International Journal of Electrical and Computer Engineering (IJECE) Vol. 7, No. 6, December 2017, pp. 3669~3673 ISSN: 2088-8708, DOI: 10.11591/ijece.v7i6.pp3669-3673  3669 Journal homepage: http://iaesjournal.com/online/index.php/IJECE Fog Computing: Issues, Challenges and Future Directions Prakash P, Darshaun K.G, Yaazhlene. P, Medidhi Venkata Ganesh, Vasudha B Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University, India Article Info ABSTRACT Article history: Received May 5, 2017 Revised Jun 14, 2017 Accepted Jul 2, 2017 In Cloud Computing, all the processing of the data collected by the node is done in the central server. This involves a lot of time as data has to be transferred from the node to central server before the processing of data can be done in the server. Also it is not practical to stream terabytes of data from the node to the cloud and back. To overcome these disadvantages, an extension of cloud computing, known as fog computing, is introduced. In this, the processing of data is done completely in the node if the data does not require higher computing power and is done partially if the data requires high computing power, after which the data is transferred to the central server for the remaining computations. This greatly reduces the time involved in the process and is more efficient as the central server is not overloaded. Fog is quite useful in geographically dispersed areas where connectivity can be irregular. The ideal use case requires intelligence near the edge where ultra- low latency is critical, and is promised by fog computing. The concepts of cloud computing and fog computing will be explored and their features will be contrasted to understand which is more efficient and better suited for real- time application. Keyword: Fog computing Cloud computing Edge nodes IoT and Big Data Copyright © 2017Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Prakash P, Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University, India. 1. INTRODUCTION Networking is shaped by two obvious trends - Cloud-based Internet and mobile computing. Cloud computing [1, 2] forms a basic need for all organizations that deal with large amount of data. Cloud forms to be very efficient in storing large amount of data and providing access to it from anywhere in the world. This could lead to unauthorized access to personal data or a firm's private data [3]. In relation to cloud-computing, bringing services to the edge of the network is fog computing. Fog computing deals with user behaviour profiling and decoy information technology to prevent unauthorized access. In Fog Computing, computing resources and application services are distributed in the most logical, efficient places, at any point along the continuum from the data source to the cloud. Fog computing is defined as " a scenario where a large number of heterogeneous wireless devices are connected together in a network, communicate and potentially cooperate among them and with the network to perform storage and processing tasks without the intrusion of third parties". Although this definition is debatable, this defines how fog computing differs from the related technologies. Fog Computing avoids primarily to store data in large-scale data centers. Fog Computing offers a significant amount of measurement, control and configuration is performed at or near the end-user. Fog Computing supports emerging Internet of Everything (IoE) applications that demand real-time/predictable latency. Fog supports densely distributed data collection points, through devices called Fog nodes [4]. The major difference between cloud computing and Fog computing is on the support of location awareness. Fog Computing, composed of geo-distributed Fog servers, targets to deliver the localized and location based