scholarly journals Decentralized Trusted Data Sharing Management on Internet of Vehicle Edge Computing (IoVEC) Networks Using Consortium Blockchain

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2410
Author(s):  
Muhammad Firdaus ◽  
Sandi Rahmadika ◽  
Kyung-Hyune Rhee
Keyword(s):  
Data Sharing ◽  
Data Storage ◽  
Traffic Safety ◽  
Network Performance ◽  
Intelligent Transportation System ◽  
Edge Computing ◽  
The Internet ◽  
Smart Vehicles ◽  
The Incentive Mechanism ◽  
Trusted Data

The emergence of the Internet of Vehicles (IoV) aims to facilitate the next generation of intelligent transportation system (ITS) applications by combining smart vehicles and the internet to improve traffic safety and efficiency. On the other hand, mobile edge computing (MEC) technology provides enormous storage resources with powerful computing on the edge networks. Hence, the idea of IoV edge computing (IoVEC) networks has grown to be an assuring paradigm with various opportunities to advance massive data storage, data sharing, and computing processing close to vehicles. However, the participant’s vehicle may be unwilling to share their data since the data-sharing system still relies on a centralized server approach with the potential risk of data leakage and privacy security. In addition, vehicles have difficulty evaluating the credibility of the messages they received because of untrusted environments. To address these challenges, we propose consortium blockchain and smart contracts to accomplish a decentralized trusted data sharing management system in IoVEC. This system allows vehicles to validate the credibility of messages from their neighboring by generating a reputation rating. Moreover, the incentive mechanism is utilized to trigger the vehicles to store and share their data honestly; thus, they will obtain certain rewards from the system. Simulation results substantially display an efficient network performance along with forming an appropriate incentive model to reach a decentralized trusted data sharing management of IoVEC networks.

scholarly journals Improving the Security and Confidentiality in the Internet of Medical Things Based on Edge Computing Using Clustering

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Anita Hatamian ◽  
Mohammad Bagher Tavakoli ◽  
Masoud Moradkhani
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Data Communication ◽  
User Interaction ◽  
Medical Data ◽  
Edge Computing ◽  
Remote Access ◽  
Physiological Data ◽  
The Internet ◽  
Internet Of Medical Things

Families, physicians, and hospital environments use remote patient monitoring (RPM) technologies to remotely monitor a patient’s vital signs, reduce visit time, reduce hospital costs, and improve the quality of care. The Internet of Medical Things (IoMT) is provided by applications that provide remote access to patient’s physiological data. The Internet of Medical Things (IoMT) tools basically have a user interface, biosensor, and Internet connectivity. Accordingly, it is possible to record, transfer, store, and process medical data in a short time by integrating IoMT with the data communication infrastructure in edge computing. (Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. A common misconception is that edge and IoT are synonymous.) But, this approach faces problems with security and intrusion into users’ medical data that are confidential. Accordingly, this study presents a secure solution in order to be used in the IoT infrastructure in edge computing. In the proposed method, first the clustering process is performed effectively using information about the characteristics and interests of users. Then, the people in each cluster evaluated by using edge computing and people with higher scores are considered as influential people in their cluster, and since users with high user interaction can publish information on a large scale, it can be concluded that, by increasing user interaction, information can be disseminated on a larger scale without any intrusion and thus in a safe way in the network. In the proposed method, the average of user interactions and user scores are used as a criterion for identifying influential people in each cluster. If there is a desired number of people who are considered to start disseminating information, it is possible to select people in each cluster with a higher degree of influence to start disseminating information. According to the research results, the accuracy has increased by 0.2 and more information is published in the proposed method than the previous methods.

scholarly journals On Blockchain-Enhanced Secure Data Storage and Sharing in Vehicular Edge Computing Networks

2021 ◽  
Vol 11 (1) ◽  
pp. 414
Author(s):  
Muhammad Firdaus ◽  
Kyung-Hyune Rhee
Keyword(s):  
Data Storage ◽  
Trust Management ◽  
Vehicular Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Intelligent Transportation System ◽  
Single Point ◽  
Edge Computing ◽  
Byzantine Fault Tolerance ◽  
Secure Data

The conventional architecture of vehicular ad hoc networks (VANETs) with a centralized approach has difficulty overcoming the increasing complexity of intelligent transportation system (ITS) applications as well as challenges in providing large amounts of data storage, trust management, and information security. Therefore, vehicular edge computing networks (VECNets) have emerged to provide massive storage resources with powerful computing on network edges. However, a centralized server in VECNets is insufficient due to potential data leakage and security risks as it can still allow a single point of failure (SPoF). We propose consortium blockchain and smart contracts to ensure a trustworthy environment for secure data storage and sharing in the system to address these challenges. Practical byzantine fault tolerance (PBFT) is utilized because it is suitable for consortium blockchain to audit publicly, store data sharing, and records the whole consensus process. It can defend against system failures with or without symptoms to reach an agreement among consensus participants. Furthermore, we use an incentive mechanism to motivate the vehicle to contribute and honestly share their data. The simulation results satisfy the proposed model’s design goals by increasing vehicular networks’ performance in general.

scholarly journals Mobile Edge Computing for the Internet of Vehicles

2021 ◽  
pp. 47-64
Author(s):  
Yan Zhang
Keyword(s):  
Edge Computing ◽  
The Internet ◽  
Vehicular Communication ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Delay Constraints ◽  
Communication Environment ◽  
Artificial Intelligence Technology ◽  
Physical Information ◽  
Computing Framework

AbstractThe advancement of cyber physical information has led to the pervasive use of smart vehicles while enabling various types of powerful mobile applications, which usually require high-intensity processing under strict delay constraints. Given their limited on-board computing capabilities, smart vehicles can offload these processing tasks to edge servers for execution. However, a highly dynamic topology, a complex vehicular communication environment, and edge node heterogeneity pose significant challenges in vehicular edge computing management. To address these challenges, in this chapter we investigate the characteristics of edge computing from both the application and service perspectives and introduce a hierarchical edge computing framework. Moreover, we leverage artificial intelligence technology to propose efficient task offloading and resource scheduling schemes.

scholarly journals Fog Computing and Edge Computing Architectures for Processing Data From Diabetes Devices Connected to the Medical Internet of Things

2017 ◽  
Vol 11 (4) ◽  
pp. 647-652 ◽  
Author(s):  
David C. Klonoff
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Cloud Model ◽  
Fog Computing ◽  
Edge Computing ◽  
Sensor Data ◽  
The Internet ◽  
Privacy And Security ◽  
Continuous Glucose Monitors

The Internet of Things (IoT) is generating an immense volume of data. With cloud computing, medical sensor and actuator data can be stored and analyzed remotely by distributed servers. The results can then be delivered via the Internet. The number of devices in IoT includes such wireless diabetes devices as blood glucose monitors, continuous glucose monitors, insulin pens, insulin pumps, and closed-loop systems. The cloud model for data storage and analysis is increasingly unable to process the data avalanche, and processing is being pushed out to the edge of the network closer to where the data-generating devices are. Fog computing and edge computing are two architectures for data handling that can offload data from the cloud, process it nearby the patient, and transmit information machine-to-machine or machine-to-human in milliseconds or seconds. Sensor data can be processed near the sensing and actuating devices with fog computing (with local nodes) and with edge computing (within the sensing devices). Compared to cloud computing, fog computing and edge computing offer five advantages: (1) greater data transmission speed, (2) less dependence on limited bandwidths, (3) greater privacy and security, (4) greater control over data generated in foreign countries where laws may limit use or permit unwanted governmental access, and (5) lower costs because more sensor-derived data are used locally and less data are transmitted remotely. Connected diabetes devices almost all use fog computing or edge computing because diabetes patients require a very rapid response to sensor input and cannot tolerate delays for cloud computing.

scholarly journals Moisture Computing-Based Internet of Vehicles (IoV) Architecture for Smart Cities

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3785
Author(s):  
Ali Tufail ◽  
Abdallah Namoun ◽  
Adnan Ahmed Abi Sen ◽  
Ki-Hyung Kim ◽  
Ahmed Alrehaili ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Traffic Monitoring ◽  
Edge Computing ◽  
Small Scale ◽  
The Internet ◽  
Cloud Infrastructure ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Scale Data

Recently, the concept of combining ‘things’ on the Internet to provide various services has gained tremendous momentum. Such a concept has also impacted the automotive industry, giving rise to the Internet of Vehicles (IoV). IoV enables Internet connectivity and communication between smart vehicles and other devices on the network. Shifting the computing towards the edge of the network reduces communication delays and provides various services instantly. However, both distributed (i.e., edge computing) and central computing (i.e., cloud computing) architectures suffer from several inherent issues, such as high latency, high infrastructure cost, and performance degradation. We propose a novel concept of computation, which we call moisture computing (MC) to be deployed slightly away from the edge of the network but below the cloud infrastructure. The MC-based IoV architecture can be used to assist smart vehicles in collaborating to solve traffic monitoring, road safety, and management issues. Moreover, the MC can be used to dispatch emergency and roadside assistance in case of incidents and accidents. In contrast to the cloud which covers a broader area, the MC provides smart vehicles with critical information with fewer delays. We argue that the MC can help reduce infrastructure costs efficiently since it requires a medium-scale data center with moderate resources to cover a wider area compared to small-scale data centers in edge computing and large-scale data centers in cloud computing. We performed mathematical analyses to demonstrate that the MC reduces network delays and enhances the response time in contrast to the edge and cloud infrastructure. Moreover, we present a simulation-based implementation to evaluate the computational performance of the MC. Our simulation results show that the total processing time (computation delay and communication delay) is optimized, and delays are minimized in the MC as apposed to the traditional approaches.

New Trends in Digital Data Storage for the Internet of Things

2018 ◽  
Vol 6 (3) ◽  
pp. 359-363
Author(s):  
A. Saxena ◽  
◽  
S. Sharma ◽  
S. Dangi ◽  
A. Sharma ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Digital Data ◽  
The Internet ◽  
Digital Data Storage ◽  
The Internet Of Things

scholarly journals Blockchain-Based Solutions for UAV-Assisted Connected Vehicle Networks in Smart Cities: A Review, Open Issues, and Future Perspectives

Telecom ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 108-140
Author(s):  
Paulo Álvares ◽  
Lion Silva ◽  
Naercio Magaia
Keyword(s):  
Traffic Congestion ◽  
Resource Constraints ◽  
Smart Cities ◽  
The Internet ◽  
Connected Vehicle ◽  
Sensitive Data ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Security Properties ◽  
Vehicle Networks

It had been predicted that by 2020, nearly 26 billion devices would be connected to the Internet, with a big percentage being vehicles. The Internet of Vehicles (IoVa) is a concept that refers to the connection and cooperation of smart vehicles and devices in a network through the generation, transmission, and processing of data that aims at improving traffic congestion, travel time, and comfort, all the while reducing pollution and accidents. However, this transmission of sensitive data (e.g., location) needs to occur with defined security properties to safeguard vehicles and their drivers since attackers could use this data. Blockchain is a fairly recent technology that guarantees trust between nodes through cryptography mechanisms and consensus protocols in distributed, untrustful environments, like IoV networks. Much research has been done in implementing the former in the latter to impressive results, as Blockchain can cover and offer solutions to many IoV problems. However, these implementations have to deal with the challenge of IoV node’s resource constraints since they do not suffice for the computational and energy requirements of traditional Blockchain systems, which is one of the biggest limitations of Blockchain implementations in IoV. Finally, these two technologies can be used to build the foundations for smart cities, enabling new application models and better results for end-users.

scholarly journals Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 955
Author(s):  
Zhiyuan Li ◽  
Ershuai Peng
Keyword(s):  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Dynamic Network ◽  
Parameter Tuning ◽  
Global Optimum ◽  
Research Field ◽  
Edge Computing ◽  
Transmission Delay ◽  
Smart Vehicles ◽  
Network Bandwidth

With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.

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