In this digital era, governing bodies and infrastructure planners are designing initiatives to transform cities into smart cities. In order to make cities smarter, they are using digital technology in each domain of smart city such as transportation, traffic management, safety, energy and much more. Some of the urban services which are governed by the internet will improve the living standards of the citizens. There is a huge trade-off as well. Having billion of people, devices and things connected to the network will cause network surge. It is projected that currently fifteen billion devices connected to the internet, while it is expected that by 2020 the number will increase to 50 billion.
The multiplex assembly of devices connected to the network will gather data from all kinds of mobile devices, smartphones, and sensors making a hefty data stream. As the network is expanding day by day, consequently increasing the volume of data. Moreover, the data produced needs to be arranged, processed, secured and analyzed. Therefore, new processing technologies must be introduced at the network end so that the network providers operate in an intelligent way by managing the huge data in a distributed fashion across the region. As a result, the network can smartly analyze and elaborate the data and control processes through informing the analyzed information, connect people and things efficiently. These data processing techniques should be able to process data instantly and ensure precise result so that cities can establish a sustainable social, economical and environmental sustainability.
Smart cities should introduce new standards in order to ensure social and economic viability. They should provide a flexible and secure platform where data should be intelligently analyzed at the network edge and efficiently communicated to the cloud. These standards should be made in such a way that they define an easy way to control and manage the smart city ecosystem through handy set-up procedure and appropriate automation.
WHAT IS FOG COMPUTING?
Fog computing is a technology introduced in order to disburden the centralized cloud. It can be referred as edge computing as it operates on the network edge, unlike cloud computing which hosts and works from a centralized cloud. In fog computing, data is processed in smart devices locally without being sent to the centralized cloud for processing. It is considered as one of the best technology in the deployment of Internet of Things (IoT). The network architecture of fog computing is shown in the figure below.
Figure 1: an illustration of architecture of Fog.
In 2015, Cisco along with the City of Barcelona and certain other partners conducted a Proof of Concept (PoC) on fog computing. The main purpose of this PoC was to realize the vision of fog computing. Fog computing is useful when dealing with real-time applications in a limited spectrum. Having millions of devices connected to the network, the volume of data generated each second is more than petabytes and exabytes. This large volume of data being generated each instant cannot be sent to the cloud as there is always limited bandwidth provided by the network. Under such situations fog computing is an excellent solution. Rather than setting up channels to the cloud for the purpose of processing and utilization, it resources, analyzes and aggregates the data at network edge thereby reducing the requirement for additional bandwidth. Through this distributed strategy it helps efficiently utilize the allocated bandwidth and lower network maintenance costs.
FOG COMPUTING CHARACTERISTICS AND USES
Fog computing has several advantages but some of the noteworthy attributes are as following:
While talking about smart cities, fog computing enhances the abilities of IoT and Cloud Computing by aggregating the data before sending to the cloud for further computation. As the information from the sensors keeps on increasing at an exponential rate, the chance of potential bottleneck becomes more and more evitable. Moreover, due to the flow of a large number of data to the cloud may also incapacitate the real-time communication applications. Therefore, fog computing provides the most feasible and best platform for critical IoT applications such as smart grid, connected vehicle, machine to machine communication, smart cities, and some IoT services like Wireless sensors and Actuator Networks (WSANs). Analysis of fog and cloud computing is shown in the figure given below.
Figure 2: Analysis of fog and cloud computing.
In Chicago traffic light system is controlled with the help of smart sensors. For instance, it’s Tuesday morning, a day of big parade on the celebration of Chicago Cubs’ first World Series championship in more than a century. Big traffic is expected to enter the city as a large number of a crowd will be visiting to celebrate the victory of their team. With the increase in traffic, traffic volume is controlled through the smart traffic sensors and data are collected from the individual traffic lights.
The application developed by the IOT specialists functions by automatically adjusting the on and off patterns of the traffic light in real-time at the network edge by monitoring the volume of traffic as it becomes large or shrinks. Therefore, the visitors spend less time on roads and more time at the celebration.
FUTURE OF FOG COMPUTING FOR SMART CITIES
It is being suggested by Cisco that by utilizing both cloud and fog computing IoT services can be utilized more smartly than ever before. Cisco says that by combining both its Java Virtual Machine and IOS Linux platforms, it will be easy to port the applications to a supportable environment. Moreover, many businesses are adopting both fog and cloud computing. It is worth mentioning that after Cisco, Microsoft has also introduced Windows 10 IoT core as an optimal operating system for devices which lack screen and thus giving the utility to use Windows for smart devices. It is estimated by IDC that the volume of data being stored, analyzed and processed on devices at the edge will be 40 percent in upcoming years. Moreover, 50 percent of the IoT use cases will be controlled by the network.
In recent years, fog computing has become a necessary component for IoT architecture. It manages the services and controls the data stream from the network edge. This particular edge computing can thus reduce the CAPEX and OPEX as well as saves the time of deployment of smart city solutions. There are many verticals of smart cities where fog computing can be used such as smart health, smart grid, smart transportation, retail, industries and many others.
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