Trust Aware Multi-Objective Metaheuristic Optimization Based Secure Route Planning Technique for Cluster Based IIoT Environment

Nagappan, Krishnaraj; Rajendran, Surendran; Alotaibi, Youseef

doi:10.1109/access.2022.3211971

Cited by 21 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study develops a trust-aware multi objective metaheuristic optimization-based secure clustering with route planning (TAMOMO-SCRP) technique for a cluster-based IIoT environment [30]. This is a feature-based approach, in which camera movement is detected using the inconsistency of image features in sequential image streams, as in PTAM [31] and ORB-SLAM [32].…”

Section: Literature Reviewmentioning

confidence: 99%

Telepresence Robot with DRL Assisted Delay Compensation in IoT-Enabled Sustainable Healthcare Environment

2023

View full text Add to dashboard Cite

Telepresence robots have become popular during the COVID-19 era due to the quarantine measures and the requirement to interact less with other humans. Telepresence robots are helpful in different scenarios, such as healthcare, academia, or the exploration of certain unreachable territories. IoT provides a sensor-based environment wherein robots acquire more precise information about their surroundings. Remote telepresence robots are enabled with more efficient data from IoT sensors, which helps them to compute the data effectively. While navigating in a distant IoT-enabled healthcare environment, there is a possibility of delayed control signals from a teleoperator. We propose a human cooperative telecontrol robotics system in an IoT-sensed healthcare environment. The deep reinforcement learning (DRL)-based deep deterministic policy gradient (DDPG) offered improved control of the telepresence robot to provide assistance to the teleoperator during the delayed communication control signals. The proposed approach can stabilize the system in aid of the teleoperator by taking the delayed signal term out of the main controlling framework, along with the sensed IOT infrastructure. In a dynamic IoT-enabled healthcare context, our suggested approach to operating the telepresence robot can effectively manage the 30 s delayed signal. Simulations and physical experiments in a real-time healthcare environment with human teleoperators demonstrate the implementation of the proposed method.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Telepresence Robot with DRL Assisted Delay Compensation in IoT-Enabled Sustainable Healthcare Environment

2023

View full text Add to dashboard Cite

show abstract

“…End if End for Data compression is used to reduce network bandwidth usage and increase efficiency [29,30]. Either Lossless or lossy algorithms can be used for data compression; however, when compared to lossy techniques, the lossless approach appears to be a better fit for our e-health application.…”

Section: Encryptionmentioning

confidence: 99%

SFoG-RPI: A Secured QoS Aware and Load Balancing Framework for FoG Computing in Healthcare Paradigm

Gunasekar,

Krishnamurthy,

Thanarajan

et al. 2023

RIA

View full text Add to dashboard Cite

Diabetes, characterized by persistently high blood glucose levels, has been identified as a hazardous health condition, potentially leading to severe complications such as heart attacks, strokes, and heart failure. This study introduces a fog-based remote health monitoring system designed to mitigate the devastating impacts of diabetes and hypoglycemia. This system persistently monitors health parameters including glucose levels, carbohydrate intake, physical activities, heart rate, and blood pressure. It additionally supports advanced services such as feature extraction, distributed local storage, and enhanced security. The traditional cloud-based architecture, while effective, often results in significant latency due to the processing of vast amounts of data. By bringing computing servers closer to users, Fog computing addresses this issue, reducing latency, and increasing security, resource accessibility, and on-demand scaling. In this context, the proposed system aims to minimize latency and network usage while addressing critical issues such as security, access control, and privacy. It employs lossy data compression at the gateway level to decrease network bandwidth and enhance efficiency. Furthermore, the system introduces a novel Load Balancing mechanism to distribute the load among fog nodes evenly. It utilizes lightweight cryptographic algorithms, efficient key exchange protocols, and digital signatures to ensure confidentiality, authentication, and user privacy. The performance of the proposed framework was evaluated in terms of average processing time, energy consumption management, computational resource distribution, latency, and network usage. When compared with other systems, the proposed framework demonstrated superior results, thus validating its effectiveness.

show abstract

“…VANETs can route ambulances and rescue teams to accident scenes, speeding emergency response. This research examines reliable emergency communication protocols, first responder system integration, and emergency response coordination [2]. This demand has been brought about by the acceleration of urbanization.…”

Section: Introductionmentioning

confidence: 99%

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Alotaibi,

Rajasekar,

Jayalakshmi

et al. 2024

CMC

View full text Add to dashboard Cite

Rapid development in Information Technology (IT) has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle (V2V) transmission. Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data. The communication occurs directly between V2V and Base Station (BS) units such as the Road Side Unit (RSU), named as a Vehicle to Infrastructure (V2I). However, the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time. Therefore, the scheme of an effectual routing protocol for reliable and stable communications is significant. Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment. Therefore, this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing (FOA-EECPCR) technique in VANETS. The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET. To accomplish this, the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy, distance, and trust level. For the routing process, the Sparrow Search Algorithm (SSA) is derived with a fitness function that encompasses two variables, namely, energy and distance. A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method. The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

show abstract

Trust Aware Multi-Objective Metaheuristic Optimization Based Secure Route Planning Technique for Cluster Based IIoT Environment

Cited by 21 publications

References 26 publications

Telepresence Robot with DRL Assisted Delay Compensation in IoT-Enabled Sustainable Healthcare Environment

Telepresence Robot with DRL Assisted Delay Compensation in IoT-Enabled Sustainable Healthcare Environment

SFoG-RPI: A Secured QoS Aware and Load Balancing Framework for FoG Computing in Healthcare Paradigm

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Contact Info

Product

Resources

About