Where there are advantages, there are risks—learn about the elements of Edge Computing.
Many Cloud-based applications use a Data Center with servers as a central location to process information generated by devices such as smartphones, tablets, and IoT devices for big data processing and analytics. This model imposes increasing demands on the communication and computing infrastructure, with an inevitable problem that has to do with the quality of service and the user experience.
The concept of Edge Computing is based on moving part of this computational load towards the Edge of the network and not using centralized servers in order to take advantage of the currently untapped computational capacity at the Edge nodes, such as stations, routers and switches. This article considers the challenges, opportunities and benefits of Edge Computing.
Cloud computing is not the best option for the new Internet of Things applications (among other reasons, because you cannot know with certainty where the public Clouds are located or whether they are simply on another continent). These “things” can be a person with a heart monitor implant, a farm animal with a biochip, a car that has built-in sensors to alert the driver when maintenance is necessary, or any other object that can be assigned an IP address and given the ability to transfer data over a network.
In these cases, computing must be done closer to the source so that data traffic can improve the service that is delivered. This benefit can also be generalized to any web-based application which depends on the processing of information, since the computing is done at peripheral nodes closer to the application users, and this could be exploited as a platform for application providers to improve their services.
Edge devices generate large data streams; on the other hand, it is not possible to make decisions in real-time when the analysis is carried out with data in the Cloud, which is almost always at a distance.
Using current Cloud infrastructure poses high latency, and this is a challenge between a connected device and the Cloud. The travel time from Sydney to Los Angeles is approximately 175 ms (milliseconds), which is far from the needs of latency-sensitive applications.
Advantages of Edge Computing
By bringing data analysis tools and applications closer to the real data source:
- It reduces the physical distance data must travel, and the time required for the transfer.
- It greatly reduces network congestion and periods of inactivity or lag.
- It increases responsiveness, speed, and overall service quality.
Unlike Cloud computing, which is based on a single Data Center, Edge Computing works with a more distributed network:
- It eliminates the round trip to the cloud, thus reducing latency and offering real-time responsiveness.
- It keeps the heaviest traffic and processing closer to the application and the devices of the end-user to dramatically reduce latency, and leads to automated, real-time decision-making, improving the user experience.
Edge Computing offers local Edge Data Centers for data storage and processing.
- Businesses can depend on reliable connectivity for their IoT applications, even when cloud services are affected.
- Edge computing allows IoT applications to use less bandwidth and operate normally under conditions of limited connectivity.
Businesses can reduce their costs considerably.
- Decrease required bandwidth.
- Replace Data Centers with Edge Device Solutions.
- Reduce data storage requirements.
Disadvantages of Edge Computing
Where there are advantages, there are risks, and Edge computing is no exception. That is why the disadvantages must be taken into account.
A distributed system is much more complex than a centralized Cloud architecture. An edge computing environment is a heterogeneous combination of various components using new technology, produced by different manufacturers, and communicating with each other through a variety of interfaces.
IoT devices often transmit trivial information, such as temperature and humidity. Manufacturers have neglected to implement strong security measures on their devices, and some IoTs are susceptible to malicious attacks (mostly denial of service).
Less robust infrastructure
These Data Centers do not have the complete infrastructure that we can usually find at a Core Data Center, which means needing to overcome some technical challenges.
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