The past decade has sparked technology catered around cloud systems to better manage and handle vast amounts of data. In the developing spaces of instant delivery and higher data processing, the technology behind Edge Computing seeks to replace and improve cloud systems and delight users with easier and more affordable data transfer. But what exactly is edge computing and how does it impact businesses? Here’s what you need to know.
What Is Edge Computing?
Simply put, edge computing is a method of optimizing cloud computing systems by performing data processing at the “edge” of the network, near the source of the data, and away from centralized nodes. In the context of the Internet of Things (IoT), edge computing refers to the infrastructure of devices away from the centralized computing available in the cloud. The role of edge computing has mainly been used to manage and send data to cloud systems, but this trait for ‘edge’ is expected to populate many business and consumer computing systems in the upcoming years in order to pack more storage and analytic power for IoT devices.
Edge Computing Stats To Know
- By the end of 2017, an estimated 1.6 billion government and enterprise IoT devices will connect via an edge computing model.
- By 2020, there will be 5,6 billion smart sensors and other IoT devices employed around the world and are estimated to generate over 507.5 zettabytes (1 zettabyte = 1 trillion gigabytes) of data.
- By 2022, Gartner – a research and advisory firm – predicts that 50% of enterprise-generated data will be created and processed outside a traditional centralized data center or cloud.
- By 2023, the global IoT market is expected to top $724.2 billion.
What Edge Computing Means For Business
The rapid growth behind edge computing is why IoT businesses aim to get ahead of the curve. The amount of IoT data and processing needed is what drives competition for IoT businesses. More data from more sources helps businesses make better decisions that allow them to streamline operations and provide better customer support.
In the mobile world, the user experience is dictated by two factors:
- Bandwidth (the maximum amount of information that can be transmitted across a channel in a given period of time)
- Latency (the time it takes for a given amount of information to be transmitted across a channel)
Network latency is a major concern for overall user experience (think of the difference in network delays between an IoT device like Amazon’s Alexa and autonomous cars) and Bandwidth is expensive (the more individuals using the cloud, the more bandwidth necessary to transmit data back and forth). Edge computing itself was born from the need to process data faster, and having the most important data at the edge of the network, especially for IoT devices, allow for immediate interactive feedback, reduced latency, and minimal bandwidth usage.
Business leaders and executives who rely on and benefit from edge computing can also focus on the operational aspects of their business, where machine automation and auto alerts can signal issues with their networks, equipment, and infrastructure before a problem worsens.
Edge computing and cloud computing can also work great separately, but together they create significant feedback off of each other. Businesses can utilize faster data processing (edge) or necessary storage capacity (cloud) exclusively. This hybrid model is also referred to as fog computing since it combines centralized and distributed computing resources into a single architecture that allows edge devices to communicate with one another and with the cloud.
Edge Computing In Action
Businesses such as Intel, IBM, General Electric, and Cisco have implemented edge computing solutions that fit either a wide distribution of data collection devices or cloud-based scenarios. In healthcare, for example, users can easily gather and analyze data from wearables and sensors that monitor health metrics and activities while managing other dedicated medical equipment at home and in clinical settings.
Immersive And Real-Time Data Application
With the number of connected devices becoming a reality – with AR/VR, connected cars, and smart cities in development – businesses are unable to tolerate more than a few milliseconds of latency and can be extremely sensitive to any variation within their data processing. Microsoft positions itself as a leading company in edge computing with their launch of Azure IoT Edge, a software platform that brings cloud services to edge devices, making hybrid cloud and edge IoT solutions a reality for optimal and immersive data application.
Edge computing has influenced industries like transportation and power infrastructure, to create environments that should have good connectivity. In these sectors, the Edge Computing Consortium identifies the following ‘edge’ benefits for automated processes:
- Flexible and rapid deployment of new production processes
- Lower energy consumption and maintenance costs
- Smarter manufacturing by means of better customization, smaller quantity and multi-batch modes of production
Network Functions Virtualization (NFV)
According to the Open Stack Edge Computing Group, NFV is “at its heart the quintessential edge computing application because it provides infrastructure functionality. Telecom operators can transform their service delivery models by running virtual network functions as part of, or layered on top of, an edge computing infrastructure.”
Improving network efficiency is a goal many businesses have in their IT strategies. With Edge Computing, bandwidth and its associated high cost of transferring data to the cloud is greatly reduced. In practice, this can allow employees immediate access to analytics. For example, a technician working in the field to check machine performance can access real-time data, or a financial advisor can pull client information based on sourced data.
Enterprises with an edge computing infrastructure can impact other business elements such as workloads, connectivity limits, security assurance and privacy. For example, financial applications that need to anonymize personal employer information before sending it to the cloud could do so by using edge computing infrastructure. The aim would be to reduce costs as much as possible during the transfer of data. Edge computing also offers better security against breaches and risks, with the ability to move security elements closer to the originating source of attack, and increases the number of layers to help defend businesses from cyber attacks.