Tytuł:

An Energy Efficient and Scalable WSN with Enhanced Data Aggregation Accuracy, Journal of Telecommunications and Information Technology, 2024, nr 2

Tytuł publikacji grupowej:

2024, nr 2, JTIT-artykuły

Autor:

Saadallah, Noor Raad ; Alabady, Salah Abdulghani

Temat i słowa kluczowe:

data aggregation ; energy consumption ; lossless compression ; LZW algorithm ; WSN ; scheduling

Abstrakt:

This paper introduces a method that combines the K-means clustering genetic algorithm (GA) and Lempel-Ziv-Welch (LZW) compression techniques to enhance the efficiency of data aggregation in wireless sensor networks (WSNs). The main goal of this research is to reduce energy consumption, improve network scalability, and enhance data aggregation accuracy. Additionally, the GA technique is employed to optimize the cluster formation process by selecting the cluster heads, while LZW compresses aggregated data to reduce transmission overhead. To further optimize network traffic, scheduling mechanisms are introduced that contribute to packets being transmitted from sensors to cluster heads. The findings of this study will contribute to advancing packet scheduling mechanisms for data aggregation in WSNs in order to reduce the number of packets from sensors to cluster heads. Simulation results confirm the system's effectiveness compared to other compression methods and non-compression scenarios relied upon in LEACH, M-LEACH, multi-hop LEACH, and sLEACH approaches.

Wydawca:

National Institute of Telecommunications

Data wydania:

2024

Typ zasobu:

artykuł

Identyfikator zasobu:

ISSN 1509-4553, on-line: ISSN 1899-8852

DOI:

10.26636/jtit.2024.2.1510

ISSN:

1509-4553

eISSN:

1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Licencja:

CC BY 4.0

Właściciel praw:

Instytut Łączności - Państwowy Instytut Badawczy