Overview - Fog Computing and Internet-of-Things (IOT)
Journal Title: EAI Endorsed Transactions on Cloud Systems - Year 2017, Vol 3, Issue 10
Abstract
The Internet today is getting connected to a very large number of devices or sensors of IOT. It is expected that 50 billion devices will be connected to the Internet by 2020..The IOT driven global economy will have many technological challenges. The computing and storage power of the IOT devices being very small, it calls for the support of enhanced resources from the Cloud. This results in overloading of the networks with limited bandwidth. The performance of Cloud services depends upon the servers located in Cloud data centres which are located at close proximity to core networks which are at large distances from the edge or field locations where the IOT devices are located for gathering the data. This results in the end-to-end latency to rise up to two orders of magnitude higher than the required values for delivering the expected performance of the Cloud services. This problem of latency is further compounded by the unprecedentedly large volumes of data generated in real time by the IOT devices and could be of great value, if analysed in real time, However, the data volumes generated overwhelm the storage systems and the analytical applications, if to be sent to the Cloud. The delay caused in transferring the data to the Cloud and getting back the results of analysis makes it infeasible to cater to the needs of real life situations such as emergency response and health management, Hence the need for a new paradigm, now known as Fog Computing. In this Paper a comprehensive overview of the Fog Computing technology is provided. After multiple definitions,, various .architectures of Fog are presented, so as to cater to the needs of a very large spectrum of applications of Fog Computing in Health, Transportation, Smart Cities, Smart Villages, Smart Homes, Augmented Reality,M2M device-to-device connection., traffic management, etc,. Latency aware application management and resource coordination issues in application management in Fog are surveyed. Fog analytics is surveyed in detail, with upcoming models and products such as Smart Data and Fog Engine being presented..Security and Privacy issues that arise in the distributed Fog ecosystem are dealt with and some existing methods as authentication, encryption are presented. Finally the multifarious directions and vast opportunities for research in the new and upcoming area of Fog Computing ,are presented.
Authors and Affiliations
C. S. R. Prabhu
Keywords
Related Articles
- EP ID EP45598
- DOI http://dx.doi.org/10.4108/eai.20-12-2017.154378
- Views 275
- Downloads 0
Towards a cloud consumers credibility assessment and trust management of cloud services
In Cloud computing, several issues arises due to malicious users. The cloud service provider does not know whether the cloud consumer is authorized user or an unauthorized user when they access the data from cloud. Cloud...
Modeling user and topic interactions in social networks using Hawkes processes
We present in this paper a framework to model information diffusion in social networks based on linear multivariate Hawkes processes. Our model exploits the effective broadcasting times of information by users, which gua...
Video Steganography using MATLAB
This paper discusses a Video Steganographic scheme that can provide approvable security with high computing speed, by embedding data in video frames. The technique of embedding data in a video file by using LSB before wh...
Specification of REST API Services for Modbus Protocol using Formal technique
With the advancements in technologies, there has been a growing trend to move from desktop applications towards web and mobile applications. This move was made possible through introduction of the RESTful Web Services. T...
Defining an Elasticity Metric for Cloud Computing Environments
Elasticity is a key property of cloud computing environments and one of the features which distinguishes this paradigm from other ones. An elasticity metric could be used to define and to monitor Service Level Agreements...