Blockchain-based Fog Computing Applications in Healthcare

Adanur, Beyhan; Bakır-Güngör, Burcu; Soran, Ahmet

doi:10.1109/siu49456.2020.9302168

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…The author has proposed fog computing as a solution to gather data from devices and encrypt it in fog nodes using the AES algorithm, and then it is sent to the cloud for storage. Adanur et al [82] have discussed the application of blockchain in healthcare on top of fog computing. The author has proposed a blockchain application based on fog architecture that caters to heterogeneity, latency, and delay sensitivity in the healthcare sector.…”

Section: Fog Computing For Healthcarementioning

confidence: 99%

A Review of Fog Computing Concept, Architecture, Application, Parameters and Challenges

Ghani,

Bakar Sajak,

Qureshi

et al. 2024

JOIV : Int. J. Inform. Visualization

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The Internet of Things (IoT) has become an integral part of our daily lives, growing exponentially from a facility to a necessity. IoT has been utilized extensively through cloud computing and has proven an excellent technology for deploying in various fields. The data generated by the IoT devices gets transmitted to the cloud for processing and storage. However, with this approach, there are specific issues like latency, energy, computation resources availability, bandwidth, heterogeneity, storage, and network failure. To overcome these obstacles, fog computing is utilized as a middle tier. Fog computing gathers and processes the generated data closer to the user end before transmitting it to the cloud. This paper aims to conduct a structured review of the current state of fog computing and its architectures deployed across multiple industries. This paper also focuses on the implementation and critical parameters for introducing fog computing in IoT-cloud architecture. A detailed comparative analysis has been carried out for 5 different architectures considering various crucial parameters to identify how the quality of service and quality of experience for end users can be optimized. Finally, this paper looks at the multiple challenges that fog computing faces in a structured six-level approach. These challenges will also lead the way for future research in resource management, green computing, and security.

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Section: Fog Computing For Healthcarementioning

confidence: 99%

A Review of Fog Computing Concept, Architecture, Application, Parameters and Challenges

Ghani,

Bakar Sajak,

Qureshi

et al. 2024

JOIV : Int. J. Inform. Visualization

View full text Add to dashboard Cite

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“…Blockchain is used with fuzzy logic in healthcare in order to provide solutions to problems faced by blockchain in healthcare applications. [25].…”

Section: Previous Workmentioning

confidence: 99%

Internet of Things Based Blockchain Technology for Gas Station

ALahmed

2022

IJICI

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The protection of information sent over the Internet has become very important because of the possibility of being hacked and leaking important or confidential information. Therefore, many studies have been conducted in the field of information security and many ways have emerged to protect the information, but blockchain technology is the most prominent technology currently due to its high potential in maintaining the study was conducted on the most important blockchain algorithms, namely the Proof of Authority (POA) algorithm and the Proof of Work (POW) algorithm. The study aimed now at the best and most reliable algorithm to protect the parameters sent via the Internet of Things technology. The POA algorithm is the first candidate to win the advantage in theory, but After applying the study and verifying the actual results, it was confirmed that the POA algorithm is superior and highly capable of protecting information, in addition to speed in executing calculations, less memory consumption, less execution time, fewer Nonce to obtain the correct hash, and many other advantages, and the obtained result was the PoA algorithm is significantly faster with a difference of 46/s to create the blockchain, and it also requires less memory than the PoW algorithm, with a difference of 1024KB. Blockchain (B.C) algorithms will be applied to the Internet of Things (IoT) technology to obtain IoT technology that is completely encrypted from hacking and information cannot be tampered with. The transmission within the network, whether it is a local or global network. The new technology will be applied to a gas station information transmission system to generate electric power. The aim of this paper are to make the smart grid of the gas station more secure and private.

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“…Nowadays, big data has been processed using edge computing. Sensor layer capabilities and generating objects are used in the calculations and processing, namely fog computing [4]. Fog computing with a cloud-computing layer can provide smart cities with a high capacity to process large data sets.…”

Section: Introductionmentioning

confidence: 99%

Harris Hawks optimization for ambulance vehicle routing in smart cities

Hussein

Frikha²,

Rahebi³

2023

EEJET

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The ambulance routing problem is one of the capacitated ambulance routing problem forms. It deals with injuries and their requests for saving. Therefore, the main aim of the ambulance routing problem is to determine the minimum (i.e., optimum) required distances of between: 1) accident places and the ambulance station; 2) the location of the nearest hospital and the accident places. Although of the efforts proposed in the literature, determining the optimum route is crucial. Therefore, this article seeks to tackle ambulance vehicle routing in smart cities using Harris Hawks Optimization (HHO) algorithm. It attempts to take the victims as quickly as possible and confidently. Several engineering optimization problems confirm that HHO outperforms many well-known Swarm intelligence approaches. In our system, let’s use the node approach to produce a city map. Initially, the control station receives accident site information and sends it to the hospital and the ambulance. The HHO vehicle routing algorithm receives data from the driver; the data includes the location of the accident and the node position of the ambulance vehicle. Then, the driver’s shortest route to the accident scene by the HHO. The locations of the accident and hospital are updated by the driver once the car reaches the accident site. The fastest route (which results in the least travel time) to the hospital is then determined. The HHO can provide offline information for a potential combination of the coordinates of destination and source. Extensive simulation experiments demonstrated that the HHO can provide optimal solutions. Furthermore, performance evaluation experiments demonstrated the superiority of the HHO algorithm over its counterparts (SAODV, TVR, and TBM methods). Furthermore, for ten malicious nodes, the PDF of the algorithm was 0.91, which is higher than the counterparts

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Blockchain-based Fog Computing Applications in Healthcare

Cited by 9 publications

References 17 publications

A Review of Fog Computing Concept, Architecture, Application, Parameters and Challenges

A Review of Fog Computing Concept, Architecture, Application, Parameters and Challenges

Internet of Things Based Blockchain Technology for Gas Station

Harris Hawks optimization for ambulance vehicle routing in smart cities

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