Edge computing is a distributed computing standard that brings computing and data storage closer to where they are needed to increase response times and save bandwidth. Edge computing is computing taking place at the physical location of the user or data source resulting in lower latency and bandwidth. It is calculated at the source of the data, rather than relying on the cloud or one of the dozens of data centers.
Edge computing brings the processing capacity of devices closer to source data, abolishing the path from the cloud to the data center and reducing latency. Unlike cloud computing, edge computing allows data from existing data sources to be networked with edge devices. Edge Computing works locally on the device itself, such as a water quality sensor or water purifier in a remote village, and stores data that would otherwise have to be transferred to a central point where connectivity is available.
At the same time, Edge Computing distributes the storage and processing of related applications and devices to the local data center. The combination of edge and cloud computing in a single continuum is part of FOG Computing Paradigm (R2) which includes joint management of computing resources. Computer data storage resources and applications and their data are positioned in an optimal location between the user and the cloud.
An early aim of edge computing is to address the cost and bandwidth of data transported over long distances, with the growth of IoT-generated data and the growth of real-time applications that require processing by edge-driven technologies. Edge Computing can help address key challenges such as data sovereignty, data latency, data integrity, and IoT / AR / VR, robotics, machine learning and telecommunications networks that require the delivery of services to users. Likewise, edge computing’s goal is to move computing from the data center to the edge of the network, using smart objects such as mobile phones and network gateways to perform tasks and provide services in the name of the cloud.
Edge gateways, for example, process data on edge devices and send relevant data to the cloud, reducing bandwidth needs. Edge computing is becoming a dominant factor in industrial use cases because the edge enables more complex and specialized computing resources and more data storage. When edge computing is implemented, data traverses the network from cloud to the data center with secure encryption, but the Edge deployment itself is hardened against hackers and other malicious activities, so the security of IoT devices remains limited.
Most edge computing surveys point to a Gartner forecast for 2018 which we mentioned in an earlier article on edge computing and IoT: 75% of business-generated data will be generated and processed by 2025 outside traditional centralized data centers and the cloud, compared to 10% in 2025. With faster speeds, it is impossible to say how long companies will continue to process data outside the cloud. Many carriers are working on an edge computing strategy for their 5G deployment to provide faster real-time processing for mobile devices, connected cars and self-driving cars. The general trend of data generation rising to the level of cloud and IDC can of course be seen at the heart of edge computing, but edge computing as a decentralized paradigm for driving digital transformation will have plenty of use cases in the coming years.
Edge computing leverages existing devices such as routers, servers, gateways, switches, telecommunications base stations, dedicated physical components (so-called cloudlets) and data center boxes with full use of virtualization technologies. The Edge IT deployment model complements the cloud and addresses some of the challenges of cloud computing, including data centers, physical infrastructure and software. Key benefits offered by Edge solutions include low latency and high bandwidths for processing data and offloading trusted computers and storage
In terms of infrastructure, Edge Computing is a network of local micro-computing centers for storage and processing. In edge computing, data moves between different distributed nodes connected to the Internet and requires special encryption mechanisms independent of the cloud. Unlike cloud data centers, resources for edge deployment are limited, scattered, and distributed, making strict edge computing more viable.
Data center equipment supplier HPE, a major investor in edge computing, believes that the next big leap in operational infrastructure will be coordinated and managed by employees and contractors, not so much through personal investment in training and hardware infrastructure, but by employees in charge of maintenance and software support.
Benefits of Edge Computing
By using a combination of cloud and edge computing solutions, workloads can be containerized and shared over multiple cloud services, edge servers and edge devices, says Craig Wright, managing director of consultancy Pace Harmon. For example, when a company tries to reduce its central data center footprint, Edge and other distributed computing technologies can be aligned.
Data centers offer cloud computing services to selected customers at competitive prices comparable to those offered by cloud providers such as Amazon, Microsoft Azure and Google Cloud Platform.
Why is Edge Computing evolving
Edge computing is evolving because of the exponential growth of the IoT devices that connect to the Internet to receive information from the cloud and to deliver data to the cloud. The increasing number of IoT devices on edge of the network is producing enormous amounts of data and computing power in the data centres – pushed the bandwidth demands of the network to the limit. There are concerns about proximity not only between the edge and the cloud region, but the edge also inherits the benefits of 5G’s transport capabilities and savings from wireless devices bypassing the Internet for computing resources.