Security and Privacy Issues in Cloud, Fog and Edge Computing

Parikh, Shalin; Dave, Dharmin; Patel, Reema; Doshi, Nishant

doi:10.1016/j.procs.2019.11.018

Cited by 82 publications

(35 citation statements)

References 5 publications

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“…With our accurate results in this paper, we are confident that MSAM is a reliable method to be used for other kinds of initial value problems. The idea of MSAM could be adapted for continuous versions of discrete problems in computing [33], and it could be extended to be analysed using advanced mathematical tools, such as, algebraic geometry and conformal mapping.…”

Section: Riccati Differential Equation Involving a Variable Coefficientmentioning

confidence: 99%

A multistage successive approximation method for Riccati differential equations

Prabowo

Mungkasi

2021

Bulletin EEI

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Riccati differential equations have played important roles in the theory and practice of control systems engineering. Our goal in this paper is to propose a new multistage successive approximation method for solving Riccati differential equations. The multistage successive approximation method is derived from an existing piecewise variational iteration method for solving Riccati differential equations. The multistage successive approximation method is simpler in terms of computing implementation in comparison with the existing piecewise variational iteration method. Computational tests show that the order of accuracy of the multistage successive approximation method can be made higher by simply taking more number of successive iterations in the multistage evolution. Furthermore, taking small size of each subinterval and taking large number of iterations in the multistage evolution lead that our proposed method produces small error and becomes high order accurate.

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Section: Riccati Differential Equation Involving a Variable Coefficientmentioning

confidence: 99%

A multistage successive approximation method for Riccati differential equations

Prabowo

Mungkasi

2021

Bulletin EEI

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“…These days most of the higher institutions are implementing regular office applications, online desktop, messaging services to hold web level solutions for students and teachers much specifically. According to Parikh et al [12] the issues of traditional cloud computing and IoT Technologies also get resolved with application of Fog Computing because of its lower latency. The response time in fog computing is lesser than any other immediate technologies.…”

Section: System Developmentmentioning

confidence: 99%

“…It has been observed that the performance offered with the education system and the way lessons are taught towards the student may get hampered due to low latency and this will eventually lead to hampering the data shared. IoT helps in providing a better platform for the students so that they can easily access the materials from the communication channel [12]. Education application tends to store huge data related to the students, staffs, and their associated document.…”

mentioning

confidence: 99%

Utilizing technologies of fog computing in educational IoT systems: privacy, security, and agility perspective

Adel

2020

J Big Data

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Fog computing architecture is referred to the architecture that is distributed over the geographical area. This architectural arrangement mainly focuses on physical and logical network elements, and software for the purpose of implementing proper network. Fog computing architecture allows the users to have a flexible communication and also ensures that the storage services are maintained efficiently for the purpose of managing the data. However, it has been observed that in the field of education fog computing architecture has gained huge importance due to its real time application feature. The main objective of the survey is to develop a systematic literature review for the technology of fog computing in the education IoT system. The survey will also focus on evaluating the essential factors that has a crucial role in the fields of education as well as investigating the limitation and findings associated with the fog computing technologies in educational systems from the perspective of privacy, security, and agility.

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“…• Communication: proximity allows to reduce the transmission hops of the data, and hence network congestion. • Privacy: distributed data permits to keep it safer locally, which prevents leakage [19]. • Energy: the advantages in computation and communication enable to reduce the energy consumption of the whole system.…”

Section: Introductionmentioning

confidence: 99%