C. Prabhu, Tony Jan, M. Prasad, Vijayakumar Varadarajan
{"title":"FOG ANALYTICS - A SURVEY","authors":"C. Prabhu, Tony Jan, M. Prasad, Vijayakumar Varadarajan","doi":"10.22452/MJCS.SP2020NO1.10","DOIUrl":null,"url":null,"abstract":"Fog computing has emerged as an essential alternative to the cloud. Fog computing is the future as it is nearer to the edge where actually the IOT devices and sensors are located. A Fog Server or Fog Node is located near to the IOT devices, connecting directly (wired or wireless) to them. The Fog Server has a functionality of fast accessibility to the data arising out of IOT devices or sensors, as against cloud server which may be located in data centers (near core Network Centers) located far away from the edge resulting in extreme delays in network transmission and latency, especially when the data is large volume as stream (or ‘Big Data’) arising out of IOT devices or sensors including cameras, etc. Real time response after completing the necessary Analytics on the data generated by IOT devices and sensors becomes critically essential for meeting the real time response requirements of critical applications such as in health care and transportation. What are the relevant techniques for Fog Analytics? In this paper we provide a brief survey of Fog Analytics techniques in stream data analytics, machine learning, deep learning techniques and also game theoretical adversarial learning.","PeriodicalId":49894,"journal":{"name":"Malaysian Journal of Computer Science","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Malaysian Journal of Computer Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.22452/MJCS.SP2020NO1.10","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1
Abstract
Fog computing has emerged as an essential alternative to the cloud. Fog computing is the future as it is nearer to the edge where actually the IOT devices and sensors are located. A Fog Server or Fog Node is located near to the IOT devices, connecting directly (wired or wireless) to them. The Fog Server has a functionality of fast accessibility to the data arising out of IOT devices or sensors, as against cloud server which may be located in data centers (near core Network Centers) located far away from the edge resulting in extreme delays in network transmission and latency, especially when the data is large volume as stream (or ‘Big Data’) arising out of IOT devices or sensors including cameras, etc. Real time response after completing the necessary Analytics on the data generated by IOT devices and sensors becomes critically essential for meeting the real time response requirements of critical applications such as in health care and transportation. What are the relevant techniques for Fog Analytics? In this paper we provide a brief survey of Fog Analytics techniques in stream data analytics, machine learning, deep learning techniques and also game theoretical adversarial learning.
期刊介绍:
The Malaysian Journal of Computer Science (ISSN 0127-9084) is published four times a year in January, April, July and October by the Faculty of Computer Science and Information Technology, University of Malaya, since 1985. Over the years, the journal has gained popularity and the number of paper submissions has increased steadily. The rigorous reviews from the referees have helped in ensuring that the high standard of the journal is maintained. The objectives are to promote exchange of information and knowledge in research work, new inventions/developments of Computer Science and on the use of Information Technology towards the structuring of an information-rich society and to assist the academic staff from local and foreign universities, business and industrial sectors, government departments and academic institutions on publishing research results and studies in Computer Science and Information Technology through a scholarly publication. The journal is being indexed and abstracted by Clarivate Analytics'' Web of Science and Elsevier''s Scopus