Skills to Thrive in the Edge Computing Industry: What are they?
Operations technology (OT) and information technology (IT) are crashing into one another. The industrial sector is investing heavily in both large- and small-scale operations to increase data availability, proliferation, and usability for expediting operations and resolving challenging field problems.
The transition to edge-oriented automation system design models—also referred to as edge computing, utilizing centralized or hierarchical models is a major trend driving this change.
What is Edge Computing in Distributed Systems?
Edge computing is part of the broader concept of distributed computing. It decentralizes computing resources rather than centralizing them in a master controller or application.
Origin and Internet Influence:
Edge computing’s origins trace back to the early 2000s, influenced by the limitations of centralized networks on the internet. Resources were moved geographically closer to reduce latency and improve responsiveness and to server areas with high demand. The proliferation of smart devices and the IoT contributed to the availability of local computing resources.
Industrial Edge Computing:
Industrial sectors are adopting edge computing as part of the Industrial Internet of Things (IIoT). Edge systems are highly distributed, bringing data processing, storage, and connectivity closer to real-world sensing and control points.
Scope of the Edge:
Depending on context, the “edge” could refer to anything in the last mile of the network. It is distinct from resources located in the network core or cloud.
- Edge Devices and Gateways:
Edge devices include intelligent field devices like transmitters, PLCs, and PACs. Edge gateways, such as protocol converters and industrial PCs, connect different network parts.
- Data Normalization:
Edge devices play a crucial role in data normalization. Data normalization involves reformatting, adding metadata, removing outliers, and filling gaps to ensure consistency. It is especially important as data is produced in various formats and protocols.
- Enhancing Functionality:
Industrial edge computing goes beyond resource utilization. More powerful edge devices can host local servers for visualization, databases, and applications. It reduces dependence on high-maintenance PCs and enhances IT integration.
Gaining Proficiency in Edge Computing Competencies:
Edge computing integrates services and technologies that were previously divided by design. OT practitioners may need to learn new skills in order to benefit from this shift. Networking, database management, security, and system design are a few of the essential edge computing skills. Here are some additional details regarding the prerequisites for developing these skills.
- System design: An individual with a broad perspective is necessary for an edge-oriented system. The efficacy of a system can be enhanced or diminished by the quality of its interactions with edge devices, computer networks, and software systems, each of which has distinct resource limitations. Interoperability becomes increasingly important when data is travelling between different domains.
It’s useful to know how to handle and arrange data effectively while working with several devices in tandem, as well as standard data interchange formats like JSON. Scalability and other system-wide characteristics are determined by these parameters and will become increasingly crucial over the next ten years as IIoT integration progresses.
- Networking: By employing network resources more effectively, edge computing enhances the performance of IT/OT systems. Therefore, engineers who are proficient in monitoring and controlling computer network performance will find it easier to deal with edge computing systems.
Several edge devices sending out massive amounts of data might cause a network to become unresponsive. Proper design can minimize utilization in the core while increasing field response.
Further lowering bandwidth use may be achieved by putting into practice effective communication protocols like message queuing telemetry transport (MQTT). Network architecture, device selection, and communication protocol selection may also be influenced by other considerations such as fault tolerance and scalability.
- Database proficiency: In IT and OT systems, databases are essential for data dissemination, storage, and analysis. Because edge computing increases their number and connectivity, OT professionals must have some understanding of their design and interaction. The frequency, kind of transactions, and the quality of incoming data can hurt database security and efficiency.
An open-source IoT connection tool is one piece of specialized software that facilitates data sharing between edge devices, databases, and cloud services. For industrial applications, database connectivity is made simpler by another piece of software.
- Security: Since data may be handled, accessed, and kept at several locations within a control network, physical security and cybersecurity cannot be taken for granted. When dealing with this type of network, engineers will need to familiarize themselves with the tools and possible hazards that need to be taken into account.
Engineers must be knowledgeable about data protection features, including authentication, encryption, and certification as well as the operation and configuration of network security devices like firewalls. It should also be within their power to evaluate the security profile of newly added hardware and software before it is connected to the network.
Conclusion:
Edge computing designs merge previously separate technologies and services, necessitating OT professionals to acquire new skills in security, networking, database administration, and system design.