The other day we were talking about cloud computing and now we come across another invention of edge computing. Now when we talk about cloud, it means that the application is hosted on some other distant computer like IBM, Google to name of. The Edge Computing idea behind the edge services is to push these cloud services close to the edge of the network. It is basically a distributed computing, in which information processing is located close to where things and people produce or consume that information. It basically gathers the data from the beginning at the very machine that processes it and uses it instead of any centralized computing like cloud. In this blog is we going to see about the Edge Computing
Edge Computing are approaching us faster than ever. So we need a service that helps us make local decisions that will help get things easier. Edge computing is transforming the way data is being handled, processed, and delivered from millions of devices around the world. The amount of data that is being transferred through the networks around is massive and it causes a lot of traffic. That’s why edge computing was essentially designed to tackle the problems with bandwidth costs and there is the need for processing real time applications.
What Is Edge Computing?
Edge computing moves IT resources closer to where data is produced and consumed in near real time, traffic from devices is processed and analysed for low latency used cases. It enables data generated by IoT devices to be processed closer to where it is created instead of sending it through the long routes to any cloud. In addition, companies can save money by having the processing done locally, reducing the amount of data that needs to be processed in a centralized or cloud-based location.
Users need robust, secure and intelligent on premise infrastructure for edge computing. Low latency, security and offline access is what it offers. This is critical for technologies such as self-driving cars and has equally important benefits for business. The ability to process data without ever putting it into a public cloud adds a useful layer of security for sensitive data.
Why Edge Computing?
Since 5G is driving the need for more flexible cloud based infrastructure, edge computing plays an important role. With the increased application of IoT, there has been a big amount of raw data flowing through networks and it just causes more flaws than benefits for data transfer. Also many times sensitive data like audio clips are send over a wide range and may have big scale effects if not handled properly. So it is better to have the data prepared, stored and handled locally. That’s where edge computing comes into role. Here are few reasons as to why it is important.
Latency: It seems really easy to analyse data locally rather than at a remote data centre or cloud. Because data processing and storage will occur at or near edge devices, IoT and mobile endpoints can react to critical information in near real-time.
Congestion: It can also help to reduce the pressure on the wide-area network. This can improve efficiency and keep bandwidth requirements in check. This is a significant challenge in the age of mobile computing and IoT. Instead of overwhelming the network with a constant flood of relatively insignificant raw data, edge devices can analyse, filter, and compress data locally.
Bandwidth: At places like cruise ships, offshore oil platforms, remote military outposts, and ecological research sites the network can be weak and almost unreliable. Edge computing helps in solving these issues. Since cloud cannot work in such places, local compute and storage resources can enable continuous operation.
Surely it can improve application performance by increasing data processing, it still has various challenges that are still to be taken care of. Even if it requires smaller bandwidth, there is a need to adjust them for the better use of edge computing. Following are some of the other problems edge computing has:
1. Distributed computing: Businesses will need to see location as an additional aspect of compute. Computing now needs to include networking as a key element, with a greater focus on east-west traffic. With compute located at both the core and the edge, application data traverses the network in each direction, sharing data and dealing with access rights. This means data transfer is no longer a simple one-way process.
2. Backup: The need for edge computing typically emerges because separate locations are collecting large amounts of data. Enterprises need an overall data protection strategy that can take care all this data. Network bandwidth requirements will be just as critical as storage media considerations when deciding how to protect these assets, because backup over the network may not make sense.
3. Data accumulation: Data is a key business asset, and collecting it at the edge brings new challenges and can create liabilities if it’s not handled as per the rules. Data storage and access are critical, both of which will need to encompass the network as part of the data lifecycle.
It might be a real enabler to autonomy, whether that’s autonomous vehicles, autonomous drones. It is going to enable better AI and ML because again, there are going to be more compute resources available out.
There are lot of new things that will be enabled by Edge in the field of security and IoT. Moreover, 5G doesn’t work without edge computing. For faster phones and better experiences on various devices, there has to be edge computing. Some concepts and studies try to see what decisions or what intelligence can an edge device do before it needs to phone home(the cloud base) and you start to realize that with some training, edge devices can become pretty self-sufficient and can maybe make some decisions.
Edge also has a future in industrial sector. All industries have the potential for transformation, thanks to edge computing. But it will depend on how they address their computing infrastructure. These companies can use edge to speed up their digital transformation. Manufacturers need faster processing services for the data. Edge can really help to decrease work time and increase efficiency. Healthcare industry requires devices to track the user exercise rate and give advice and they are looking forward to new innovations with the emerging use of edge.