#Technology #Business #IoT #Data Science
Power of the Edge Computing
An Innovative Extension to the Cloud Computing, the Internet of Things (IoT), and the Big Data Analytics
Purpose
The purpose of this article is to introduce Edge Computing as a functional and non-functional extension of the IoT (Internet of Things) and the Cloud Computing service model. Edge Computing is a powerful extension to the Cloud and IoT-based Big Data Analytics projects.
Let me set the context by giving you a brief background on the Cloud and the IoT relationship, then introduce Edge Computing in this context.
Background
We all know the recent trends in Cloud Computing. The Cloud marked a paradigm shift in Information Technology and Computing field.
The IoT Cloud is a critical player in the data ecosystem of large business organisations. The central role the Cloud plays in the IoT is to facilitate data integration of the solution components effectively.
IoT solutions are mainly used to provide real-time information to consumers.
The data required to generate real-time information can be massive in scale.
The Cloud, along with computing power, storage, networking, analytics, metering, billing, and other service management components, can make this vast information available to consumers.
The integration of the Cloud to the IoT can create new revenue streams for business organisations. Integrating the Cloud with the IoT can create new business models enriched by real-time analytics and directly consumed information simultaneously.
In other words, the IoT is empowered by the Cloud capabilities. Without the Cloud, the IoT can hardly add any value due to its real-time data and information-rich nature.
The addition of the Cloud to the IoT can also contribute to improved security, availability, scalability, and performance of the IoT solutions.
Cloud providers have rigorous security, availability, sclability, and performance metrics established based on a service consumption model. In particular, the IoT-enabled Cloud systems seem to pose additional security measures.
However, the next critical innovative integration to IoT Cloud is the Edge Computing.
After the Cloud Computing, the Edge Computing can be seen as a paradigm shift in the IT industry.
What is the Edge Computing?
The purpose of the Edge Computing is to bring computing and data storage components close to the service consumption locations.
This innovative approach can dramatically improve network bandwidth and network response times especially by reducing network latency.
The key technical functionality of Edge Computing is to reduce the volumes of data and ease the data traffic in costly business networks.
This functionality can lower detrimental network latency and reduce data transmission costs.
The key use case for Edge Computing is the computation offloading for real-time IoT applications.
The prime example for computation offloading use case is facial recognition data in airports and other secure public places.
The computation offloading is also widely used for computer games based on virtual reality, augmented reality, cognitive computing, and artificial intelligence features.
Edge Computing gained significant acceptance from various industries and business applications.
For example, Edge Computing is currently being used by smart city projects, self-driving car systems, and home automation initiatives.
What is special about these applications and initiatives?
These applications and initiatives are data-hungry, in fact, they use streaming Big Data as their main input mechanism.
There are several requirements and use cases that these data sets that can be injected from multiple remote sites.
Therefore, the Edge Computing solutions implemented in local sites can provide tremendous support to the initiatives by storing, analysing, filtering, and only sending the essential streaming data to the target IoT systems and the Cloud storage.
Architectural Importance of Edge Computing
When integrated with Edge Computing in the IoT ecosystem, The Cloud Computing service model can add better business value to the IoT based Big Data and Analytics solutions.
The main architectural benefit is that Edge Computing can do the filtering for the Cloud systems to focus on the usable data. Edge Computing can do the heavy lifting for Cloud systems.
Therefore, the IoT solution architects and designers need to understand the Cloud Computing service models leveraging the Edge Computing design constructs and lead the solutions considering these key technology components in an integrated way.
As architectural decisions, to obtain optimal performance, desirable scalability, higher security, higher availability, and lower costs, we must integrate the Cloud and Edge Computing for the IoT and the Big Data Analytics solutions. These critical architectural decisions must be made at the macro design level and mandated for granular details at the micro design levels in the solution lifecycle.
Conclusions
We understand that Edge Computing can be a powerful extension to Cloud Computing and consequently contribute to the functionality, performance, scalability, availability, and security of the IoT and Big Data Analytics solutions.
As IoT solution architects and designers, being aware of the capabilities of the Cloud technology stacks, the Edge Computing mechanism, and their powerful management tools can be extremely beneficial in creating large-scale commercial IoT and Big Data Analytics solutions.
This knowledge, capability, and architectural governance consideration for integrated solutions is a technical leadership requirement for the IoT solution architects and designers to add desired business value to the commercial IoT and Big Data Analytics solutions.
In my next article, I plan to introduce Fog Computing (another innovative architectural construct) related to the Edge & Cloud Computing concepts.
Related Articles
You may also check my other articles, from an architectural standpoint, relevant to this topic.
References
The following resources can provide useful insights into the recent progress and technical details for Edge Computing.
Edge Computing: From Hype to Reality (EAI/Springer Innovations in Communication and Computing)
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