The Edge of Computing in Realtime Applications
Edge computing is a distributed computing platform that makes computation and data storage closer to sources. Let’s discuss how this works in realtime applications.
Edge computing has transformed the way people handle, process, and deliver various sources of data from many devices around the world. The increasing growth of mobile devices and new applications need real-time computing power, driving edge-computing systems.
Modern networking technologies such as 5G wireless allow edge computing technology to create and support various applications regarding video processing and analytics, self-driving cars, robotics, etc. In this post, we have defined definitions, benefits, and the potential future of edge computing.
What is edge computing?
Edge computing is a part of a distributed computing topology allowing information to be close to the edge. An edge is an ideal place for people and things to produce and analyze information. At its fundamental level, edge computing brings computation and data storage close to the devices gathering data rather than relying on a centralized location. Edge computing helps data, especially real-time data not to suffer latency issues affecting the performances of mobile applications. Additionally, firms save money by having data processed locally and reducing the amount of data that needs to be processed in a cloud-based location.
Nowadays, many IoT devices are capable of collecting, storing, and processing more data than ever. This creates opportunities for firms to optimize their networks and relocate processing functions closer to the network edge. Thus, people use edge computing to analyze and apply real-time data much closer to the users. Today, edge computing takes this concept, showcasing computational capabilities into nodes at the edge to process and deliver information.
Defining enormous benefits of edge computing
Reducing latency
The ability to improve network performance by reducing latency is one of the huge benefits of edge computing. Edge computing devices analyze data locally or near centers, so the information doesn’t have to travel as far as it is under traditional cloud computing. Commercial technology allows data to go as fast as two-thirds the speed of light.
Processing data closer to the source and reducing the distance helps edge computing technology greatly reduce latency. This can boost the speeds for end-users in microseconds rather than milliseconds. Thus, the speed advantage of edge computing technology is of utmost to your network. Edge computing brings value propositions for IoT applications in various fields. So outsourcing software development service apply edge computing to the custom software development process. That helps to improve the performance, security, and productivity of companies.
Ensuring the security
Another benefit of edge computing is providing security advantages. Cloud computing architecture is centralized, making it vulnerable to distributed denial of service (DDoS) and power outages. Meanwhile, edge computing technology distributes processing, storage, and applications in a wide range of devices and data centers, making it difficult to disrupt the entire network.
As people process data on local devices rather than transmit it back to the center, edge computing cuts down the amount of data at risk. Thus, edge computing helps developers ensure the security of data during custom software development projects.
Scalability
As firms are growing, they wouldn’t predict their IT infrastructure needs. So hiring software outsourcing services might be their solution to maintain their IT infrastructure. Building a data center is quite expensive, which makes it difficult for firms to activate their future plans. Fortunately, the emergence of cloud computing and edge computing makes it easier for companies to scale their business operations.
Companies don’t need to establish central and private centers for collecting, storing, and processing data. They combine colocation services with edge computing through quick reach and cost-effective edge networks. Therefore, offering a less expensive route to scalability is one of the benefits of edge computing.
Enhancing the versatility
Partnering with local data centers helps companies easily target desirable markets without huge investments in IT infrastructure expansion. Edge computing centers serve end-users effectively and efficiently with minimal physical distance and latency.
Additionally, edge computing empowers IoT devices to collect data rather than wait for people to log in with their devices. Edge computing technology is always connected and generates data for future analysis. So one of the best benefits of edge computing is the versatility..
Reliability
Edge computing offers better reliability as well. This technology makes IoT devices and edge computing data centers closer to end-users, so there is less opportunity for network problems in a far location affecting customers. Besides, IoT edge computing devices continue operating effectively on their own as they solve essential processing functions natively.
Locating edge computing systems in data centers geographically makes them closer to end-users and distributes data processing. These edge computing networks ensure a seamless experience for customers expecting to access the content and mobile applications from far anywhere. Furthermore, many edge computing devices and data centers linked together make it more difficult for any singular failure to shut down entire services.
How edge computing works
With the huge benefits of edge computing, how does edge computing work? Edge computing works through capturing and processing data as close to the data source and desired event as possible. It counts on sensors, computing devices, and machine learning to gather data and feed it to edge computing. Depending on the desired outcomes, data might feed analytics and machine learning systems, offering visibility into the current state of a device and product.
Nowadays, data calculations take place in the cloud. As organizations migrate the edge model with IoT devices, it is essential to deploy edge servers, gateway devices, and other gears. It helps reduce time and distance for edge computing tasks and connects through the entire infrastructure, especially running custom apps. The infrastructure might include smaller edge computing data centers located in cities, rural sites, or clouds easily moved across clouds and systems.
However, edge data centers are not the unique way to process data. In some cases, IoT devices may process data onboard, or send it to a mobile device, an edge server, or a storage device to solve calculations.
Edge computing offers flexibility, agility, and scalability that are needed for growing business cases. For instance, a sensor provides updates of temperature for storing and transportation. Software outsourcing services might consider the operation of edge computing during the custom software development process.
What are the challenges of edge computing?
The edge computing architecture comprises compute systems, connectivity, and storage. When developing a custom software development product, it is essential to require software developers to have a connected site or device. Consequently, this leads to some challenges of edge computing such as costs, delays, and even the closure of many custom software development projects.
Inefficient bandwidth: If a firm has many devices collectively producing data, the organization is likely to store that data in the cloud. However, transferring raw data to the cloud directly from edge devices might be difficult.
Speed bottlenecks: Firms prefer connectivity networks such as 5G, DSL, etc that prioritize data from cloud to edge as most mobile applications use this approach. Meanwhile, edge computing technology wants to push data in the other way. Consequently, uplink speed might lead to a bottleneck. If people use a central cloud to store data and the cloud goes down, the data is out of reach until resolved, leading to potential loss.
Processing little amount of information: As edge computing processes and analyzes a certain set of information, many firms tend to lose valuable information.
Ineffective security: 66% of software development teams see edge computing as a threat to data organizations. When people solve data through different devices, it may not be as secure as a centralized or cloud-based system. That makes it essential for perceiving the potential vulnerabilities regarding security and ensuring IT teams secure the systems.
No microservice support: Unlike traditional cloud computing, people deploy edge computing in parallel to various geographical diverse points of presence. However, these areas have many edge computing systems across various regions that need to plan and monitor carefully.
Edge computing and cloud computing: Key differences
Companies
- Edge computing: Helps to boost business operations with latency concerns. Thus, companies that have limited budgets use edge computing technology to save money.
- Cloud computing: is suitable for custom software development projects and firms that deal with massive data.
Programming
- Edge computing: People use edge computing for developing software programs. All those programs require platforms that have different runtimes.
- Cloud computing: is better for actual programs since each program will have one target platform and a programming language.
Security
- Edge computing: Edge computing requires robust security such as advanced authentication approaches and proactive tackles.
- Cloud computing: requires a less robust security plan.
Some best edge computing examples for daily life
- Autonomous vehicles: Self-driven cars and many vehicles need a massive set of data from their surroundings to operate effectively in real-time. There is a delay for vehicles if people use cloud computing.
- Streaming services: Services such as Netflix, Hulu, Amazon, etc create a huge network of IT infrastructure. Edge computing helps provide a smoother and faster customer experience through edge technology.
- Smart home appliances: Like streaming services, the increasing growth of smart homes poses an issue. There is too much network load to rely on cloud computing. Processing, and storing data are closer to the data source meaning less latency and quicker response times in emergency circumstances.
Looking to the future
Many firms are changing their move towards edge computing for its huge benefits to daily life applications. However, edge computing technology is not the only solution. Regarding computing challenges, cloud computing might be a viable solution. That’s why cloud computing providers have started combining IoT technologies with edge computing. In this post, we have given you a brief overview of edge computing regardless of definition, benefits, examples, and challenges. Hopefully, you will have a better understanding of edge computing.
Special thanks to Tremis Skeete, Executive Editor at Product Coalition for the valuable input which contributed to the editing of this article.
