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Scalable solutions for implementing satellite-based sensor networks
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DOI：10.1016/j.rineng.2024.102481.png)
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摘要
En 中文
The importance of sensor networks in the field of IoT cannot be overstated, especially with the growing demand for IoT solutions. The new Internet protocols such as IPv6 and 5G mobile provide high-capacity communication networks, demonstrating the relevance and potential applications of IoT in the future. However, with new demands come new challenges. This paper aims to explore the challenges of Satellite-based Sensor Networks, a new topic with various applications. This article explores the challenges and constraints of implementing a scalable satellite-based sensor network. We examined the hardware and software limitations of the Iridium satellite SBD protocol and proposed tailored solutions using design flow algorithms to tackle flexibility, power consumption, bandwidth, and scalability issues. Satellite-based sensor networks face challenges in data transmission and sensor lifespan. In this study, we introduce event-driven and compression algorithms to address these challenges. By implementing clustering, we achieved a significant increase in the number of nodes within each cluster. Our proposed methods were validated using simulated datasets derived from temperature and location data. A unique data transmission method, based on event count, was introduced. Notably, the Differential Huffman compression algorithm resulted in an 81 % reduction in data transmission compared to traditional methods. This demonstrates about 62 % improvement in efficiency over existing techniques. Our approach not only paves the way for future advancements in this domain but also highlights the untapped potential of satellite-based sensor networks.
Keyword:
Satellite -based sensor network
Design flow
Algorithm
Scalable sensor network
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7.9
论文数:
1.2W
被引数:
1.7W
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