Edge Computing: Implementation, Advantages, and Disadvantages

Edge Computing: Implementation, Advantages, and Disadvantages

The range of enterprise technology at present has taken a giant leap. The race to ‘achieve more in less time has been the motto that many organizations around the globe are following. Increasing processing capability at the edge has become a popular trend in recent years, providing the groundwork for autonomous systems. As a result, firms may increase efficiency and production while employees can focus on higher-value jobs.

What Do You Understand About Edge Computing?

Edge computing is a distributed/network computing strategy in which processing occurs near the point where data is collected and processed rather than on a centralized server or in the cloud. With this new architecture, you can access sensors that collect data and edge servers that securely analyze data in real time and on-site. You may also connect additional devices to the network, such as mobile phones, computers, etc.  

Data processing at the edge aids in the quick application of analytics and the deployment of AI capabilities, which is interesting to know. Furthermore, edge computing allows for seamless data transmission with no latency and lower network bandwidth and storage needs.  

  The usefulness of edge computing has been realized at the global level. The below-mentioned statistics say it all.  

  • According to Gartner’s report, by 2022, 50% of enterprise-generated data will be generated and processed outside of centralized cloud data centers via edge computing.  
  • Based on IDC’s Worldwide Edge Expenditure Guide, enterprise & service provider spending on software, hardware, and services around edge solutions will expand at a rapid pace through 2025, reaching around $274 billion.  

Edge Computing & Relationship with Cloud

Many question whether edge computing is a subset of cloud computing or vice versa. The fact is that edge computing works in tandem with the cloud to provide a customizable solution built based on data collecting and analysis specific to each enterprise. 

ImpactQA - Edge Computing & Cloud Computing

The edge is appropriate in terms of specific workloads for handling real-time data collecting and processing. Simultaneously, the cloud aids in the provision of a centralized site for large-scale analytics. They work together to provide real-time insights on performance and enable projects like machine learning. 

Why is Edge Computing Gaining Popularity?

  • Supports the automation of all business processes
  • Motivates operational capabilities  
  • Presents a less costly strategy to achieve scalability
  • Better performance & security across all devices
  • Lowers bandwidth to offer low transmission cost  

Use Cases of Edge Computing

The implementation of edge computing can be seen in our day-to-day lives. Here are a couple of use cases that can prove helpful in understanding the value of this computing paradigm.

A. Edge Computing in Smart Homes

Smart homes have become the talk of the town, with several cities in the United States already benefiting from intelligent automation to make their lives as comfortable as possible. IoT devices are the primary elements of the smart home and are responsible for data collection and analysis.

The collected information is typically transmitted to a specialized remote server for storage and processing. However, the existing configuration may have several flaws, such as security, latency, etc. Edge computing decreases roundtrip time and simplifies processing and storage by allowing sensitive information to be analyzed at the edge. In addition, your voice-based assistance devices, such as Google Home, will reply to your orders more quickly, thanks to the presence of edge computing.  

B. Edge Computing in Fitness Tracker

Consider the case of a fitness tracker. Its primary purpose is to keep track of the user’s heartbeat. When edge computing is used, it may be converted into a far more complex information-delivery device, such as providing data when the user’s heartbeat stops. It’s a life-saving breakthrough since the gadget can instantly contact an EMT service, which may provide rapid medical aid. Because edge computing produces low latency, the delay caused is minimal, allowing the EMT service to respond quickly.

C. Edge Computing in Smart Tunnels  

The development of a smart tunnel in Spain illustrates how edge computing can be combined with traffic safety measures. The smart Cereixal tunnel in Galicia uses edge computing and 5G technology. Data is collected and analyzed using cameras, sensors, and connected vehicles.  

The supervisors can remotely monitor what is happening inside the tunnel. Drivers entering the tunnel are also informed of potential delays, the presence of pedestrians, and any emergency vehicles requiring a quick passage. At the exit, drivers can also get information about weather conditions and traffic jams.   

Advantages of Edge Computing

  • Better Speed: Edge computing offers improved speed and lower latency to permit faster data processing  
  • Improved Scalability: It delivers a cost-effective path to scalability and adaptability, thereby permitting businesses to enhance their computing abilities  
  • Security: Since a large amount of raw data is processed close to secure edge devices, it ensures data privacy and security when transmitting data across international borders.  
  • Low Bandwidth Usage: Edge computing enables IoT apps to use less bandwidth, allowing them to function normally even when connectivity is limited

Disadvantages of Edge Computing

  • Abide Regulations: For a business to stay on track, data is king. When the data/information is gathered at the edge server, it becomes imperative to check for compliances & regulations thoroughly.  
  • Network Susceptibility: The networked architecture of edge computing increases known attacks. Such a system is susceptible to security flaws and malware infiltration.  
  • Balancing Bandwidth: As more data is secured at the edge, more computers are required. As a result, the bandwidth must be increased. Therefore, the implementation of edge computing necessitates the balancing of network bandwidth.  
  • Technical Issues: Since these Data Centers lack the comprehensive infrastructure of a typical Core Data Center, they must work around some technical challenges.   

How is QA Crucial in Edge Computing?

The tiered architecture of edge computing involves a lot of interdependent components. It includes:  

   

  • Edge software
  • Edge hardware
  • Edge gateway
  • Interconnection
  • Cloud
  • Data syncing  

The value of Quality Assurance (QA) may be evident during the authentication of the functionality for each of the components mentioned above and further testing to ensure that they operate in harmony as part of an integrated structure.  

 Some of the testing activities which are performed on edge components are: 

  • Unit testing
  • API testing
  • Performance testing
  • Database testing
  • Integration testing
  • Security testing

With ImpactQA, you can achieve quick QA and software testing service solutions for your edge systems. Our experts are dedicated to ensuring customer satisfaction and managing projects with meticulous analysis and reporting.  

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