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Enhancing Energy Saving in Smart Farming through Aggregation and Partition Aware IoT Routing Protocol
Karim Fathallah1, Mohamed Amine Abid2, Nejib Ben Hadj-Alouane1
1National Engineering School of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia.
Precision agriculture using Internet of Things (IoT) faces network challenges. A new Partition Aware-Routing Protocol for Low power and Lossy Networks (PA-RPL) significantly reduces energy consumption by optimizing data routing.
Area of Science:
- Agricultural Engineering
- Computer Science
- Network Engineering
Background:
- Precision agriculture, or Smart Farming (SF), utilizes Internet of Things (IoT) sensor networks.
- Increasing farm complexity leads to network congestion, interference, and high energy use in IoT deployments.
- Existing routing protocols like RPL struggle with large-scale, complex agricultural environments.
Purpose of the Study:
- To propose a novel routing algorithm, Partition Aware-RPL (PA-RPL), to enhance IoT efficiency in precision agriculture.
- To improve network performance by reducing data traffic and energy consumption.
- To address the limitations of standard RPL in complex, partitioned farmlands.
Main Methods:
- Developed PA-RPL, an extension of the IPv6 Routing Protocol for Low power and Lossy Networks (RPL).
- Designed PA-RPL to build a routing topology that facilitates efficient in-network data aggregation.
- Evaluated PA-RPL performance in a realistic precision agriculture scenario for potato late blight prevention.
Main Results:
- PA-RPL dramatically reduces data traffic through efficient in-network aggregation.
- The proposed algorithm significantly lowers energy consumption compared to standard RPL.
- Performance analysis demonstrated up to 40% energy savings in a potato pest prevention case study.
Conclusions:
- PA-RPL offers a significant improvement over standard RPL for IoT in precision agriculture.
- The algorithm's data aggregation capabilities effectively mitigate network congestion and energy waste.
- PA-RPL presents a viable solution for more sustainable and efficient smart farming.
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