{"title":"AOF:智能农业物联网网络中增强 RPL 目标函数的自适应算法","authors":"Abubakar Wakili, Sara Bakkali","doi":"10.1016/j.ijin.2024.09.001","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":100702,"journal":{"name":"International Journal of Intelligent Networks","volume":"5 ","pages":"Pages 325-339"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666603024000320/pdfft?md5=bf0e841f7517d2e4a59787401fa56ed6&pid=1-s2.0-S2666603024000320-main.pdf","citationCount":"0","resultStr":"{\"title\":\"AOF: An adaptive algorithm for enhancing RPL objective function in smart agricultural IoT networks\",\"authors\":\"Abubakar Wakili, Sara Bakkali\",\"doi\":\"10.1016/j.ijin.2024.09.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":100702,\"journal\":{\"name\":\"International Journal of Intelligent Networks\",\"volume\":\"5 \",\"pages\":\"Pages 325-339\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666603024000320/pdfft?md5=bf0e841f7517d2e4a59787401fa56ed6&pid=1-s2.0-S2666603024000320-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666603024000320\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Networks","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666603024000320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.