A STUDY ON DATA STREAMING IN FOG COMPUTING ENVIRONMENT

In lately years, data streaming is become more important day by day, considering technologies employed to servethat manner and share number of terminals within the system either direct or indirect interacting with them.Smart devices now play active role in the data streaming environment as well as fog and cloud compatibility. It is affectingthe data collectivity and appears clearly with the new technologies provided and the increase for the number of theusers of such systems. This is due to the number of the users and resources available system start to employ the computationalpower to the fog for moving the computational power to the network edge. It is adopted to connect system that streamed dataas an object. Those inter-connected objects are expected to be producing more significant data streams, which are produced atunique rates, in some cases for being analyzed nearly in real time. In the presented paper a survey of data streaming systemstechnologies is introduced. It clarified the main notions behind big data stream concepts as well as fog computing. From thepresented study, the industrial and research communities are capable of gaining information about requirements for creatingFog computing environment with a clearer view about managing resources in the Fog.The main objective of this paper is to provide short brief and information about Data Streaming in Fog ComputingEnvironment with explaining the major research field within this meaning

Mobile learning architecture using fog computing and adaptive data streaming

With the huge development in mobile and network fields, sensor technologies and fog computing help the students for more effective learning, flexible and in and effective manner from anywhere. Using the mobile device for learn encourage the transition to mobile computing (cloud and fog computing) which is led to the ability to design customized system that help student to learn via context aware learning which can be done by set the user preference and use proper methods to show only related manner subject. The presented study works on developing a system of e-learning which has been on the basis of fog computing concepts with deep learning approaches utilized for classification to the data content for accomplishing the context aware learning and use the adaptation of video quality using special equation and the data encrypted and decrypted using 3DES algorithm to ensure the security side of the operation

Retracted: Smart optimal path with blockchain modelling in internet of things using enhanced K‐means clustering and advance encryption standard

Abstract Retraction: [Inas Ismael Imran, Shymaa Mohammed Jameel, Refed Adnan Jaleel, Smart optimal path with blockchain modelling in internet of things using enhanced K‐means clustering and advance encryption standard, IET Software 2023 (https://doi.org/10.1049/sfw2.12095)]. The above article from IET Software, published online on 28 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract