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Edge Computing - Future and Business Applications
Edge Computing - Future and Business Applications

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Edge computing in practice just means that when something is done on a device relating to the internet, such as a web search, the data is processed as close to the source of the action as possible. So normally, when I go onto Google and search for something, my search request is sent to Google’s cloud, it is processed, data is retrieved, and then the results are sent back to me. This entire process doesn’t take too long but edge computing seeks to make it even faster.  

The “cloud” is a term for a group of servers on which information is stored. So, depending on where that server is, the request may take some time to fetch results. You can notice this when you select servers that are not near you, if you live in Los Angeles but the server is in Chicago, then you might notice a slight delay in your result. If that server were to be in San Francisco, however, then the result would show up slightly faster. The goal of edge computing is to compute as much data as possible near to where the action is happening, that way thousands of requests are not flowing all over the world multiple times to retrieve one result.  

 

Edge Computing

Image – Edge Computing (Courtesy - TechTarget

Edge computing has its fair share of challenges though, and many of them are the biggest hurdle in its adoption.

  • Locations and Human Limitations: In order to implement edge computing more companies will need to invest in more locations, more data centers, more servers and most importantly, more people. The issue lies in the fact that it isn’t always feasible to have an IT admin at each location or to have someone who always watches over every device or server. The key will be to enable remote development and monitoring to reduce location costs and IT experts on-site. 
  • Hardware: Building the hardware of servers and these individual locations will come at a high initial cost. This is not only time-consuming but also difficult to manage and run. It might be a slow process at first.  
  • Latency: Knowing that the goal of edge computing is to increase performance and speed while reducing latency, the question arises of how these companies will ensure they do not experience any latency at each site or through their massive growing network. It will be time-consuming and will require a lot of planning, also money, to ensure their own services do not suffer while providing the best to their customers.  

Innovation comes from places where curiosity is strongest. Many companies want their customers to be as happy as possible so naturally many large companies want to implement edge computing to improve their services especially for the people who rely on them. AWS has been updating its toolset for quite a while and isn’t looking to slow down. Amazon currently offers over 200 device-based services to choose from including Alexa, Echo, IoT device simulator, and AWS IoT Camera Connector. These devices and services they offer are going to rely on more edge computing to be implemented so that each customer has the best performance and experience possible.  

Edge computing can prove to be extremely useful at certain locations or with certain clients in particular fields. Good examples are places such as hospitals, government organizations, and emergency services which rely heavily on data and its processing. Some companies have already started to implement these ideas and practices for use internally and with their clients. Some of the companies who have said they are working on it include Amazon (AWS), Google, Intel, IBM, Dell, and other more specialized ones such as ADLINK, EdgeConneX, and ClearBlade.  

These companies plan to put locations near their largest collection of clients to increase their overall speeds and performance of services and communications. Amazon plans to achieve reduced load times and cut back on wait times for logging into services. For point-of-sale systems or POS, a lot of companies plan to implement edge computing near or on-site retail to increase customer experience. Some ideas in banking were to utilize facial recognition more and use edge computing to ensure quick processing and loading while also reducing fraud or theft.  

Edge Computing SWOT Analysis 

  • Strength
    • Security

      By processing more things away from a centralized network, you can avoid the ‘all eggs in one basket’ issue. If my entire account was stored on one server at Googles data center in Chicago and then that server was to be destroyed or corrupted, I would lose all my data. So, by storing the data in various places closer to the source it improves my data privacy and overall account security.

    • Reduce Latency

      As mentioned, when you can reduce the number of times that you have to call the central cloud, you can cut down on the load time especially in areas that might have limited bandwidth.

  • Weakness
    • Costs and New Storage

      Updating Hardware can be a price heavy initiative. For edge computing, some equipment will need to be either installed or replaced for its end goal to be more achievable. This is mostly to be carried out on the company's end and not the consumer, but this could easily delay edge computing being used and adopted at smaller companies and platforms.

  • Opportunities
    • Improved Services and Revenues

      If places such as airports, retail shops, phone stores, kiosks, etc. leverage this technology, it could help companies improve their revenues and sales. Another example could be if a company has a web-based app and a fast-food chain, this technology can help with faster delivery of services like when the customer wants to pick up their orders. At airports when people enquire about flights or want to pick a new seat, if the service is near the airport, then it could help reduce the long lines and improve turnaround time.

  • Threats
    • Loss of Data

      One of the advantages of edge computing is that after data processing it will discard any data that isn’t needed to save time, however, if any part of the data that isn’t used and is discarded fully then it can result in a small loss of data. Engineers will have to be sure to thoroughly plan the process and develop products that well consider the flow of data and its complexities.

What really makes edge computing special is that while its process might be slow to begin rolling out, you might not even notice it once it happens. Every year our services get better and perform better which we barely even notice. The amount of work and time that is put into shaving off milliseconds of load time is insane yet many large companies and even some smaller ones are committed to providing the best product or service in the market which is a high bar to set these days. I look forward to seeing where our devices and online services are at in 2025, which seems to be a common goal for large companies to have implemented more aspects of edge computing.

Read more such articles on technology innovations from InfoCepts authors Eric Young and Shailesh Barde.


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