The role of Edge computing in computer networks

DOI: 10.31673/2412-9070.2025.011762

Abstract

In modern computer networks, edge computing is becoming increasingly relevant, particularly due to its impact on the efficiency of data processing amidst the growing volume of data, the operation of network systems, real-time requirements, and the high demands for speed and security in information transmission.
The main challenges faced by traditional centralized computing systems include data processing delays, network congestion, rising costs for maintaining data centers, and risks to data confidentiality. The article highlights that edge computing can address these issues by processing data directly at the network edge, closer to the source of data generation. This approach reduces delays, optimizes network bandwidth usage, and enhances security by keeping data local.
With the rapid development of 5G and artificial intelligence (AI) technology, more and more intelligent devices are connected to the Internet, and the demand for computing services is also increasing. The traditional combination of cloud computing and the Internet of Things (IoT) has gradually revealed some drawbacks, such as transmission delay, greatly reduced transmission rate and network bandwidth pressure. Edge computing is a new computing paradigm. It puts the service near the physical edge of the end users. Due to its close proximity, dense distribution and low latency, edge computing can effectively reduce latency, improve transmission speed and relieve bandwidth pressure.
At present, there are more and more researches on edge computing. It is necessary to discuss edge computing in general. The system mapping study uses the visualization method to summarize a specific field. This paper aims to introduce the development of edge computation in detail by means of a systematic mapping study.
This paper examines the concept, characteristics, and key aspects of edge computing, its role in computer networks, and its practical applications. Modern hardware solutions for implementing edge computing are explored. A comparison of edge, fog, and cloud computing is presented, highlighting their advantages, disadvantages, and areas of application. Practical examples of edge computing usage in industries such as healthcare, autonomous transport, energy, and gaming are provided.
Recommendations are offered for selecting hardware and implementing edge computing based on the specific needs of users and organizations.

Keywords: computer network, edge computing, data center, cloud computing, Internet of Things,
IoT, enterprise networks, computer network management.