The stack in various forms has been widely used as an architectural template for networking systems. Recently the stack has been subject to criticism for a lack of flexibility. However, when it comes right down to it nobody has offered a truly compelling alternative. Various cross-layer optimizations have been proposed, but these optimizations are frequently hacks to achieve a particular goal and offer no direct insight into why the existing network stack is inadequate. We propose that a fundamental problem with the existing network stack is that it attempts to layer functionality that is not well-suited to layering. In this work we use a "bottom up" model of information computation, storage, and transfer and the "top down" goals of networking systems to formulate a modular decomposition of networking systems. Based on this modular decomposition we propose a semantic layered structure for networking systems that eliminates many awkward cross-layer interactions that arise in the canonical layered stack.
Goal-Oriented Multi-Agent Semantic Networking: Unifying Intents, Semantics, and Intelligence
Department of Engineering, King’s College London（伦敦国王学院工程系）；Network Automation Department, NSSR Lab, Nokia Bell Labs（诺基亚贝尔实验室网络自动化部门）；Bristol Research and Innovation Laboratory, Toshiba Europe Ltd.（东芝欧洲有限公司布里斯托尔研究与创新实验室）
Imitation Learning-based Implicit Semantic-aware Communication Networks: Multi-layer Representation and Collaborative Reasoning
Huazhong University of Science and Technology（华中科技大学）；Peng Cheng Laboratory（鹏城实验室）；Pazhou Laboratory (Huangpu)（琶洲实验室（黄埔））；Xidian University（西安电子科技大学）；Nanyang Technological University（南洋理工大学）
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks
Virginia Tech（弗吉尼亚理工大学）；Technology Innovation Institute（技术创新研究院）；CentraleSupelec（巴黎中央理工-高等电力学院）；University Paris-Saclay（巴黎萨克雷大学）；University of Houston（休斯顿大学）；Kyung Hee University（庆熙大学）；Princeton University（普林斯顿大学）
