Academic literature on the topic 'Computer network architecture'

The Internet architecture works well for a wide variety of communication scenarios. However, its flexibility is limited because it was initially designed to provide communication links between a few static nodes in a homogeneous network and did not attempt to solve the challenges of today’s dynamic network environments. Although the Internet has evolved to a global system of interconnected computer networks, which links together billions of heterogeneous compute nodes, its static architecture remained more or less the same. Nowadays the diversity in networked devices, communication requirements, and network conditions vary heavily, which makes it difficult for a static set of protocols to provide the required functionality. Therefore, we propose a self-aware network architecture in which protocol stacks can be built dynamically. Those protocol stacks can be optimized continuously during communication according to the current requirements. For this network architecture we propose an FPGA-based execution environment called EmbedNet that allows for a dynamic mapping of network protocols to either hardware or software. We show that our architecture can reduce the communication overhead significantly by adapting the protocol stack and that the dynamic hardware/software mapping of protocols considerably reduces the CPU load introduced by packet processing.

Cloud-native network design, which leverages network virtualization and softwarization together with the service-oriented architectural principle, is transforming communication networks to a versatile platform for converged network-cloud/edge service provisioning. Intelligent and autonomous management is one of the most challenging issues in cloud-native future networks, and a wide range of machine learning (ML)-based technologies have been proposed for addressing different aspects of the management challenge. It becomes critical that the various management technologies are applied on the foundation of a consistent architectural framework with a holistic vision. This calls for standardization of new management architecture that supports seamless the integration of diverse ML-based technologies in cloud-native future networks. The goal of this paper is to provide a big picture of the recent developments of architectural frameworks for intelligent and autonomous management for future networks. The paper surveys the latest progress in the standardization of network management architectures including works by 3GPP, ETSI, and ITU-Tand analyzes how cloud-native network design may facilitate the architecture development for addressing management challenges. Open issues related to intelligent and autonomous management in cloud-native future networks are also discussed in this paper to identify some possible directions for future research and development.