Big Data, Internet of Things and Cloud Convergence – An Architecture for Secure E-Health Applications

Suciu, George; Suciu, Victor; Marțian, Alexandru; Crăciunescu, Răzvan; Vulpe, Alexandru; Marcu, Ioana; Halunga, Simona; Fratu, Octavian

doi:10.1007/s10916-015-0327-y

Cited by 161 publications

(58 citation statements)

References 17 publications

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“…Finally, they present the findings of extended results from the European Union (EU)‐funded project BIG and the German‐funded project PEC . As a conclusion, we have study the combination of the technologies of Mobile Cloud Computing, Big Data, and IoT, and we have study some analysation of existing components and methods of securely integrating Big Data processing with cloud machine‐to‐machine systems based on remote telemetry units .…”

Section: Related Workmentioning

confidence: 95%

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

2016

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SUMMARYThe Internet of Things (IoT) is a new technology that is growing rapidly in the field of telecommunications and especially in the modern field of wireless telecommunications. The main goal of the interaction and cooperation between things and objects sent through the wireless networks is to fulfill the objective set to them as a combined entity. In addition, based on the technology of wireless networks, both the technologies of Mobile Cloud Computing (MCC) and IoT develop rapidly. In this paper, we combine the two aforementioned technologies (i.e., MCC and IoT) with the technology of the Big Data in order to examine the common features and tο discover which of the MCC and IoT benefits improve the use of the Big Data applications. Finally, we present the contribution of MCC and IoT individually to the technology of Big Data.

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Section: Related Workmentioning

confidence: 95%

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

2016

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“…Every single IoT device might present a potential risk that could be exploited to either harm the end-users or jeopardize the privacy of them [130]. If IoT security is compromised, end-users information can be accessed through unauthorized authentications.…”

Section: E Security and Privacymentioning

confidence: 99%

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Farahani

Firouzi

Chang

et al. 2018

Future Generation Computer Systems

818

371

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Internet of Things (IoT) offers a seamless platform to connect people and objects to one another for enriching and making our lives easier. This vision carries us from compute-based centralized schemes to a more distributed environment offering a vast amount of applications such as smart wearables, smart home, smart mobility, and smart cities. In this paper we discuss applicability of IoT in healthcare and medicine by presenting a holistic architecture of IoT eHealth ecosystem. Healthcare is becoming increasingly difficult to manage due to insufficient and less effective healthcare services to meet the increasing demands of rising aging population with chronic diseases. We propose that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other. This patient-centric IoT eHealth ecosystem needs a multi-layer architecture: 1) device, 2) fog computing and 3) cloud to empower handling of complex data in terms of its variety, speed, and latency. This fog-driven IoT architecture is followed by various case examples of services and applications that are implemented on those layers. Those examples range from mobile health, assisted living, e-medicine, implants, early warning systems, to population monitoring in smart cities. We then finally address the challenges of IoT eHealth such as data management, scalability, regulations, interoperability, device-network-human interfaces, security, and privacy.

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“…In this way, problems are expected to be detected before they arise in the ongoing processes. When data is generated with a rate and volume at a scale beyond the capacity of the state-of-the-art systems and therefore creates a need for revolutionary solutions, it is called Big Data [9][10][11][56][57][58][59]. With the revolutionary Big Data solutions, the tremendous amount of data generated by M2M applications can be handled effectively.…”

Section: Review Articlementioning

confidence: 99%

Big Data Analysis for M2M Networks:Research Challenges and Open Research Issues

Tuna¹,

Daş²,

Ramakrishnan³

et al. 2017

ijcna

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-In recent years, solutions based on machine-tomachine (M2M) communications have started to support us in many areas of our life and work. However, the amount of data collected by M2M has increased tremendously and surpassed our expectations. This makes it necessary to investigate data mining methodologies and machine learning techniques in order to efficiently utilize large amounts of data gathered by M2M devices. In this paper, we first review existing data mining and machinelearning techniques specifically designed and proposed for M2M networks. Then, we discuss Big Data concept, investigate Big Data analysis techniques, and the importance of Big Data for M2M networks. Finally, we investigate research challenges and open research issues in M2M to provide an insight into future research opportunities.

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Big Data, Internet of Things and Cloud Convergence – An Architecture for Secure E-Health Applications

Cited by 161 publications

References 17 publications

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Big Data Analysis for M2M Networks:Research Challenges and Open Research Issues

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