scholarly journals A Survey on Internet of Things and Cloud Computing for Healthcare

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 768 ◽  
Author(s):  
L. Minh Dang ◽  
Md. Jalil Piran ◽  
Dongil Han ◽  
Kyungbok Min ◽  
Hyeonjoon Moon
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Assisted Living ◽  
Data Exchange ◽  
Fog Computing ◽  
Ambient Assisted Living ◽  
Healthcare Industry ◽  
Healthcare Applications ◽  
Privacy And Security

The fast development of the Internet of Things (IoT) technology in recent years has supported connections of numerous smart things along with sensors and established seamless data exchange between them, so it leads to a stringy requirement for data analysis and data storage platform such as cloud computing and fog computing. Healthcare is one of the application domains in IoT that draws enormous interest from industry, the research community, and the public sector. The development of IoT and cloud computing is improving patient safety, staff satisfaction, and operational efficiency in the medical industry. This survey is conducted to analyze the latest IoT components, applications, and market trends of IoT in healthcare, as well as study current development in IoT and cloud computing-based healthcare applications since 2015. We also consider how promising technologies such as cloud computing, ambient assisted living, big data, and wearables are being applied in the healthcare industry and discover various IoT, e-health regulations and policies worldwide to determine how they assist the sustainable development of IoT and cloud computing in the healthcare industry. Moreover, an in-depth review of IoT privacy and security issues, including potential threats, attack types, and security setups from a healthcare viewpoint is conducted. Finally, this paper analyzes previous well-known security models to deal with security risks and provides trends, highlighted opportunities, and challenges for the IoT-based healthcare future development.

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 A Novel Fog-IoT based Framework for Improving Performance of Cloud Computing

2019 ◽  
Vol 8 (12S) ◽  
pp. 889-895
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Secure Communication ◽  
Fog Computing ◽  
Cloud Service ◽  
Raspberry Pi ◽  
New Paradigm ◽  
Privacy And Security ◽  
Security Issues ◽  
Iot Devices

Internet-of-Things (IoT) has been considered as a fundamental part of our day by day existence with billions of IoT devices gathering information remotely and can interoperate within the current Internet framework. Fog computing is nothing but cloud computing to the extreme of network security. It provides computation and storage services via CSP (Cloud Service Provider) to end devices in the Internet of Things (IoT). Fog computing allows the data storing and processing any nearby network devices or nearby cloud endpoint continuum. Using fog computing, the designer can reduce the computation architecture of the IoT devices. Unfortunitily, this new paradigm IoT-Fog faces numerous new privacy and security issues, like authentication and authorization, secure communication, information confidentiality. Despite the fact that the customary cloud-based platform can even utilize heavyweight cryptosystem to upgrade security, it can't be performed on fog devices drectly due to reseource constraints. Additionally, a huge number of smart fog devices are fiercely disseminated and situated in various zones, which expands the danger of being undermined by some pernicious gatherings. Trait Based Encryption (ABE) is an open key encryption conspire that enables clients to scramble and unscramble messages dependent on client qualities, which ensures information classification and hearty information get to control. Be that as it may, its computational expense for encryption and unscrambling stage is straightforwardly corresponding to the multifaceted nature of the arrangements utilized. The points is to assess the planning, CPU burden, and memory burden, and system estimations all through each phase of the cloud-to-things continuum amid an analysis for deciding highlights from a finger tapping exercise for Parkinson's Disease patients. It will be appeared there are confinements to the proposed testbeds when endeavoring to deal with upwards of 35 customers at the same time. These discoveries lead us to a proper conveyance of handling the leaves the Intel NUC as the most suitable fog gadget. While the Intel Edison and Raspberry Pi locate a superior balance at in the edge layer, crossing over correspondence conventions and keeping up a self-mending network topology for "thing" devices in the individual territory organize.

A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things

2016 ◽  
Vol 29 (11) ◽  
pp. e4043 ◽  
Author(s):  
Berto de Tácio Pereira Gomes ◽  
Luiz Carlos Melo Muniz ◽  
Francisco José da Silva e Silva ◽  
Luis Eduardo Talavera Ríos ◽  
Markus Endler
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Assisted Living ◽  
Ambient Assisted Living

Adaptive mobile Web server framework for Mist computing in the Internet of Things

2018 ◽  
Vol 14 (3/4) ◽  
pp. 247-267 ◽  
Author(s):  
Mohan Liyanage ◽  
Chii Chang ◽  
Satish Narayana Srirama
Keyword(s):  
Internet Of Things ◽  
Assisted Living ◽  
Fog Computing ◽  
Ambient Assisted Living ◽  
Base Station ◽  
Content Type ◽  
The Real ◽  
Platform As A Service ◽  
Station Grid ◽  
And Performance

Purpose The distant data centre-centric Internet of Things (IoT) systems face the latency issue especially in the real-time-based applications, such as augmented reality, traffic analytics and ambient assisted living. Recently, Fog computing models have been introduced to overcome the latency issue by using the proximity-based computational resources, such as the computers co-located with the cellular base station, grid router devices or computers in local business. However, the increasing users of Fog computing servers cause bottleneck issues and consequently the latency issue arises again. This paper aims to introduce the utilisation of Mist computing (Mist) model, which exploits the computational and networking resources from the devices at the very edge of the IoT networks. Design/methodology/approach This paper proposes a service-oriented mobile-embedded Platform as a Service (mePaaS) framework that allows the mobile device to provide a flexible platform for proximal users to offload their computational or networking program to mePaaS-based Mist computing node. Findings The prototype has been tested and performance has been evaluated on the real-world devices. The evaluation results have shown the promising nature of mePaaS. Originality/value The proposed framework supports resource-aware autonomous service configuration that can manage the availability of the functions provided by the Mist node based on the dynamically changing hardware resource availability. In addition, the framework also supports task distribution among a group of Mist nodes.

scholarly journals A Comprehensive Study of Caching Effects on Fog Computing Performance

2021 ◽  
pp. 1-18
Author(s):  
Marwa Mahfodh Abdulqadir ◽  
Azar Abid Salih ◽  
Omar M. Ahmed ◽  
Dathar Abas Hasan ◽  
Lailan M. Haji ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Fog Computing ◽  
Middle Layer ◽  
Fast Response ◽  
The Internet ◽  
Main Task ◽  
Reference Architecture ◽  
The Internet Of Things

The rapid advancement in the Internet of things applications generates a considerable amount of data and requires additional computing power. These are serious challenges that directly impact the performance, latency, and network breakdown of cloud computing. Fog Computing can be depended on as an excellent solution to overcome some related problems in cloud computing. Fog computing supports cloud computing to become nearer to the Internet of Things. The fog's main task is to access the data generated by the IoT devices near the edge. The data storage and data processing are performed locally at the fog nodes instead of achieving that at cloud servers. Fog computing presents high-quality services and fast response time. Therefore, Fog computing can be the best solution for the Internet of things to present a practical and secure service for various clients. Fog computing enables sufficient management for the services and resources by keeping the devices closer to the network edge. In this paper, we review various computing paradigms, features of fog computing, an in-depth reference architecture of fog with its various levels, a detailed analysis of fog with different applications, various fog system algorithms, and also systematically examines the challenges in Fog Computing which act as a middle layer between IoT sensors or devices and data centers of the cloud.

Toward an efficient healthcare CloudIoT architecture by using a game theory approach

2019 ◽  
Vol 27 (3) ◽  
pp. 189-200 ◽  
Author(s):  
Douglas Dyllon Jeronimo de Macedo ◽  
Gustavo Medeiros de Araújo ◽  
Moisés Lima Dutra ◽  
Silvana Toriani Dutra ◽  
Álvaro Guillermo Rojas Lezana
Keyword(s):  
Game Theory ◽  
Internet Of Things ◽  
Assisted Living ◽  
Search Algorithm ◽  
Ambient Assisted Living ◽  
Stochastic Search ◽  
The Internet ◽  
Theory Approach ◽  
Healthcare Applications ◽  
The Internet Of Things

The increasing adoption of the Internet of things and cloud computing in recent years provided the increasing development and improvement of various well-known approaches, such as the ambient assisted living approach. The merging of Internet of things and cloud brought about the so-called CloudIoT paradigm. CloudIoT intends to extend both technologies to make possible developing the next generation of smart environments, such as healthcare applications. New healthcare applications demand an increasing capacity of resources for storing, processing, and transmitting data. Looking at this scenario, along with the growing number of devices connected to the Internet of things, we must consider providing mechanisms to mitigate the excessive data offloading on the network, the latency between nodes, and even the unnecessary waste of computing power. In this article, we present an efficient and effective CloudIoT-based healthcare architecture for ambient assisted living environments. The innovation of our approach lies on the use of a game theory approach (by means of a stochastic search algorithm) to improve efficiency and latency of the CloudIoT network. This proposal aims to provide better availability levels to the whole environment. Experiments performed through simulation have shown us a remarkable improvement of network parameters, by applying a stochastic search algorithm called Gur game, when compared to a baseline application.

PENGGUNAAN INTERNET OF THINGS DALAM PEMASARAN PRODUK PERTANIAN

2018 ◽  
Vol 3 (2) ◽  
pp. 74
Author(s):  
Helina Apriyani ◽  
Sismadi Sismadi ◽  
Sefrika Sefrika
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Electronic Devices ◽  
Agricultural Products ◽  
Main Concept ◽  
Farmers Market ◽  
Incremental Method ◽  
Sales Process ◽  
Internet Connections

AbstrakInternet of things (IoT) adalah sebuah konsep yang menghubungkan komputer dan perangkat elektronik melalui internet dan dapat dikendalikan dari jarak jauh. Konsep terpenting dalam Internet of things (Iot) adalah modul sistem informasi, koneksi internet dan penyimpanan datanya dalam cloud computing. Konsep ini memiliki manfaat besar dalam perkembangan usaha dan kelangsungan bisnis perusahaan dimana hampir semua bidang menggunakan IoT untuk dapat bersaing di pasaran. Indonesia merupakan sebuah negara yang dianugerahi kekayaan alam yang melimpah ruah. Salah satu komoditi unggulan adalah produk pertanian. Penelitian ini bertujuan untuk membantu para petani dalam memasarkan produknya melalui e-commerce dengan menggunakan konsep Internet of things IoT. Metode penelitian dengan menggunakan metode incremental.  Incremental digunakan untuk mendesai produk, kemudian  diimplementasikan, dan diuji secara bertahap (setiap modul akan ditambahkan bertahap) hingga produk selesai. Hasil penelitian ini digunakan untuk membantu petani di Kabupaten Bogor untuk mendistribusikan penjualannya secara luas, meningkatkan revenue dan memutus rantai panjang proses penjualan. Kata kunci— sistem penjualan, incremental, Internet of Things (IoT), produk pertanian, Kabupaten Bogor Abstract Internet of things (IoT) is a concept that connects computers and electronic devices via the internet and can be controlled remotely. The main concept in Internet of things (IoT) is information systems, internet connections and data storage in cloud computing. This concept has great benefits in the efforts and efforts used to use IoT to be able to compete in the market. Indonesia is a country that is blessed with abundant natural resources. One of the leading commodities is agricultural products. This study aims to help farmers market their products through e-commerce using the IoT Internet of things concept. Research method using incremental method. Incremental to design the product, then implemented, and gradually delay (each module will be added gradually) until the product is finished. The results of this study are to help farmers in Bogor Regency to distribute sales widely, increase revenue and break the sales process. Keywords—sales system, incremental, Internet of Things (IoT), agricultural products, Kabupaten Bogor

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

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