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A novel efficient data storage and data auditing in cloud environment using enhanced child drawing development optimization strategy

  • 0Computer Science and Engineering, SA Engineering College, Poonamallee, India.
Electronic Structure (bristol, England) +

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January 17, 2025

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January 17, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study introduces the Adaptive Level and Skill Rate-based Child Drawing Development Optimization (ALSR-CDDO) algorithm to optimize cloud data structures, reducing costs. The method uses Divide and Conquer Tables (D&CT) for efficient data storage and auditing.

Area Of Science

  • Cloud Computing
  • Data Structures
  • Algorithm Optimization

Background

  • Cloud-based data structures require efficient management for cost and performance.
  • Existing methods may not adequately address dynamic data updates and auditing.
  • Optimizing data structure selection is crucial for reducing computational and communication costs.

Purpose Of The Study

  • To introduce and evaluate the Adaptive Level and Skill Rate-based Child Drawing Development Optimization (ALSR-CDDO) algorithm for cloud data structures.
  • To reduce the overall computing and communication costs associated with cloud data management.
  • To implement a robust data storage and auditing mechanism for cloud platforms.

Main Methods

  • Utilizing the ALSR-CDDO algorithm for optimal selection of cloud-based data structures.
  • Employing the Divide and Conquer Table (D&CT) method for data storage, including location and information tables.
  • Implementing dynamic and batch auditing for stored data, even with real-time updates.

Main Results

  • The ALSR-CDDO algorithm effectively optimizes data structure selection, leading to reduced costs.
  • The D&CT method provides efficient data storage with version control and updated location tracking.
  • The proposed auditing scheme demonstrates security comparable to existing methods.

Conclusions

  • The ALSR-CDDO algorithm offers a cost-effective solution for cloud data structure optimization.
  • The D&CT approach enhances data management through efficient storage and dynamic auditing.
  • The implemented security scheme provides reliable data auditing in cloud environments.

Keywords:

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