AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks
Within the Internet of Things (IoT) ecosystem, the Routing Protocol for Low-Power and Lossy Networks (RPL) serves as a foundational element for network communication. The protocol's effectiveness depends on its Objective Function (OF), which orchestrates route selection based on predefined crit...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-01-01
|
| Series: | International Journal of Intelligent Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666603024000320 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850129342241177600 |
|---|---|
| author | Abubakar Wakili Sara Bakkali |
| author_facet | Abubakar Wakili Sara Bakkali |
| author_sort | Abubakar Wakili |
| collection | DOAJ |
| description | Within the Internet of Things (IoT) ecosystem, the Routing Protocol for Low-Power and Lossy Networks (RPL) serves as a foundational element for network communication. The protocol's effectiveness depends on its Objective Function (OF), which orchestrates route selection based on predefined criteria. However, traditional OFs often struggle to adapt to the dynamic nature of IoT environments. This paper presents the Adaptive Objective Function (AOF), an innovative algorithm designed to dynamically adjust the OF in real-time, responding to fluctuating network conditions and application requirements. AOF comprises: a Network Monitor, an OF Selector, an OF Switcher, and an Event Handler, all working in concert to enhance network performance, reliability, and energy efficiency. Through simulations, AOF has demonstrated superior performance over legacy OFs, achieving a 10 %–20 % reduction in End-to-End Delay (EED), a 1 %–2 % increase in Packet Delivery Ratio (PDR), a 10 %–20 % improvement in Network Lifetime (NLT), and a substantial 50 %–80 % decrease in Control Overhead (COH). The paper also presents a smart agriculture case study that illustrates AOF's practical application in optimizing sensor network data routing—a testament to its versatility and practicality. Future endeavours will concentrate on further refining AOF and broadening its application across various IoT domains. |
| format | Article |
| id | doaj-art-a290d2945fce4e4da8773f8db53e5b43 |
| institution | OA Journals |
| issn | 2666-6030 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Journal of Intelligent Networks |
| spelling | doaj-art-a290d2945fce4e4da8773f8db53e5b432025-08-20T02:33:01ZengKeAi Communications Co., Ltd.International Journal of Intelligent Networks2666-60302024-01-01532533910.1016/j.ijin.2024.09.001AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networksAbubakar Wakili0Sara Bakkali1Corresponding author.; Euromed University of Fez, MoroccoEuromed University of Fez, MoroccoWithin the Internet of Things (IoT) ecosystem, the Routing Protocol for Low-Power and Lossy Networks (RPL) serves as a foundational element for network communication. The protocol's effectiveness depends on its Objective Function (OF), which orchestrates route selection based on predefined criteria. However, traditional OFs often struggle to adapt to the dynamic nature of IoT environments. This paper presents the Adaptive Objective Function (AOF), an innovative algorithm designed to dynamically adjust the OF in real-time, responding to fluctuating network conditions and application requirements. AOF comprises: a Network Monitor, an OF Selector, an OF Switcher, and an Event Handler, all working in concert to enhance network performance, reliability, and energy efficiency. Through simulations, AOF has demonstrated superior performance over legacy OFs, achieving a 10 %–20 % reduction in End-to-End Delay (EED), a 1 %–2 % increase in Packet Delivery Ratio (PDR), a 10 %–20 % improvement in Network Lifetime (NLT), and a substantial 50 %–80 % decrease in Control Overhead (COH). The paper also presents a smart agriculture case study that illustrates AOF's practical application in optimizing sensor network data routing—a testament to its versatility and practicality. Future endeavours will concentrate on further refining AOF and broadening its application across various IoT domains.http://www.sciencedirect.com/science/article/pii/S2666603024000320RPLSmart agricultureAdaptive routing protocolsIoT networksPrecision farming technologiesSustainable IoT systems |
| spellingShingle | Abubakar Wakili Sara Bakkali AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks International Journal of Intelligent Networks RPL Smart agriculture Adaptive routing protocols IoT networks Precision farming technologies Sustainable IoT systems |
| title | AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks |
| title_full | AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks |
| title_fullStr | AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks |
| title_full_unstemmed | AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks |
| title_short | AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks |
| title_sort | aof an adaptive algorithm for enhancing rpl objective function in smart agricultural iot networks |
| topic | RPL Smart agriculture Adaptive routing protocols IoT networks Precision farming technologies Sustainable IoT systems |
| url | http://www.sciencedirect.com/science/article/pii/S2666603024000320 |
| work_keys_str_mv | AT abubakarwakili aofanadaptivealgorithmforenhancingrplobjectivefunctioninsmartagriculturaliotnetworks AT sarabakkali aofanadaptivealgorithmforenhancingrplobjectivefunctioninsmartagriculturaliotnetworks |