A Novel Resource Management Framework for Fog Computing by Using Machine Learning Algorithm

2020 ◽  
pp. 42-52
Author(s):  
Shanthi Thangam Manukumar ◽  
Vijayalakshmi Muthuswamy
Keyword(s):  
Machine Learning ◽  
Resource Management ◽  
Mobile Devices ◽  
Service Providers ◽  
Learning Algorithm ◽  
Fog Computing ◽  
Mobile Network ◽  
Resource Provisioning ◽  
Management Framework ◽  
Iot Devices

With the development of edge devices and mobile devices, the authenticated fast access for the networks is necessary and important. To make the edge and mobile devices smart, fast, and for the better quality of service (QoS), fog computing is an efficient way. Fog computing is providing the way for resource provisioning, service providers, high response time, and the best solution for mobile network traffic. In this chapter, the proposed method is for handling the fog resource management using efficient offloading mechanism. Offloading is done based on machine learning prediction technology and also by using the KNN algorithm to identify the nearest fog nodes to offload. The proposed method minimizes the energy consumption, latency and improves the QoS for edge devices, IoT devices, and mobile devices.

Autonomic Trust Management in Cloud-Based and Highly Dynamic IOT Applications

2016 ◽  
Vol 1 (5) ◽  
pp. 26-32
Author(s):  
Suneth Namal ◽  
Hasindu Gamaarachchi ◽  
Gyu Myoung Lee ◽  
Tai-Won Um
Keyword(s):  
Cloud Computing ◽  
Feedback Control ◽  
Internet Of Things ◽  
Life Style ◽  
Trust Management ◽  
Control Loop ◽  
Management Framework ◽  
Iot Applications ◽  
Iot Devices ◽  
The Way

In this paper, we propose an autonomic trust management framework for cloud based and highly dynamic Internet of Things (IoT) applications and services. IoT is creating a world where physical objects are seamlessly integrated in order to provide advanced and intelligent services for humanbeings in their day-to-day life style. Therefore, trust on IoT devices plays an important role in IoT based services and applications. Cloud computing has been changing the way how provides are looking into these issues. Many studies have proposed different techniques to address trust management although non of them addresses autonomic trust management in cloud based highly dynamic IoT systems. To our understanding, IoT cloud ecosystems help to solve many of these issues while enhancing robustness and scalability. On this basis, we came up with an autonomic trust management framework based on MAPE-K feedback control loop to evaluate the level of trust. Finally, we presents the results that verify the effectiveness of this framework.

scholarly journals Intelligent Risk Management framework

2019 ◽  
Vol 8 (3) ◽  
pp. 278
Author(s):  
Wissam ABBASS ◽  
Zineb BAKRAOUY ◽  
Amine BAINA ◽  
Mostafa BELLAFKIH
Keyword(s):  
Risk Management ◽  
Dynamic Structure ◽  
Large Set ◽  
Key Factors ◽  
Iot Security ◽  
Management Framework ◽  
Risk Management Framework ◽  
Risk Management Process ◽  
Iot Devices ◽  
Area Monitoring

The Internet of Things(IoT) is rapidly increasing and enhancing today’s world by introducing a large set of interconnected devices. Several beneficial services are produced by these devices as for area monitoring and process control. However, IoT security is still a major problem. In fact, IoT’ security beggings largely whith an effective Risk Management process. However, the essense of this process is to acquire a risk inventory cibling the IoT devices. Nevertheless, it is quite difficult to obtaining this latter which significantly adds complication issues to the Risk Management.Without the ability of holisticly identify the IoT critical devices, inaccurate Risk Management is achieved which leads unfortunately to novel risk exposures. Traditional Risk-based approaches fails drastically at apprending IoT’ potential attacks. The dynamic structure, the heteregouns nature of devices, the various security objectives and infrastructure pervasiveness are key factors impacting the overall perfomance. Thus, a holistic Risk Management witihin the IoT is indispensable. Accordingly, we propose an intelligent Risk Management framework using Mobile Agents in order to deliver preventive and responsive assessment.

SCIoT: A Secure and sCalable End-to-End Management Framework for IoT Devices

2018 ◽  
pp. 595-617 ◽  
Author(s):  
Moreno Ambrosin ◽  
Mauro Conti ◽  
Ahmad Ibrahim ◽  
Ahmad-Reza Sadeghi ◽  
Matthias Schunter
Keyword(s):  
Management Framework ◽  
End To End ◽  
Iot Devices

Developing and implementing the risk management framework into business processes of Gazprom transgaz Tomsk Ltd., for implementation of the Eastern gas program of PJSC Gazprom

2020 ◽  
Vol 17 (1) ◽  
pp. 68-77
Author(s):  
V. E. Zaikovsky ◽  
A. V. Karev
Keyword(s):  
Risk Management ◽  
Human Resources ◽  
Management Information System ◽  
Business Processes ◽  
Project Success ◽  
Management Information ◽  
Timely Manner ◽  
Project Approach ◽  
Management Framework ◽  
Risk Management Framework

Project success depends on the ability to respond to risks and make correct decisions in a timely manner. The project approach provides a better framework for implementing a new management system into the company’s business processes. The risk management framework developed by the company comprises a risk management infrastructure, a set of standards, human resources, and a risk management information system. To improve staff compliance, it is necessary to provide training and to communicate the goals of the project effectively. It is also important to develop a motivation system because well trained and motivated staff are able to work more efficiently.

Heuristic vs Metaheuristic Method: Improvement of Spoofed Fingerprint Identification in IoT Devices

2019 ◽  
Vol 12 (3) ◽  
pp. 168
Author(s):  
Guruh Fajar Shidik ◽  
Edi Jaya Kusuma ◽  
Safira Nuraisha ◽  
Pulung Nurtantio Andono
Keyword(s):  
Fingerprint Identification ◽  
Iot Devices ◽  
Method Improvement
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