|Edge computing is revolutionizing the way data is being handled, processed, and provided from millions of connected devices across the globe / Photo by: Damiano Poli via 123RF|
Edge computing is revolutionizing the way data is being handled, processed, and provided from millions of connected devices across the globe, wrote Keith Shaw of Network World, a network news website. The rapid proliferation of IoT and new applications that require real-time computing power helps drive edge-computing systems.
Moreover, faster networking technologies like 5G accelerate edge computing systems to create or support real-time applications, including video processing and analytics, self-driving cars, AI, and robotics.
One of the objectives of edge computing has been to address the costs of bandwidth for data traveling long distances due to the rise of IoT-generated data. As real-time applications continue to increase, the need for processing at the edge will propel the technology forward.
Statistics on Edge Computing and IoT
German statistics platform Statista found that the forecast net worth of the global IoT market in 2019 was $1.7 trillion as cited by Louie Andre of Finances Online, a website containing online reviews of B2B and SaaS solutions. Ericsson, one of the leading providers of information and communication technology (ICT) to service providers, stated that there will be 3.5 billion cellular devices that employ IoT connections by 2023, per the company’s 2018 mobility report.
As for IoT’s benefits, Statista stated that 90% of senior executives in telecom, media, and tech companies consider IoT growth as essential to their business as of 2018. Interestingly, healthcare organizations can save up to 25% in business growth, thanks to IoT edge devices, data analytics news site Health IT said.
The edge computing market was valued at $1,734.8 million in 2017 and is forecasted to reach $16,556.6 million in 2025 at a CAGR of 32.8% from 2018 to 2025, said market research company Allied Market Research. The large enterprise segment had the highest revenue for the edge computing market share in 2017 due to the influx of data gathered from intelligent machines, vehicles, and other IoT devices.
The IT and telecom industry dominated the edge computing market in 2017 and is projected to generate the highest revenue during the forecast period 2018 to 2025. This is attributed to the increased need to speed up the deployment of products to customers. The retail industry is also expected to have the highest growth rate during the forecast period.
What Is Edge Computing?
According to global research and advisory firm Gartner, edge computing is defined as a “part of a distributed computing topology where information processing is located close to the edge, where things and people produce or consume that information.”
Rather than depending on a central location that is stationed thousands of miles away, edge computing brings computation and data storage closer to the devices where data is gathered. This way, data, particularly real-time data, does not suffer latency issues that can jeopardize the application’s performance.
Further, companies can also save on costs since the processing is done locally, minimizing the amount of data needed to be processed in a centralized or cloud-based location. Edge devices include IoT sensors, an employee’s notebook computer, their smartphone, a security camera, and even an internet-connected microwave oven.
|According to global research and advisory firm Gartner, edge computing is defined as a “part of a distributed computing topology where information processing is located close to the edge, where things and people produce or consume that information” / Photo by: everythingpossible via 123RF|
Why Is Edge Computing Important for IoT?
Low Latency and Faster Data Processing
As mentioned before, edge computing reduces latency for critical applications as well minimizes dependency on the cloud and to better manage volumes of data generated by IoT devices, noted Raj Talluri of Network World.
A low-latency connection means an IoT device can gather data, process that data at the edge, and retrieve that data without noticeable lag for the user, said Connor Craven of Sdx Central, a trusted news and resource website for Software-defined Everything (SDx), SDN, and more.
One example is the Nest Cam IQ indoor security camera, which utilizes on-device vision processing to observe a person’s movement, distinguish family members, and sends notifications if an individual is not recognized or “doesn’t fit pre-defined parameters.”
Nest slashes the amount of bandwidth, cloud processing, and cloud storage used by performing computer vision tasks within the security camera. On-device processing boosts the speed of alerts while it minimizes the chances of sending out annoying, recurrent false alarms.
More Responsive and Robust IoT Applications
Edge computing also makes IoT applications more responsive and robust. For example, it can enhance natural language interfaces, enabling smart speakers to react quicker by interpreting voice instructions locally, toggle thermostat settings even if connectivity is disrupted, as well as run basic commands such as switching lights on or off.
Indeed, edge computing drives innovation in IoT applications, especially for those relying on machine learning for object detection, facial recognition, language processing, obstacle avoidance, and other tasks.
Edge computing offers tangible value in consumer and industrial IoT use cases by sending pertinent information instead of raw streams of sensor data, thereby slashing connectivity costs. This benefit is valuable on devices that are connected via LTE/cellular like smart meters or asset trackers.
If an industrial facility or mining operation deals with large amounts of data generated by sensors, edge computing can help analyze and filter that data, resulting in huge savings in network and computing power since most IoT devices run on battery.
Bolster Security and Privacy
It can also enhance security and privacy by storing sensitive data within the device. For instance, new retail advertising systems and digital signage are developed to deliver targeted ads and information to customers based on key parameters (ex. demographic information) set on a field device. Edge computing can safeguard user privacy by anonymizing, analyzing, and storing the data at the source rather than sending them to the cloud.
Looking Ahead: 5G is the Future
In the IoT context, edge devices are designed with more sophisticated computing capabilities. If coupled with 5G, which will provide more robust and faster connectivity, we will get to witness the emergence of a new generation of smart devices and applications.
Research and analysis firm Futuriom mentioned in its report, “5G, IoT and Edge Computing Trends,” that 5G will drive edge-computing technology. It added that applications leveraging 5G technology will alter traffic demand patterns, which will be the biggest driver for edge computing in mobile networks.
Low-latency applications such as IoT analytics, machine learning, VR, and AVs “have new bandwidth and latency characteristics that will require support from edge-compute infrastructure,” Futuriom noted.
Edge computing can help process data generated by IoT devices and improve security and privacy by anonymizing data. It consumes less networking and computing power without noticeable lag, which can be attractive to prospective end users. Benefits aside, 5G will catalyze edge-computing technologies, leading to the emergence of new applications in the next several years.