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Edge Computing

Edge Computing: Unravelling Its Fate

Edge computing burst onto the tech scene several years ago with great fanfare and promise. It was heralded as a revolutionary new paradigm that would change computing as we knew it. By pushing computation and data storage closer to the “edge” where local devices and sensors reside, rather than relying solely on the cloud, edge computing aimed to reduce latency, enable real-time data processing, improve reliability, and enhance security. The potential benefits for IoT, AI, AR/VR, autonomous vehicles, and other emerging technologies were tremendous.

However, the heady optimism surrounding edge computing has dampened somewhat in recent years. The technology has not yet lived up to its full disruptive potential. There are several key factors that help explain what happened to edge computing:

  1. Complexity of implementation – While conceptually straightforward, actually deploying and managing edge networks at scale has proven difficult. Integrating heterogeneous devices, optimizing latency across geographies, allocating workloads, and orchestrating connectivity across edge and cloud introduces daunting complexity. The lack of unified standards and best practices has hindered adoption.
  2. Cost – Building out distributed infrastructure across metro areas and globally requires enormous capital expenditure. For many companies, the costs have outweighed the promised benefits thus far, especially given the immaturity of edge-enabled use cases. The edge business case remains unproven.
  3. Skills gap – Extracting value from edge networks requires expertise in OT/IT convergence, data engineering, middleware, device management, and more. Talent with this precise mix of skills has been hard to come by. Many organizations lack the right in-house teams to deploy edge computing.
  4. Security risks – Pushing out compute power to the edge expands the attack surface dramatically. New edge-specific vulnerabilities combined with inadequate security measures have exposed networks to greater risk. Not enough attention has been paid to securing edge devices and infrastructure.
  5. Regulation – Strict data sovereignty and privacy regulations in some regions have made it difficult to deploy centralized, cloud-reliant edge networks. As edge use cases like self-driving cars and smart factories emerge, regulatory uncertainty persists.

In summary, while edge computing is still in its early stages, the hype has cooled as pragmatic challenges have surfaced. However, the core value proposition remains compelling. As technologies and skills mature, edge is likely to proliferate in clearly defined, high-value use cases. But it may take time for edge computing to truly become the seismic shift many predicted. Careful management of complexity, costs, security, and compliance is needed to unlock the full potential of this important innovation.

Technology

What is Edge computing

Edge computing is a decentralized computing concept in which data processing takes place nearer to the data source, at the network’s edge. When low latency or high security are required, or when it is impractical to send huge volumes of data to a central point for processing, this can be especially helpful.

Additionally, edge computing may be utilized to lessen the stress on central servers and increase a system’s scalability. With the help of computing resources like processors, storage, and memory, edge computing enables Internet of Things (IoT) devices like sensors, cameras, and other IoT devices to carry out local data processing activities.

This can help to reduce the amount of data that needs to be transmitted across a network and can improve the performance and responsiveness of a system.

This can enhance a system’s performance and responsiveness while reducing the quantity of data that has to be transferred across a network. The usage of autonomous vehicles is one instance of edge computing. To make judgments about how to negotiate the road, these cars generate a lot of data from their sensors and cameras, which must be analyzed in real-time. Due to the size of the data involved, it would be impracticable to send all of this information back to a central server for processing. Additionally, doing so would cause lengthy delays that would jeopardize the safety of the vehicle.

Instead, edge computing is utilized to allow the vehicle to evaluate this data locally, allowing for real-time decision-making utilizing onboard computers.Utilizing edge computing in smart cities is another example. In a smart city, sensors and other Internet of Things (IoT) devices are placed all over the place to collect data on various metrics, including traffic patterns, air quality, and energy use.

The quality of life for residents is enhanced by the use of this data to optimize city services. The network would rapidly become overwhelmed if all of this data were transmitted back to a central server for processing. Edge computing enables the data to be processed locally, decreasing network traffic and allowing the city to react more rapidly.

In commercial environments like manufacturing facilities or oil and gas rigs, edge computing may also be deployed. Real-time data processing is frequently necessary for these settings to enhance productivity or spot possible issues before they arise. This real-time processing may be made possible by edge computing, which will increase the effectiveness and dependability of these systems.

Edge Computing

Edge Computing Trends 2022

Workplace safety in the energy sector

One of the most powerful and important benefits of Edge computing is its use in the oil and energy industries. These industries traditionally rely on collecting and transmitting data to surveillance centers located in remote locations. This means that even with real-time sensors monitoring, for example, pressure and conductivity, information about potential emergency situations can reach the data center much later than a critical failure occurs. With Edge computing, anomalies and problems can be tracked and resolved faster than ever before.

Security

Many different emerging technologies, and 5G and IoT are no exception, have their own vulnerabilities. In doing so, edge computing can be used to mitigate potential threats. Traditional centralized networks and data warehouses make it easy for attackers to sign in and access data, but Edge diversifies some aspects of attack and provides better protection.

This does not mean that edge computing is extremely reliable. In fact, for most of 2022, companies will be dealing with vulnerabilities, not the merits of Edge. According to Kollective, 66% of IT teams see this technology as a threat to their organizations.

One of the main threats posed by edge computing is the proliferation of physical data sources. Since Edge involves operating more physical resources in the real world, attackers have more targets to compromise networks. If they gain access to Edge devices, they can extract valuable information, tamper with or destroy node diagrams, or even change the OS and software of the nodes.

According to some experts, fears associated with Edge computing, to some extent, devalue their benefits and may even slow down implementation.

Customer experience

One of the hottest business uses for Edge is in customer service. By reducing latency inherent in this technology, companies can provide optimal service. For example, amusement parks use IoT sensors and edge computing to quickly communicate the performance of their rides. Based on this data, adjustments are made to optimize their performance and prevent possible failures.

Even more tangible is the significant increase in the speed of sales that Edge computing provides. A Deloitte Digital study found that a 100ms increase in mobile retail speed resulted in an 8.4% increase in sales conversions. Reducing latency can also help marketers process customer data in near real time. This allows for more personalized and interactive customer services, advanced chatbots, and even offline interactions.

Internet of Things


The Internet of Things (IoT) is the fastest growing area that includes edge computing devices. These include smart appliances, smartphones, wearable devices, gaming systems, printers, and more.

According to forecasts Statista, by 2025, the prevalence of smart devices will increase four-fold. This is expected to significantly expand edge computing capabilities. In fact, the rise of IoT could lead to great benefits in the Edge sector, such as lower latency. The growth in the number of IoT devices will not only contribute to its development, but will also revolutionize various industries such as healthcare and education. In fact, IoT devices are already being deployed at the edge in healthcare and for remote site monitoring.

Edge computing in healthcare

The healthcare industry is at the forefront of IoT adoption, so it’s expected to lead the way in edge computing as well. Large hospitals are realizing that it is more profitable for them to store medical sensor data, electronic medical records and digital imaging nearby, rather than transfer it to the cloud. An example is a real-time sepsis diagnostic solution. Thanks to Edge, this traditionally lengthy process has been reduced to almost one day.