Fog computing extends the cloud computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are 1) low latency and location awareness, 2) widespread geographical distribution, 3) mobility, 4) very large number of nodes, 5) predominant role of wireless access, 6) strong presence of streaming and real time applications, and 7) heterogeneity. In this chapter, the authors argue that the above characteristics make the Fog the appropriate platform for a number of critical internet of things (IoT) services and applications, namely connected vehicle, smart grid, smart cities, and in general, wireless sensors and actuators networks (WSANs).
TopIntroduction
An emerging wave of Internet deployments, most notably the Internet of Things (IoTs), requires mobility support and geo-distribution in addition to location awareness and low latency. We argue that a new platform is needed to meet these requirements; a platform we call Fog Computing or Fog because the fog is a cloud close to the ground. We also claim that rather than cannibalizing Cloud Computing, (Bonomi, 2011). Fog Computing enables a new breed of applications and services, and that there is a fruitful interplay between the Cloud and the Fog, particularly when it comes to data management and analytics. The Internet of Things (IoT) is generating an unprecedented volume and variety of data. But by the time the data makes its way to the cloud for analysis, the opportunity to act on it might be gone.
Fog Computing
Fog computing also known as edge computing which provides elastic resources and services to the end users at the edge of network. Fog computing is an extension of cloud computing not its replacement. As the number of devices connected to internet has been increasing. In future the world would be full of sensor, it would provide the massive amount of data and storing these data in the cloud and retrieving is difficult. Hence fog can be used. Fog computing is an effective replacement of cloud computing for Internet of Things. It reduces the latency and overcomes the security issues in sending data to the cloud.
Cloud, Fog, and Edge: Overview
Fog Computing extends a substantial amount of data storage, computing, communication, and networking of cloud computing near to the end devices. Due to close integration with the front-end intelligence enabled end devices, fog computing enhances the overall system efficiency, after that improving the performance of critical cyber-physical systems. An important key difference is that cloud computing tries to optimize resource in a global view, whereas fog computing organizes and manages the local virtual cluster. Edge computing and fog computing terms are interchangeably used in both academia and industry. Although the main objectives of edge computing and fog computing are same, i.e., to reduce end-to-end delay and lower network congestion, however, they differ how they process and handle the data and where the intelligence and computing power are placed. The main idea of Edge computing is to push computation facility towards data sources, e.g., sensors, actuators, and mobile devices. In Edge computing, each individual edge component plays its role to process data locally rather than sending them towards the cloud, whereas, fog node decides whether to process the data from multiple data sources using its own resource or send to the cloud. Also, several services like Infrastructure-as-a-Service (IaaS), Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and other cloud-related services are not supported in Edge computing, however, these services can be extended with fog computing. To summary, Edge computing is totally edge localized, however, fog computing extends the computing and communication resources towards edge of the network.
Fog Computing: An Effective Replacement Of Cloud For Iot Devices
Though cloud computing offers on demand service and scalable storage and processing capabilities for IoT devices, for monitoring health, emergency applications and other latency sensitive applications, the time or delay caused by the applications for transferring data to the cloud and then processing it, is unacceptable. On the other hand, sending large amount big data collected by the devices to the cloud will saturate the network bandwidth sometimes. To overcome these issues, edge computing was introduced which provides the computing capabilities within the edge of the network near the IoT sensors. This also has some drawbacks like the edge computing resources can’t handle multiple applications competing for the same limited resources. This again increases the latency or delay time for processing the application requests.
Fog computing has the following characteristics: multiple application support, simple, fast and standardized protocols, strong security, fault tolerance, versatile operating environment, supports multiple operating platforms such as unix, linux, mac, windows etc..,