Edge Computing
Edge computing devices are the hardware that drives the application of edge computing across diverse industries. They are used to accomplish different tasks depending on the software applications or features they’re provisioned with. For edge devices to be smart, they need to process the data they collect, share timely insights and if applicable, take appropriate action.
In this article, I want to give you some background knowledge on the topic “Edge Computing”
Edge computing is computing that takes place at or near the physical location of either the user or the source of the data. By placing computing services closer to these locations, users benefit from faster, more reliable services while companies benefit from the flexibility of hybrid cloud computing. Edge computing is one way that a company can use and distribute a common pool of resources across a large number of locations.
Why is Edge Computing important?
Edge computing is important because it creates new and improved ways for industrial and enterprise-level businesses to maximize operational efficiency, improve performance and safety, automate all core business processes, and ensure “always on” availability. It is a leading method to achieve the digital transformation of how you do business.
Basic steps for implementing effective edge computing
However, even easier-to-use edge devices still require users to learn and understand how to apply them in individual process applications. Here are some basic steps for implementing effective edge computing:
1. Strive to identify pain points and operations that could benefit from edge computing, even though potential opportunities may not be apparent in existing applications and networks.
2. Recruit OT and IT staffs who can show where edge computing might solve problems and improve production, and invite all stakeholders to develop a plan for migrating to edge devices and software;
3. Draft edge program specifications based on requirements such as application cycles, lags and turnaround periods, and required response times to determine how close to real-time an edge-computing solution will need to be, or if a cloud service would be sufficient;
4. Determine what data should be handled by local/edge devices, where to retain it, what should be reported to the cloud and administrative/business platforms, and on what schedule to deliver it.
5. Research and decide which edge components and enabling devices will satisfy the edge project’s requirements, such as where to locate computing functions, how to tie in legacy equipment, what Ethernet infrastructure and communication protocols to use, and whether to employ wired or wireless and linking to PLCs and servers.
6. Evaluate and enable the most appropriate cybersecurity capabilities are each stage of the edge computing application and its network.
Edge computing examples
Edge computing is implemented in commercial, industrial, and military applications. Here are lists of edge computing applications.
· Virtual Assistants
· Autonomous vehicles
· Oil rigs
· Assembly line and surveillance cameras
· Soldier’s wearable gear
· Navigational assistance
Does the Edge Replace the Cloud?
Edge computing works hand in hand with the cloud to provide a flexible solution based on the data collection and analysis needs of each organization. For real-time collection and analysis, the edge is ideal for certain workloads. At the same time, the cloud can provide a centralized location for large-scale analytics. Together they provide real-time and longer-term insights into performance and power initiatives like machine learning and asset performance management.
Advantages and disadvantages of cloud computing
Advantages:
· It offers high speed, reduced latency better reliability which allows for quicker data processing and content delivery.
· It offers better security by distributing processing, storage, and applications across a wide range of devices and data centers, which makes it difficult for any single disruption to take down the network.
· It offers a far less expensive route to scalability and versatility, allowing companies to expand their computing capacity through a combination of IoT devices and edge data centers.
Disadvantages:
· It requires more storage capacity.
· Security challenges in edge computing are high due to the huge amount of data.
· It only analyses the data.
· Cost of edge computing is very high.
· It requires advanced infrastructure.
Conclusions
Edge computing has changed the way data is accessed and computed rationally. As per the research, the IoT base worldwide is expected to reach 75.4 billion devices. This estimate is sufficient to understand how they have been incorporated across sectors. Edge computing architecture is expected to reach the peak earlier than expected with the research and developments in artificial intelligence and connectivity technologies with the increase in demand for smart IoT applications.
References
https://www.ukessays.com/essays/computer-science/edge-computing-and-cdn.php
https://searchdatacenter.techtarget.com/definition/edge-computing
https://www.exorint.com/en/blog/what-are-edge-computing-devices
https://www.redhat.com/en/topics/edge-computing/what-is-edge-computing
