scholarly journals Edge and Fog Computing in Healthcare – A Review

2019 ◽  
Vol 20 (2) ◽  
pp. 191-206 ◽  
Author(s):  
Sujata Dash ◽  
Sitanath Biswas ◽  
Debajit Banerjee ◽  
Atta UR Rahman
Keyword(s):  
Healthcare System ◽  
Fog Computing ◽  
Edge Computing ◽  
Wireless Devices ◽  
Privacy Concerns ◽  
Health Care Informatics ◽  
Trade Offs ◽  
Architectural Framework ◽  
Edge And Fog Computing ◽  
Care Informatics

The architectural framework of Fog and edge computing reveals that the network components which lie between the cloud and devices computes application oriented operations. In this paper, an in-depth review of fog and mist computing in the area of health care informatics is analyzed, classified, and discussed various applications cited in the literature. For that purpose, applications are classified into different categories and a list of application-oriented tasks that can be handled by fog and edge computing are enlisted. It is further added that on which layer of the network system such fog and edge computing tasks can be computed and trade-offs with respect to requirements relevant to healthcare are provided. The review undertaken in this paper focuses on three important areas: firstly, the enormous amount of computing tasks of healthcare system can take mileage of these two computing principles; secondly, the limitation of wireless devices can be overcome by having higher network tiers which can execute tasks and aggregate the data; and thirdly, privacy concerns and dependability prevent computation tasks to completely move to the cloud. Another area which has been considered in the study is how Edge and Fog computing can make the security algorithms more efficient. The findings of the study provide evidence of the need for a logical and consistent approach towards fog and mist computing in healthcare system.

scholarly journals A Data-driven Platform for Simulating Vehicular Fog Computing Environment

2022 ◽  
Author(s):  
Ozgur Umut Akgul ◽  
Wencan Mao ◽  
Byungjin Cho ◽  
Yu Xiao
Keyword(s):  
Capacity Planning ◽  
Fog Computing ◽  
Deep Understanding ◽  
Temporal Variations ◽  
Edge Computing ◽  
Business Strategies ◽  
Open Platform ◽  
Trade Offs ◽  
Spatio Temporal ◽  
Computing Capacity

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

scholarly journals Deployment of IoT Edge and Fog Computing Technologies to Develop Smart Building Services

2018 ◽  
Vol 10 (11) ◽  
pp. 3832 ◽  
Author(s):  
Francisco-Javier Ferrández-Pastor ◽  
Higinio Mora ◽  
Antonio Jimeno-Morenilla ◽  
Bruno Volckaert
Keyword(s):  
Fog Computing ◽  
Edge Computing ◽  
Climate Control ◽  
Embedded Devices ◽  
Computing Systems ◽  
Smart Building ◽  
Computing Paradigm ◽  
Novel Approach ◽  
Edge And Fog Computing ◽  
Building Designs

Advances in embedded systems, based on System-on-a-Chip (SoC) architectures, have enabled the development of many commercial devices that are powerful enough to run operating systems and complex algorithms. These devices integrate a set of different sensors with connectivity, computing capacities and cost reduction. In this context, the Internet of Things (IoT) potential increases and introduces other development possibilities: “Things” can now increase computation near the source of the data; consequently, different IoT services can be deployed on local systems. This paradigm is known as “edge computing” and it integrates IoT technologies and cloud computing systems. Edge computing reduces the communications’ bandwidth needed between sensors and the central data centre. Management of sensors, actuators, embedded devices and other resources that may not be continuously connected to a network (such as smartphones) are required for this method. This trend is very attractive for smart building designs, where different subsystems (energy, climate control, security, comfort, user services, maintenance, and operating costs) must be integrated to develop intelligent facilities. In this work, a method to design smart services based on the edge computing paradigm is analysed and proposed. This novel approach overcomes some drawbacks of existing designs related to interoperability and scalability of services. An experimental architecture based on embedded devices is described. Energy management, security system, climate control and information services are the subsystems on which new smart facilities are implemented.

Recent Advances in Edge Computing Paradigms

2021 ◽  
Vol 4 (1) ◽  
pp. 37-51
Author(s):  
Sana Sodanapalli ◽  
Hewan Shrestha ◽  
Chandramohan Dhasarathan ◽  
Puviyarasi T. ◽  
Sam Goundar
Keyword(s):  
Network Architecture ◽  
Fog Computing ◽  
Minimum Cost ◽  
Workplace Safety ◽  
Edge Computing ◽  
New Approach ◽  
Data Source ◽  
Edge And Fog Computing ◽  
New Research ◽  
And Storage

Edge computing is an exciting new approach to network architecture that helps organizations break beyond the limitations imposed by traditional cloud-based networks. It has emerged as a viable and important architecture that supports distributed computing to deploy compute and storage resources closer to the data source. Edge and fog computing addresses three principles of network limitations of bandwidth, latency, congestion, and reliability. The research community sees edge computing at manufacturing, farming, network optimization, workplace safety, improved healthcare, transportation, etc. The promise of this technology will be realized through addressing new research challenges in the IoT paradigm and the design of highly-efficient communication technology with minimum cost and effort.

scholarly journals An Overview of Fog Computing and Edge Computing Security and Privacy Issues

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8226
Author(s):  
Ahmed M. Alwakeel
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Edge Computing ◽  
Security And Privacy ◽  
Local Network ◽  
Security Issues ◽  
Computing Paradigm ◽  
Edge And Fog Computing ◽  
Cloud Technologies ◽  
Privacy Issues

With the advancement of different technologies such as 5G networks and IoT the use of different cloud computing technologies became essential. Cloud computing allowed intensive data processing and warehousing solution. Two different new cloud technologies that inherit some of the traditional cloud computing paradigm are fog computing and edge computing that is aims to simplify some of the complexity of cloud computing and leverage the computing capabilities within the local network in order to preform computation tasks rather than carrying it to the cloud. This makes this technology fits with the properties of IoT systems. However, using such technology introduces several new security and privacy challenges that could be huge obstacle against implementing these technologies. In this paper, we survey some of the main security and privacy challenges that faces fog and edge computing illustrating how these security issues could affect the work and implementation of edge and fog computing. Moreover, we present several countermeasures to mitigate the effect of these security issues.

scholarly journals A Data-driven Platform for Simulating Vehicular Fog Computing Environment

2022 ◽  
Author(s):  
Ozgur Umut Akgul ◽  
Wencan Mao ◽  
Byungjin Cho ◽  
Yu Xiao
Keyword(s):  
Capacity Planning ◽  
Fog Computing ◽  
Deep Understanding ◽  
Temporal Variations ◽  
Edge Computing ◽  
Business Strategies ◽  
Open Platform ◽  
Trade Offs ◽  
Spatio Temporal ◽  
Computing Capacity

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

Edge and Fog Computing Enabled AI for IoT-An Overview

2019 ◽  
Author(s):  
Zhuo Zou ◽  
Yi Jin ◽  
Paavo Nevalainen ◽  
Yuxiang Huan ◽  
Jukka Heikkonen ◽  
...  
Keyword(s):  
Fog Computing ◽  
Edge And Fog Computing

scholarly journals Implementation analysis of IoT-based offloading frameworks on cloud/edge computing for sensor generated big data

2021 ◽  
Author(s):  
Karan Bajaj ◽  
Bhisham Sharma ◽  
Raman Singh
Keyword(s):  
High Speed ◽  
Smart Cities ◽  
Fog Computing ◽  
Edge Computing ◽  
Computation Offloading ◽  
Performance Parameters ◽  
Iot Applications ◽  
Time Sensitivity ◽  
Implementation Analysis ◽  
Increasing Demand

AbstractThe Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not possible to process all the data on the devices itself. The data collected by the device sensors are in vast amount and require high-speed computation and processing, which demand advanced resources. Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet these performance parameters and extreme computation requirements. Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications. In this paper, the role of context or situation to perform the offloading is studied and drawn to a conclusion, that to meet the performance requirements of IoT enabled services, context-based offloading can play a crucial role. Some of the existing frameworks EMCO, MobiCOP-IoT, Autonomic Management Framework, CSOS, Fog Computing Framework, based on their novelty and optimum performance are taken for implementation analysis and compared with the MAUI, AnyRun Computing (ARC), AutoScaler, Edge computing and Context-Sensitive Model for Offloading System (CoSMOS) frameworks. Based on the study of drawn results and limitations of the existing frameworks, future directions under offloading scenarios are discussed.

scholarly journals Network governance forms in healthcare: empirical evidence from two Italian cancer networks

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Anna Romiti ◽  
Mario Del Vecchio ◽  
Gino Sartor
Keyword(s):  
Healthcare System ◽  
Governance Structure ◽  
Network Governance ◽  
Public Healthcare ◽  
Structured Interviews ◽  
General Validity ◽  
Regional Administration ◽  
Trade Offs ◽  
Italian Regions ◽  
Cancer Networks

Abstract Background This study focuses on the application of Provan and Kenis’ modes of network governance to the specific field of public healthcare networks, extending the framework to an analysis of systems in which networks are involved. Thus, the aim of this study is to analyze and compare the governance of two cancer networks in two Italian regions that underwent system reconfiguration processes due to reforms in the healthcare system. Methods A qualitative study of two clinical networks in the Italian healthcare system was conducted. The sample for interviews included representatives of the regional administration (n = 4), network coordinators (n = 6), and general and clinical directors of health organizations involved in the two networks (n = 25). Data were collected using semi-structured interviews. Results Our study shows that healthcare system reforms have a limited impact on network governance structures. In fact, strong inertial tendencies characterize networks, especially network administrative organization models (NAO). Networks tend to find their own balance with respect to the trade-offs analyzed using a mix of formal and informal ties. Our study confirms the general validity of Provan and Kenis’ framework and shows how other specific factors and contingencies may affect the possibility that cancer networks find positive equilibria between competing needs of inclusivity and efficiency, internal and external legitimacy, and stability and flexibility. It also shows how networks react to external changes. Conclusions Our study shows the importance of considering three factors and contingencies that may affect network effectiveness: a) the importance of looking at network governance modes not in isolation, but in relationship to the governance of regional systems; b) the influence of a specific network’s governance structure on the network’s ability to respond to tensions and to achieve its goals; and c) the need to take into account the role of professionals in network governance.

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