Why do enterprises need edge computing in 2020?
What is edge computing?
Edge computing promotes the spread of data analytics technology to the perimeter of computer networks.
Why do enterprises need edge computing in 2020? Enterprises are forecast to spend over £1 trillion on internet of things networks, devices and the systems required to manage them. As long as they’re reliant on data centers and cloud technologies, that bill will only increase. These businesses require edge computing to process and analyze the vast streams of data they’ll generate as a result – particularly industrial enterprises, which will experience more IoT disruption than most. They need solutions to take data analysis out of central cloud or data center systems, and instruct sensors, gateway devices and IoT devices to transmit collected information to nearby systems which analyze this information locally.
Driving awareness & Action
In the 2016 PWC global industry 4.0 survey, in which over 2000 firms worldwide participated from nine different industries, 83% of respondents predicted that data would have a significant impact on their decision making in the next five years, but only roughly half are using data to drive these decisions today. If users adopt edge computing, this could be a way for industry players to convert data from the factory floor to the supply chain into business intelligence – discovering patterns, trends and methods to improve efficiency, lower operational costs and boost business revenue. Some enterprises still need convincing that all their decision making should be data influenced. Many more need to be shown how this can be done effectively.
Data acceleration & Analysis
IOT technology means collecting and processing data in real- time locally, eradicating the need to first send information out to data centers or the cloud. Latency can be lowered by pushing analytics capabilities to the edge of networks. As data is collected close to the source, analysis can take place almost instantaneously, improving the speed and efficiency of industrial applications.
Another benefit of edge computing is the ability to scale. As iot becomes engrained in the market and is integrated into existing frameworks, localized, bolt-on deployment of edge computing solutions can be added to the platform as time goes on, especially if the technology is used in closed iot ecosystems. With the correct security protocols in place, edge computing platforms can also be extended to third-party suppliers in the supply chain, thereby sharing data and potentially increasing the efficiency of business processes further.
The introduction of wi-fi-enabled embedded devices and IoT in industrial applications has paved the way for improved efficiency, new business practices and revenue streams, but the transition has also created a pathway for hackers to potentially exploit. If an edge computing platform is being used to analyze data in different areas within an industrial framework, suspicious network traffic or device activity can be discovered quickly, potentially stopping attack in their tracks before a full network is compromised. Full spectrum recently published a new wireless standard for the industrial internet of things, IEEE 802.16s-2017. This new global standard has the potential to encourage IoT device use in industry. But without a means to keep the data-related costs of such innovation down as well maintaining clear visibility into IoT device networks through edge computing, clients may not be able to enjoy the full business benefit of connected systems.
Edge computing has the potential to bring down the cost of data management by controlling network bandwidth and keeping data analysis and storage within closed systems, rather than pushing it out to the cloud and data centers. This can also resolve the challenge of data build>up in closed iot systems which can incur further expense. It's important that those considering edge computing applications are made aware of the potential for long-term savings, as well as improved efficiency, security and network speed.
The Challenge of Ageing Infrastructure
Industrial systems often have long replacement cycles and legacy systems are still in use in many businesses. While iot adoption is still in the early stages, overlaying this? Together with embedded systems and edge computing ? Is likely to be a challenge without help, especially as the concept is so new. It admins may also have a tough time understanding the decentralized, autonomous nature of edge computing architecture and platforms.