scholarly journals Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1974
Author(s):  
Abdullah Lakhan ◽  
Qurat-ul-ain Mastoi ◽  
Mazhar Ali Dootio ◽  
Fehaid Alqahtani ◽  
Ibrahim R. Alzahrani ◽  
...  
Keyword(s):  
Heterogeneous Computing ◽  
Security Issue ◽  
Healthcare Applications ◽  
Delay Sensitive ◽  
Task Sequencing ◽  
Healthcare Monitoring ◽  
Searching Method ◽  
Cloud Network ◽  
Delay Tolerant ◽  
Healthcare Architecture

The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan.

Exploring the Applications of Machine Learning in Healthcare

2020 ◽  
Vol 10 (4) ◽  
pp. 458-472
Author(s):  
Tausifa Jan Saleem ◽  
Mohammad Ahsan Chishti
Keyword(s):  
Machine Learning ◽  
Disease Risk ◽  
Disease Diagnosis ◽  
Machine Intelligence ◽  
Healthcare Applications ◽  
Comprehensive Overview ◽  
Machine Learning Applications ◽  
Remote Healthcare ◽  
Healthcare Monitoring ◽  
Applications Of Machine Learning

The rapid progress in domains like machine learning, and big data has created plenty of opportunities in data-driven applications particularly healthcare. Incorporating machine intelligence in healthcare can result in breakthroughs like precise disease diagnosis, novel methods of treatment, remote healthcare monitoring, drug discovery, and curtailment in healthcare costs. The implementation of machine intelligence algorithms on the massive healthcare datasets is computationally expensive. However, consequential progress in computational power during recent years has facilitated the deployment of machine intelligence algorithms in healthcare applications. Motivated to explore these applications, this paper presents a review of research works dedicated to the implementation of machine learning on healthcare datasets. The studies that were conducted have been categorized into following groups (a) disease diagnosis and detection, (b) disease risk prediction, (c) health monitoring, (d) healthcare related discoveries, and (e) epidemic outbreak prediction. The objective of the research is to help the researchers in this field to get a comprehensive overview of the machine learning applications in healthcare. Apart from revealing the potential of machine learning in healthcare, this paper will serve as a motivation to foster advanced research in the domain of machine intelligence-driven healthcare.

DOS Attacks on Cloud Platform

2021 ◽  
pp. 476-490
Author(s):  
Rohit Kumar
Keyword(s):  
Financial Services ◽  
Denial Of Service ◽  
Dos Attacks ◽  
Security Issue ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Utmost Care ◽  
Cloud Network ◽  
Financial Losses ◽  
Very High

IaaS, PaaS, and SaaS models collectively form the Cloud Computing Infrastructure. The complexity of interrelationship of service models is very high and so security issue becomes essentials and must be developed with utmost care. Distributed DOS attacks are a major concern for different organization engaged in using cloud based services. The denial of service attack and distributed denial of service attacks in particular in cloud paradigms are big threat on a cloud network or platform. These attacks operate by rendering the server and network useless by sending unnecessary service and resource requests. The victims host or network isn't aware of such attacks and keeps providing recourses until they get exhausted. Due to resource exhaustions, the resources requests of genuine users doesn't get fulfilled. Severity of these attacks can lead to huge financial losses if, they are able to bring down servers executing financial services. This chapter presents DOS threats and methods to mitigate them in varied dimensions.

Cloud Based Wireless Infrastructure for Health Monitoring

2020 ◽  
pp. 34-55 ◽  
Author(s):  
Ajay Chaudhary ◽  
Sateesh Kumar Peddoju ◽  
Suresh Kumar Peddoju
Keyword(s):  
Cloud Computing ◽  
Health Monitoring ◽  
Healthcare Services ◽  
Power Source ◽  
Vital Role ◽  
Healthcare Applications ◽  
Related Data ◽  
Health Related ◽  
Healthcare Monitoring ◽  
Wireless Infrastructure

The wireless infrastructure based devices can collect data for long period of time even with a tiny power source as they perform specific function of collection of health related data and sending to gateways. The sensing data of healthcare monitoring consumes low power but they had limited computation power to process this data, where the cloud computing plays a vital role and compliment the loophole of wireless infrastructure based systems. In cloud computing with its immense computation power for easily deployment of healthcare monitoring algorithms and helps to process sensed data. As these two technologies did great jobs in their respective fields a conflate framework of these two technologies may lead to a great architecture for healthcare applications. This chapter reviews complete state-of-the-art and several use cases related to healthcare monitoring using different wireless infrastructure and adapting cloud based technologies in providing the healthcare services.

scholarly journals Green Data Gathering under Delay Differentiated Services Constraint for Internet of Things

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Mingfeng Huang ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Changqin Huang
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Data Gathering ◽  
Differentiated Services ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensitive Data ◽  
Delay Sensitive ◽  
Delay Tolerant

Energy-efficient data gathering techniques play a crucial role in promoting the development of smart portable devices as well as smart sensor devices based Internet of Things (IoT). For data gathering, different applications require different delay constraints; therefore, a delay Differentiated Services based Data Routing (DSDR) scheme is creatively proposed to improve the delay differentiated services constraint that is missed from previous data gathering studies. The DSDR scheme has three advantages: first, DSDR greatly reduces transmission delay by establishing energy-efficient routing paths (E2RPs). Multiple E2RPs are established in different locations of the network to forward data, and the duty cycles of nodes on E2RPs are increased to 1, so the data is forwarded by E2RPs without the existence of sleeping delay, which greatly reduces transmission latency. Secondly, DSDR intelligently chooses transmission method according to data urgency: the direct-forwarding strategy is adopted for delay-sensitive data to ensure minimum end-to-end delay, while wait-forwarding method is adopted for delay-tolerant data to perform data fusion for reducing energy consumption. Finally, DSDR make full use of the residual energy and improve the effective energy utilization. The E2RPs are built in the region with adequate residual energy and they are periodically rotated to equalize the energy consumption of the network. A comprehensive performance analysis demonstrates that the DSDR scheme has obvious advantages in improving network performance compared to previous studies: it reduces transmission latency of delay-sensitive data by 44.31%, reduces transmission latency of delay-tolerant data by 25.65%, and improves network energy utilization by 30.61%, while also guaranteeing the network lifetime is not lower than previous studies.

scholarly journals IoMT-based biomedical measurement systems for healthcare monitoring: a review

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 174
Author(s):  
Imran Ahmed ◽  
Eulalia Balestrieri ◽  
Francesco Lamonaca
Keyword(s):  
Healthcare Systems ◽  
Future Research ◽  
Pressure Measurements ◽  
Healthcare Applications ◽  
Measurement Systems ◽  
Biomedical Equipment ◽  
Research Activities ◽  
Biomedical Measurement ◽  
Healthcare Monitoring ◽  
Internal Body

<p class="Abstract"><span lang="EN-US">Biomedical measurement systems (BMS) have provided new solutions for healthcare monitoring and the diagnosis of various chronic diseases. With a growing demand for BMS in the field of medical applications, researchers are focusing on advancing these systems, including Internet of Medical Things (IoMT)-based BMS, with the aim of improving bioprocesses, healthcare systems and technologies for biomedical equipment. This paper presents an overview of recent activities towards the development of IoMT-based BMS for various healthcare applications. Different methods and approaches used in the development of these systems are presented and discussed, taking into account some metrological aspects related to the requirement for accuracy, reliability and calibration. The presented IoMT-based BMS are applied to healthcare applications concerning, in particular, heart, brain and blood sugar diseases as well as internal body sound and blood pressure measurements. Finally, the paper provides a discussion about the shortcomings and challenges that need to be addressed along with some possible directions for future research activities.</span></p>

scholarly journals Secure and failure hybrid delay enabled a lightweight RPC and SHDS schemes in Industry 4.0 aware IIoHT enabled fog computing

2021 ◽  
Vol 19 (1) ◽  
pp. 513-536
Author(s):  
Mazhar Ali Dootio ◽  
◽  
Abdullah Lakhan ◽  
Ali Hassan Sodhro ◽  
Tor Morten Groenli ◽  
...  
Keyword(s):  
Model Simulation ◽  
Blood Pressure Monitoring ◽  
Fog Computing ◽  
Healthcare Applications ◽  
Linear Integer Programming ◽  
Industrial Internet ◽  
Healthcare Monitoring ◽  
Internet Of Healthcare Things ◽  
Security Network ◽  
The Mathematical Model

<abstract><p>These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes.</p></abstract>

scholarly journals On Cellular Networks Supporting Healthcare Remote Monitoring in IoT Scenarios

2021 ◽  
Vol 2 ◽  
Author(s):  
Andrea Petroni ◽  
Pierpaolo Salvo ◽  
Francesca Cuomo
Keyword(s):  
Cellular Networks ◽  
Remote Monitoring ◽  
Network Performance ◽  
Research Direction ◽  
Cellular Systems ◽  
Traffic Load ◽  
Physical Interaction ◽  
Healthcare Applications ◽  
Remote Healthcare ◽  
Healthcare Monitoring

In the next few years, fundamental technological transitions are expected both for wireless communications, soon resulting in the 5G era, and for the kind of pervasiveness that will be achieved thanks to the Internet of Things. The implementation of such new communication paradigms is expected to significantly revolutionize people’s lives, industry, commerce, and many daily activities. Healthcare applications are considered to be one of the most impacted industries. Sadly, in relation to the COVID-19 pandemic currently afflicting our society, health remote monitoring has become a fundamental and urgent application. The overcrowding of hospitals and medical facilities due to COVID-19, has unavoidably created delays and key issues in providing adequate medical assistance. In several cases, asymptomatic or light symptomatic COVID-19 patients have to be continuously monitored to prevent emergencies, and such an activity does not necessarily require hospitalization. Considering this research direction, this paper investigates the potentiality of cloud-based cellular networks to support remote healthcare monitoring applications implemented in accordance with the IoT paradigm, combined with future cellular systems. The idea is to conveniently replace the physical interaction between patients and doctors with a reliable virtual one, so that hospital services can be reserved for emergencies. Specifically, we investigate the feasibility and effectiveness of remote healthcare monitoring by evaluating its impact on the network performance. Furthermore, we discuss the potentiality of medical data compression and how it can be exploited to reduce the traffic load.

scholarly journals AI-Inspired Non-Terrestrial Networks for IIoT: Review on Enabling Technologies and Applications

IoT ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 21-48
Author(s):  
Emmanouel T. Michailidis ◽  
Stelios M. Potirakis ◽  
Athanasios G. Kanatas
Keyword(s):  
Wireless Communication ◽  
Communication Technologies ◽  
Optimization Methods ◽  
Sensors And Actuators ◽  
Delay Sensitive ◽  
Industrial Internet ◽  
Lower Complexity ◽  
Terrestrial Networks ◽  
Delay Tolerant ◽  
High Degree

During the last few years, various Industrial Internet of Things (IIoT) applications have emerged with numerous network elements interconnected using wired and wireless communication technologies and equipped with strategically placed sensors and actuators. This paper justifies why non-terrestrial networks (NTNs) will bring the IIoT vision closer to reality by providing improved data acquisition and massive connectivity to sensor fields in large and remote areas. NTNs are engineered to utilize satellites, airships, and aircrafts, which can be employed to extend the radio coverage and provide remote monitoring and sensing services. Additionally, this paper describes indicative delay-tolerant massive IIoT and delay-sensitive mission-critical IIoT applications spanning a large number of vertical markets with diverse and stringent requirements. As the heterogeneous nature of NTNs and the complex and dynamic communications scenarios lead to uncertainty and a high degree of variability, conventional wireless communication technologies cannot sufficiently support ultra-reliable and low-latency communications (URLLC) and offer ubiquitous and uninterrupted interconnectivity. In this regard, this paper sheds light on the potential role of artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), in the provision of challenging NTN-based IIoT services and provides a thorough review of the relevant research works. By adding intelligence and facilitating the decision-making and prediction procedures, the NTNs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics with significantly lower complexity compared to typical optimization methods.

DOS Attacks on Cloud Platform

2018 ◽  
pp. 167-184 ◽  
Author(s):  
Rohit Kumar
Keyword(s):  
Financial Services ◽  
Denial Of Service ◽  
Dos Attacks ◽  
Security Issue ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Utmost Care ◽  
Cloud Network ◽  
Financial Losses ◽  
Very High

IaaS, PaaS, and SaaS models collectively form the Cloud Computing Infrastructure. The complexity of interrelationship of service models is very high and so security issue becomes essentials and must be developed with utmost care. Distributed DOS attacks are a major concern for different organization engaged in using cloud based services. The denial of service attack and distributed denial of service attacks in particular in cloud paradigms are big threat on a cloud network or platform. These attacks operate by rendering the server and network useless by sending unnecessary service and resource requests. The victims host or network isn't aware of such attacks and keeps providing recourses until they get exhausted. Due to resource exhaustions, the resources requests of genuine users doesn't get fulfilled. Severity of these attacks can lead to huge financial losses if, they are able to bring down servers executing financial services. This chapter presents DOS threats and methods to mitigate them in varied dimensions.

Internet of Things-Based Healthcare Applications

2020 ◽  
pp. 1-28 ◽  
Author(s):  
Seema Ansari ◽  
Tahniyat Aslam ◽  
Javier Poncela ◽  
Pablo Otero ◽  
Adeel Ansari
Keyword(s):  
Internet Of Things ◽  
Healthcare Systems ◽  
Health Improvement ◽  
Monitoring Systems ◽  
Healthcare Applications ◽  
Iot Applications ◽  
History Of ◽  
Healthcare Monitoring ◽  
The Difference ◽  
The Impact

The demand for global healthcare systems for human health improvement is ever growing. Internet of things (IoT) has influenced every industry in the market. IoT-based healthcare monitoring systems have emerged using smart gateways between sensor networks and the internet. This chapter aims at focusing on the impact of IoT on healthcare and explores the difference that IoT has made in the recent years. IoT applications in healthcare have helped people keep track of their medical requirements such as reminding them of appointments, keeping a check on calorie count, variations in blood pressure, a check on exercises, and many more. In this chapter, studies of IoT-based healthcare applications are presented. The chapter begins with the introduction and history of IoT in healthcare, sharing state of the art, architecture, applications of IoT in healthcare, advantages, future concerns and challenges, and future of IoT in healthcare, followed by conclusion.

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