OF-ECF: A New Optimization of the Objective Function for Parent Selection in RPL

Lamaazi, Hanane; Ahmadi, Adnan El; Benamar, Nabil; Jara, Antonio J.

doi:10.1109/wimob.2019.8923273

Cited by 17 publications

(7 citation statements)

References 19 publications

(23 reference statements)

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“…The authors in [164] provide a versatile objective function. The data forwarder is selected based on a combination of forwarding delay, ETX, and EC criteria for applications that require real-time data exchange, data durability, and energy efficiency.…”

Section: Available Improvements For Rpl Using Intelligencementioning

confidence: 99%

A Review of Intrusion Detection Systems in RPL Routing Protocol Based on Machine Learning for Internet of Things Applications

Seyfollahi

Ghaffari

2021

Wireless Communications and Mobile Computing

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IPv6 routing protocol for low-power and lossy networks (RPL) has been developed as a routing agent in low-power and lossy networks (LLN), where nodes’ resource constraint nature is challenging. This protocol operates at the network layer and can create routing and optimally distribute routing information between nodes. RPL is a low-power, high-throughput IPv6 routing protocol that uses distance vectors. Each sensor-to-wire network router has a collection of fixed parents and a preferred parent on the path to the Destination-oriented directed acyclic graph (DODAG) graph’s root in steady-state. Each router part of the graph sends DODAG information object (DIO) control messages and specifies its rank within the graph, indicating its position within the network relative to the root. When a node receives a DIO message, it determines its network rank, which must be higher than all its parents’ rank, and then continues sending DIO messages using the trickle timer. As a result, DODAG begins at the root and eventually extends to encompass the whole network. This paper is the first review to study intrusion detection systems in the RPL protocol based on machine learning (ML) techniques to the best of our knowledge. The complexity of the new attack models identified for RPL and the efficiency of ML in intelligent and collaborative threats detection, and the issues of deploying ML in challenging LLN environments underscore the importance of research in this area. The analysis is done using research sources of “Google Scholar,” “Crossref,” “Scopus,” and “Web of Science” resources. The evaluations are assessed for studies from 2016 to 2021. The results are illustrated with tables and figures.

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Section: Available Improvements For Rpl Using Intelligencementioning

confidence: 99%

A Review of Intrusion Detection Systems in RPL Routing Protocol Based on Machine Learning for Internet of Things Applications

Seyfollahi

Ghaffari

2021

Wireless Communications and Mobile Computing

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“…Lamaazi and Benamar [166], Lamaazi et al [167] had considered fuzzy logic to improve energy efficiency. In their next work they had proposed a new objective function to choose the best parent using Routing Protocol for Low Power and Lossy Networks (RPL).…”

Section: Energy Qosmentioning

confidence: 99%

Accessible review of internet of vehicle models for intelligent transportation and research gaps for potential future directions

Garg

Mehrotra

Pandey

et al. 2021

Peer-to-Peer Netw. Appl.

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This paper presents a state-of-the-art review of various models of Internet of Vehicles (IoV) that were proposed to revolutionize the transportation and automation industry. In the last few years, IoV technology has emerged as a global revolution, demonstrating considerable impact upon the transportation and automation industry, hence, the interest of the researchers bends towards the utility of the IoV technology which motivated us to present a comprehensive review. This paper, thus, collates recent findings along with some anticipated applications of IoV technologies for transportation. It brings to light the evolution of the IoV studies referred as models for transportation since its birth and aims to present a deep insightful review of various IoV technologies with their strengths and weaknesses. The reviewed literature is organized systematically to give a categorical overview of recent developments. This article also discusses the outstanding potentialities and challenges that exist in transportation from IoV perspective with the belief that these will have the capacity to be addressed in the near future. As there is no review literature on IoV technology available for transportation. Hence, we strongly believe that this study will be useful and enable the researchers to utilize IoV technologies to solve complex outstanding problems in transportation and automation. Keywords Internet of vehicles . V2X . network . Energy efficiency . Big data . QoS 1 IoV is abbreviated as Internet of Vehicles which has also been referred to by various names like ICV (Internet Connected Vehicles) or CV (Connected Vehicles) or AUV (Autonomous Vehicles) by other academicians. 2 V2X represents V2V, V2I, V2H, V2R and V2C which is also referred to as V2α by other academicians.

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“…In the paper [22], using the additive composition approach, the protocol proposes a new flexible Objective Function dependent on Consumed power, ETX, and Forwarding delay (OF-ECF). This method allows for the development of a new composite metric that nodes use to choose the right parent.…”

Section: Related Workmentioning

confidence: 99%

Improved RPL Protocol for Low-Power and Lossy Network for IoT Environment

Hadaya

Alabady

2021

SN COMPUT. SCI.

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The routing protocol for low-power and lossy networks (RPL) has gained considerable popularity in the research community with the advent of the Internet of Things (IoT), primarily because of its versatility to cope with various network topologies and its ability to offer features such as self-healing, auto-configuration, detection, and loop avoidance. The objective function (OF) of the RPL calculates the ranks of nodes in the network depending on one routing metric, and then selects and optimizes the routes. Because of the single metric, both MRHOF and OF0 will suffer from long hops when selecting the routes to the sink, selecting inefficient routes such as paths containing nodes with small residual energy may cause the nod's energy to be consumed faster than other nodes. The other problem with RPL is the unbalanced choice of parents that make bottleneck nodes that cause more network delay and high packet loss ratio because of the high congestion nodes, especially the nodes located near the sink node. In this paper, we first reviewed the proposed objective functions and then suggested an improvement in the RPL objective function that considers three metrics (load, residual energy, and ETX metrics) instead of only one metric. The tool used in this paper is the Cooja simulator, we took three scenarios, and we compared the results of the proposed protocol with the original RPL MRHOF objective function; the results showed that the proposed protocol succeeded to enhance the RPL protocol in term of PDR, packet loss ratio, and total power consumption. The best performance of the proposed protocol is shown in the network with 60 nodes, and the proposed protocol increased the PDR by 0.4059, decreased the packet loss ratio by 0.21015, and decreased the total power consumption by 132.16 mw compared with the MRHOF protocol.

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OF-ECF: A New Optimization of the Objective Function for Parent Selection in RPL

Cited by 17 publications

References 19 publications

A Review of Intrusion Detection Systems in RPL Routing Protocol Based on Machine Learning for Internet of Things Applications

A Review of Intrusion Detection Systems in RPL Routing Protocol Based on Machine Learning for Internet of Things Applications

Accessible review of internet of vehicle models for intelligent transportation and research gaps for potential future directions

Improved RPL Protocol for Low-Power and Lossy Network for IoT Environment

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