segmentation algorithms for text processing.
  • Cloud Index Layer Functions:
    • Implements aggregated address inverted indexing for efficient data retrieval.
    • Enhances performance with high data density and flexible indexing.

IV. System Operation and Results

  • Comprehensive and stress testing showed high system reliability, processing 200 requests per second with no errors post-deployment.

V. Conclusion

  • The cloud retrieval system addresses vast and varied information needs effectively.
  • Focus on user personalization is needed to adapt to diverse user requirements, achieved through user behavior analysis and data mining methodologies.