scholarly journals Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6574
Author(s):  
Syed Rizwan Hassan ◽  
Ishtiaq Ahmad ◽  
Shafiq Ahmad ◽  
Abdullah Alfaify ◽  
Muhammad Shafiq
Keyword(s):  
Cloud Computing ◽  
Monitoring System ◽  
Fog Computing ◽  
Self Report ◽  
Healthcare Applications ◽  
Computing Architecture ◽  
Computing Paradigm ◽  
Smart Healthcare ◽  
Number Of Patients ◽  
Iot Devices

The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.

scholarly journals Leveraging Fog Computing for a Secure and Smart Healthcare

2019 ◽  
Vol 8 (2) ◽  
pp. 6117-6122
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fog Computing ◽  
Healthcare Services ◽  
Decision Fusion ◽  
Sensor Data ◽  
Smart Sensors ◽  
Healthcare Applications ◽  
Smart Healthcare ◽  
Iot Devices

From hairbrushes to scales, all devices have sensors embedded in them to collect and communicate data. Smart Healthcare is proving to be an exciting and dynamic area with lots of room for new innovations and the increasing consumer demand for proactive health monitoring devices. Having India poised to spend a lot on healthcare, recent innovations using IoT devices and big data analytics can propel the healthcare industry into the future. Smart healthcare providers are leveraging cloud computing with fog computing to optimize their healthcare services. These smart healthcare applications depend mainly on the raw sensor data collected, aggregated, and analyzed by the smart sensors. Smart sensors these days generate myriad amount of data like text, image, audio, and video that require real-time or batch processing. Aggregating these diverse data from various types of resources remains a dispute till date. To resolve this issue, we have proposed a softwarized infrastructure that integrates cloud computing and fog computing, message brokers, and Tor for supple, safe, viable, and a concealed IoT exploitation for smart healthcare applications and services. Our proposed platform employs machine-to-machine (M2M) messaging, data fusion and decision fusion, and uses rule-based beacons for seamless data management. Our proposed flexBeacon system provides an IoT infrastructure that is nimble, secure, flexible, private, and reasonable. We have also proposed an M2M transceiver and microcontroller for flawless data incorporation of smart healthcare applications and services. Based on the IoT devices’ technical capabilities and resource availability, some systems are capable of making use of homomorphic encryption and zero knowledge proofs. The proposed flexBeacon platform offers seamless management and data aggregation without loss of accuracy. The cost of implementing a softwarized IoT for smart healthcare is also greatly reduced.

From Cloud Computing to Fog Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Close Proximity ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

From Cloud Computing to Fog Computing

2021 ◽  
pp. 999-1010
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Key Characteristics ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

scholarly journals Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3159
Author(s):  
Jakub Jalowiczor ◽  
Jan Rozhon ◽  
Miroslav Voznak
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
The Internet ◽  
Long Distance ◽  
Daily Lives ◽  
Communication Architecture ◽  
Computing Paradigm ◽  
Data Volume ◽  
Distance Communication ◽  
Iot Devices

The technologies of the Internet of Things (IoT) have an increasing influence on our daily lives. The expansion of the IoT is associated with the growing number of IoT devices that are connected to the Internet. As the number of connected devices grows, the demand for speed and data volume is also greater. While most IoT network technologies use cloud computing, this solution becomes inefficient for some use-cases. For example, suppose that a company that uses an IoT network with several sensors to collect data within a production hall. The company may require sharing only selected data to the public cloud and responding faster to specific events. In the case of a large amount of data, the off-loading techniques can be utilized to reach higher efficiency. Meeting these requirements is difficult or impossible for solutions adopting cloud computing. The fog computing paradigm addresses these cases by providing data processing closer to end devices. This paper proposes three possible network architectures that adopt fog computing for LoRaWAN because LoRaWAN is already deployed in many locations and offers long-distance communication with low-power consumption. The architecture proposals are further compared in simulations to select the optimal form in terms of total service time. The resulting optimal communication architecture could be deployed to the existing LoRaWAN with minimal cost and effort of the network operator.

Integrated Fog and Cloud Computing Issues and Challenges

2021 ◽  
Vol 11 (4) ◽  
pp. 174-193
Author(s):  
Shivom Sharma ◽  
Mohammad Sajid
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Fog Computing ◽  
Low Latency ◽  
Traffic Lights ◽  
Computing Paradigm ◽  
Iot Devices ◽  
Smart Traffic ◽  
Smart Computing ◽  
Cloud Resources

Due to the exponential growth in the number of internet-of-things (IoT) devices like smartphones and smart traffic lights, the data generated by the devices and the service requirements are increasing. The biggest issue in accessing the cloud computing is that all processing is done on cloud resources. For cloud-based services, it is utmost required to send all data to cloud resources which leads to many issues and challenges. The important issues are large volume of data, low latency rate, low bandwidth. In order to resolve such issues, there is an essential need of a smart computing paradigm which works as a moderator between cloud computing and IoT devices to improve the performances of the services, maximizing utilization of computing resources, storage. This work presents an overview and description of fog computing in the context of cloud computing and internet of things (IoT) and also sheds light on the key differences between cloud computing and fog computing. This work also presents various issues and challenges in the context of fog computing with its various applications.

Opportunistic Edge Computing Architecture for Smart Healthcare Systems

2021 ◽  
pp. 289-306
Author(s):  
Nivethitha V. ◽  
Aghila G.
Keyword(s):  
Cloud Computing ◽  
Healthcare Systems ◽  
Edge Computing ◽  
Healthcare Applications ◽  
Sensitive Data ◽  
Network Resource ◽  
Computing Architecture ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Network Response Time

Some of the largest global industries that is driving smart city environments are anywhere and anytime health monitoring applications. Smart healthcare systems need to be more preventive and responsive as they deal with sensitive data. Even though cloud computing provides solutions to the smart healthcare applications, the major challenge imposed on cloud computing is how could the centralized traditional cloud computing handle voluminous data. The existing models may encounter problems related to network resource utilization, overheads in network response time, and communication latency. As a solution to these problems, edge-oriented computing has emerged as a new computing paradigm through localized computing. Edge computing expands the compute, storage, and networking capabilities to the edge of the network which will respond to the above-mentioned issues. Based on cloud computing and edge computing, in this chapter an opportunistic edge computing architecture is introduced for smart provisioning of healthcare data.

Fog Computing Application Deployment and Management

2019 ◽  
pp. 68-83
Author(s):  
Ranjitha G. ◽  
Pankaj Lathar ◽  
G. M. Siddesh
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Smart Cities ◽  
Fog Computing ◽  
The Internet ◽  
Access Points ◽  
Computing Paradigm ◽  
Application Deployment ◽  
Iot Devices ◽  
The Internet Of Things

Fog computing enhances cloud computing to be closer to the processes that act on IOT devices. Fogging was introduced to overcome the cloud computing paradigm which was not able to address some services, applications, and other limitations of cloud computing such as security aspects, bandwidth, and latency. Fog computing provides the direct correlation with the internet of things. IBM and CISCO are linking their concepts of internet of things with the help of fog computing. Application services are hosted on the network edge. It improves the efficiency and reduces the amount of data that is transferred to the cloud for analysis, storage, and processing. Developers write the fog application and deploy it to the access points. Several applications like smart cities, healthcare domain, pre-processing, and caching applications have to be deployed and managed properly.

Fog Computing and Its Challenges

2019 ◽  
pp. 36-52
Author(s):  
Vighnesh Srinivasa Balaji
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Service Level ◽  
Future Research ◽  
Research Directions ◽  
Security Issues ◽  
Computing Paradigm ◽  
Future Research Directions ◽  
Time Latency ◽  
Iot Devices

In recent times, the number of internet of things (IoT) devices/sensors increased tremendously. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named fog computing has been introduced. In this chapter, the authors will introduce fog computing, its difference in comparison to cloud computing, and issues related to fog. Among the three issues (i.e. service, structural, and security issues), this chapter scrutinizes and comprehensively discusses the service and structural issues also providing the service level objectives of the fog. They next provide various algorithms for computing in fog, the challenges faced, and future research directions. Among the various uses of fog, two scenarios are put to use.

scholarly journals A Multidomain Standards-Based Fog Computing Architecture for Smart Cities

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Víctor Rampérez ◽  
Javier Soriano ◽  
David Lizcano
Keyword(s):  
Cloud Computing ◽  
Smart Cities ◽  
Fog Computing ◽  
Cost Savings ◽  
Low Latency ◽  
Location Awareness ◽  
Rapid Urbanization ◽  
Computing Architecture ◽  
Computing Paradigm ◽  
Urban Population Growth

Many of the problems arising from rapid urbanization and urban population growth can be solved by making cities “smart”. These smart cities are supported by large networks of interconnected and widely geo-distributed devices, known as Internet of Things or IoT, that generate large volumes of data. Traditionally, cloud computing has been the technology used to support this infrastructure; however, some of the essential requirements of smart cities such as low-latency, mobility support, location-awareness, bandwidth cost savings, and geo-distributed nature of such IoT systems cannot be met. To solve these problems, the fog computing paradigm proposes extending cloud computing models to the edge of the network. However, most of the proposed architectures and frameworks are based on their own private data models and interfaces, which severely reduce the openness and interoperability of these solutions. To address this problem, we propose a standard-based fog computing architecture to enable it to be an open and interoperable solution. The proposed architecture moves the stream processing tasks to the edge of the network through the use of lightweight context brokers and Complex Event Processing (CEP) to reduce latency. Moreover, to communicate the different smart cities domains we propose a Context Broker based on a publish/subscribe middleware specially designed to be elastic and low-latency and exploit the context information of these environments. Additionally, we validate our architecture through a real smart city use case, showing how the proposed architecture can successfully meet the smart cities requirements by taking advantage of the fog computing approach. Finally, we also analyze the performance of the proposed Context Broker based on microbenchmarking results for latency, throughput, and scalability.

Survey on DDoS Attacks and Defense Mechanisms in Cloud and Fog Computing

2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta
Keyword(s):  
Cloud Computing ◽  
Defense Mechanisms ◽  
Low Cost ◽  
Fog Computing ◽  
Smart Devices ◽  
Cloud Environment ◽  
Security Issue ◽  
Process Data ◽  
Ddos Attack ◽  
Iot Devices

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.

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