IoT and Edge Computing

What is IoT?

The Internet of things (IoT) is the inter-networking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.

What is Edge Computing?

Edge computing is a method of optimising cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors and the central datecentre by performing analytics and knowledge generation at or near the source of the data. This approach requires leveraging resources that may not be continuously connected to a network such as laptops, smartphones, tablets and sensors.Edge Computing covers a wide range of technologies including wireless sensor networks, mobile data acquisition, mobile signature analysis, cooperative distributed peer-to-peer ad hoc networking and processing.

Why is Edge Computing beneficial for IoT?

Moving data, computation and control into the cloud has been a significant trend in the past decade. However, as the explosion of connected lightweight devices starts the era of the Internet-of-Things (IoT), cloud computing is facing increasing difficulty to meet the data computing and intelligent service demands of IoT devices and applications. Moving the data computation and service supply from the cloud to the edge enables the possibility of meeting application delay requirements, improves the scalability and energy efficiency of lightweight IoT devices, provides contextual information processing, and mitigates the traffic burdens of the backbone network.

Instead of performing data storage and computing in a cluster of clouds, edge computing emphasizes leveraging the power of local computing and using different types of edge devices, such as smartphones, routers and PCs, as edge servers to provide intelligent services. Data storage, computing and control can be separated and intelligently distributed among the connected edge servers and IoT devices. Thus, edge computing can bring many beneficial advantages, such as, highly-improved scalability by remote and intelligent service supply, local computing that makes full use of client computing capabilities and meets the requirements of contextual computing Furthermore, by interacting with the cloud, edge computing can provide more scalable services for delay-tolerant IoT applications.

How does Edge Computing give the 'edge' to IoT?

IoT nodes are closer to the action, but for the moment, they do not have the computing and storage resources to perform analytics and machine learning tasks. Cloud servers, on the other hand, have the horsepower, but are too far away to process data and respond in time.The fog layer is the perfect junction where there are enough compute, storage and networking resources to mimic cloud capabilities at the edge and support the local ingestion of data and the quick turnaround of results.The cloud will continue to have a pertinent role in the IoT cycle. In fact, with fog computing shouldering the burden of short-term analytics at the edge, cloud resources will be freed to take on the heavier tasks, especially where the analysis of historical data and large datasets is concerned. Insights obtained by the cloud can help update and tweak policies and functionality at the fog layer.It is the combination of fog and cloud computing that will accelerate the adoption of IoT, especially for the enterprise.

What are the various use cases?

• Thanks to the power of fog computing, New York-based renewable energy company Envision has been able to obtain a 15 percent productivity improvement from the vast network of wind turbines it operates.
• IoT company Plat One is another firm using fog computing to improve data processing for the more than 1 million sensors it manages. The company uses the ParStream platform to publish real-time sensor measurements for hundreds of thousands of devices, including smart lighting and parking, port and transportation management and a network of 50,000 coffee machines.
• In Palo Alto, California, a $3 million project will enable traffic lights to integrate with connected vehicles, hopefully creating a future in which people won’t be waiting in their cars at empty intersections for no reason.
• In transportation, it’s helping semi-autonomous cars assist drivers in avoiding distraction and veering off the road by providing real-time analytics and decisions on driving patterns.
• It also can help reduce the transfer of gigantic volumes of audio and video recordings generated by police dashboard and video cameras. Cameras equipped with edge computing capabilities could analyze video feeds in real time and only send relevant data to the cloud when necessary.