Cloud computing has secured its place as the traditional approach to network infrastructures. In recent years, another approach called edge computing has also gained popularity.
One might think that edge computing, a more decentralized model of computing, is here to replace the traditional cloud architectures. This is not the case.
Edge computing and cloud computing are both exceedingly important infrastructures in Industry 4.0.
As it is important to know which one to use to improve the management and maintenance of an IT system, this article introduces the basics and compares the benefits of both infrastructures.
One might think that edge computing, a more decentralized model of computing, is here to replace the traditional cloud architectures. This is not the case.
Edge computing and cloud computing are both exceedingly important infrastructures in Industry 4.0.
As it is important to know which one to use to improve the management and maintenance of an IT system, this article introduces the basics and compares the benefits of both infrastructures.
Cloud computing
Centralized data collection and processing
In traditional cloud computing, the data is gathered and processed in a centralized location, usually in a data center. All devices must be connected to the cloud to be able to access this data or use the associated applications.
Due to everything being centralized, the cloud is easy to control. Cloud computing is to a certain degree outsourcing computing resources, which are hosted by an external party and are in a virtual space – the cloud.
Due to everything being centralized, the cloud is easy to control. Cloud computing is to a certain degree outsourcing computing resources, which are hosted by an external party and are in a virtual space – the cloud.
60 years in the making
The history of centralized computing started already in the early 1960s.
During those early times of technology, storing data in CPU was very expensive, and for that reason, the client-server architecture was popular with mainframe and terminal applications. File servers gained popularity for storing huge amounts of information.
During those early times of technology, storing data in CPU was very expensive, and for that reason, the client-server architecture was popular with mainframe and terminal applications. File servers gained popularity for storing huge amounts of information.
The late ’90s introduces the term “cloud”
One of the first definitions of cloud computing dates to 1997 when Professor Ramnath Chellappa referred to cloud computing as the “computing paradigm where the boundaries of computing will be determined by economic rationale rather than technical limits alone.”
By that time, the cloud metaphor was already used for virtualized services. It originates from the cloud symbol used by flow charts and diagrams to symbolize the Internet.
By that time, the cloud metaphor was already used for virtualized services. It originates from the cloud symbol used by flow charts and diagrams to symbolize the Internet.
The cloud as we know it
Amazon Web Services launched its public cloud in 2002, this being the introduction to the modern-day cloud.
In the present day, one of the best scenarios for the use of a cloud is a test and development environment. Cloud users can store files, data, and applications on remote servers and access this data with the help of the Internet.
In the present day, one of the best scenarios for the use of a cloud is a test and development environment. Cloud users can store files, data, and applications on remote servers and access this data with the help of the Internet.
Edge computing
Moving resources closer to users and devices
Edge computing is a paradigm change compared to centralized computing. It enables the devices to process data right there, where the data is collected. The computation is mostly or completely performed on distributed device nodes.
With edge computing, the data can be gathered, analyzed, and applied faster than ever before.
With edge computing, the data can be gathered, analyzed, and applied faster than ever before.
The beginning: CDN introducing the new nodes in the 1990s
The history of edge computing began in the 1990s when the content delivery network (CDN) by a cloud service company Akamai Technologies was launched.
The CDN introduced nodes, that stored cached static content, at locations geographically closer to the end-user.
The CDN introduced nodes, that stored cached static content, at locations geographically closer to the end-user.
Optimizing data flow
In the setting of industrial IoT, edge computing enables industrial equipment to make decisions without human intervention.
Performing computations at the edge of the network reduces network traffic, which reduces the risk of a data bottleneck. It optimizes the data flow to minimize operating costs.
In edge computing, the computing resources are moved as close as possible to end-users and devices. This is especially useful in locations with harsh conditions, such as remote or outdoor areas with poor quality connections.
Edge computing also helps to reduce unplanned machine downtime, due to its continuous connectivity. The edge technology may interact with a centralized cloud, but it does not need contact with it.
Performing computations at the edge of the network reduces network traffic, which reduces the risk of a data bottleneck. It optimizes the data flow to minimize operating costs.
In edge computing, the computing resources are moved as close as possible to end-users and devices. This is especially useful in locations with harsh conditions, such as remote or outdoor areas with poor quality connections.
Edge computing also helps to reduce unplanned machine downtime, due to its continuous connectivity. The edge technology may interact with a centralized cloud, but it does not need contact with it.
Comparing the two S's: Speed and Scalability
As mentioned earlier, edge computing is not here to replace cloud computing or vice versa.
Even though they are not direct competitors, to know which infrastructure to use, it is necessary to compare the main benefits.
Even though they are not direct competitors, to know which infrastructure to use, it is necessary to compare the main benefits.
Speed - Only relevant data counts
In cloud computing, the geographical location of data centers is often far from the data entry point.
The centralized nature of cloud computing makes it difficult to process data gathered from the edge of the network quickly and effectively. This latency can lead to difficulties when data must be processed in real-time.
The centralized nature of cloud computing makes it difficult to process data gathered from the edge of the network quickly and effectively. This latency can lead to difficulties when data must be processed in real-time.
Edge computing reduces latency
Edge computing increases network performance by reducing latency. It enables data stream acceleration, which includes real-time data processing without latency.
This is possible by processing data closer to the source and reducing the physical distance it must travel. The longer it takes to process data, the less relevant it is.
Edge computing makes your data more relevant, useful, and actionable. It also reduces the traffic load.
Not all the data collected is critical, so sending only relevant data saves bandwidth, and the speed, quality, and responsiveness of the overall service are increased.
An additional moment of downtime might be very costly, and for that reason, the advantages of edge computing should not be missed.
Scalability – Avoiding bottlenecks
Cloud computing is based upon a scalable data center infrastructure, and so it can expand its storage and processing capacity as needed. It allows companies to start with a small deployment of clouds and expand efficiently and fast.
Cloud computations need to transfer a lot of data over the internet, requiring a high bandwidth network. Scalability limitations are very present in cloud computing since the constant communications between servers and users use up bandwidth and can eventually saturate it.
To improve the performance, optimizations for the data exchange bottleneck have been done, but cloud computing is still prone to slow operations.
Cloud computations need to transfer a lot of data over the internet, requiring a high bandwidth network. Scalability limitations are very present in cloud computing since the constant communications between servers and users use up bandwidth and can eventually saturate it.
To improve the performance, optimizations for the data exchange bottleneck have been done, but cloud computing is still prone to slow operations.
No storage worries with the edge
Edge computing is a cheaper choice for a data center. It allows companies to grow their computing capability through the combination of edge data centers and IoT devices.
Edge computing reduces the load on networks by reducing the volume of data pushed back to the core network.
The edge can be used to scale an IoT network without needing to worry about the storage requirements. Adding more devices does not increase the network’s bandwidth demands considerably, and this reduces growth costs.
Edge computing reduces the load on networks by reducing the volume of data pushed back to the core network.
The edge can be used to scale an IoT network without needing to worry about the storage requirements. Adding more devices does not increase the network’s bandwidth demands considerably, and this reduces growth costs.
Two approaches complementing each other
It is clear, that both edge and cloud computing approaches have their benefits as well as their challenges.
Cloud and edge computing do not rule out one another but complement each other.
Sometimes the solution to get high results is to use both technologies. The combination of edge computing and cloud computing can provide the opportunity to maximize their potential and, at the same time, reduce their drawbacks.
Cloud and edge computing do not rule out one another but complement each other.
Sometimes the solution to get high results is to use both technologies. The combination of edge computing and cloud computing can provide the opportunity to maximize their potential and, at the same time, reduce their drawbacks.
We at Treon focus on sensing at the edge. We make it easy to utilize the best of both edge and cloud computing. Our products enable innovation in a wide range of IoT-applications, such as condition monitoring, logistic & asset tracking, environmental monitoring, and more.
Check out our products to learn more about our wireless devices.
Treon developed a wireless vibration and temperature monitoring solution in cooperation with the global leader in fluid engineering, Sulzer. The cost-efficient, easy-to-install, and battery-powered sensor and gateway are the key enablers for the wireless IoT condition monitoring solution, Sulzer Sense!