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Research Topics in Design and Analysis of RPL Objective Functions

Research Topics in Design and Analysis of RPL Objective Functions

Masters and PhD Research Topics in Design and Analysis of RPL Objective Functions

The IoT applications implement the Routing protocol for low-power and lossy networks, RPLs in the routing layer. The RPL protocol connects IoT devices through multi-hop paths to the root node, responsible for collecting and distributing the sensed data. The RPL accounts for Objective Functions (OFs) to construct the Destination Oriented Directed Acyclic Graph (DODAG) to the root node. The OF optimizes the route to the destination in the perspective of communication reliability, energy conservation, or security. The lifetime of IoT devices mainly depends on the selection of the OFs.

The OF accounts for the metrics of Packet Delivery Ratio (PDR), the Expected Transmission Count (ETX), remaining energy, and security-related metrics by separately or combinable to select the best parent towards the root.

By default, the RPL has no security mechanism, so it is a vulnerable protocol to several types of attacks. The security pitfalls in RPL enforce the attackers to disrupt communication and make the RPL invaluable in IoT smart applications. It is imperative to design reliable and secure OFs for RPL for IoT networks.

Some of the potential research topics in the design of RPL objective functions are discussed below:
A new RPL objective functions to support various IoT (Internet of Things) applications such as smart city, smart agriculture, and industrial IoT.
Comparison of different RPL objective functions in terms of energy efficiency, network scalability, and data delivery reliability.
Study of the trade-off between energy consumption and data delivery reliability in RPL networks and the development of objective functions that balance these two metrics.
Investigation of the impact of network heterogeneity on RPL performance and the design of objective functions that account for heterogeneity.
Development of RPL objective functions that consider Quality of Service (QoS) requirements for various IoT applications.
Design of secure RPL objective functions to protect against attacks on RPL networks.
Exploration of the use of machine learning algorithms in the design of RPL objective functions to optimize network performance dynamically.
Investigation of the impact of network dynamics on the performance of RPL objective functions and the design of robust objective functions for dynamic networks.