Dynamic Skip-Layer Trees: A Novel Data Structure for Efficient Multi-level IoT Data Processing in Smart Cities

Year : 2024 | Volume : 02 | Issue : 02 | Page : 11 21
    By

    Ushaa Eswaran,

  1. Principal and Professor, Department of Electronics and Communication Engineering, Mahalakshmi Tech Campus Affiliated to Anna University, Chennai, Tamil Nadu, India

Abstract

This paper introduces dynamic skip-layer trees (DSLTs), a novel hierarchical data structure specifically designed for processing and managing multi-layered Internet of Things (IoT) sensor data in smart city environments. DSLTs extend the traditional skip list concept by incorporating dynamic layer adjustment and spatial awareness, enabling efficient querying and updates across various geographical and temporal dimensions. Our experimental results demonstrate that DSLTs achieve up to 40% faster query processing and a 30% reduction in memory overhead compared to conventional data structures when handling large-scale IoT sensor networks. The implementation of a real-world smart traffic management system in Singapore showed significant improvements in real-time data processing capabilities.

Keywords: IoT data structures, smart cities, dynamic skip-layer trees, spatial-temporal data processing, hierarchical data management, sensor networks

[This article belongs to International Journal of Data Structure Studies ]

How to cite this article:
Ushaa Eswaran. Dynamic Skip-Layer Trees: A Novel Data Structure for Efficient Multi-level IoT Data Processing in Smart Cities. International Journal of Data Structure Studies. 2024; 02(02):11-21.
How to cite this URL:
Ushaa Eswaran. Dynamic Skip-Layer Trees: A Novel Data Structure for Efficient Multi-level IoT Data Processing in Smart Cities. International Journal of Data Structure Studies. 2024; 02(02):11-21. Available from: https://journals.stmjournals.com/ijdss/article=2024/view=181598


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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 24/10/2024
Accepted 26/10/2024
Published 07/11/2024
260

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