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Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

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

Aruna Kari Balakrishnan¹, Arunachalaperumal Chellaperumal², Sudha Lakshmanan¹

¹Computer Science and Engineering, SA Engineering College, Poonamallee, India.

Network (Bristol, England)

|January 17, 2025

Summary

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.

Keywords:

Big data adaptive level and skill rate-based child drawing development optimization cloud computing data auditing data integrity data storage divide and conquer table

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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.