该杂志涵盖的主题包括：网络协议和架构；协议设计和验证；通讯软件；网络控制、信令和管理；网络实施（LAN、MAN、W​​AN）；和微主机通信。

The IEEE Network journal covers topics including network protocols and architectures, protocol design and verification, communication software, network control, signaling and management, network implementation (LAN, MAN, WAN), and micro-host communication.

《IEEE Network》杂志涵盖的主题包括网络协议和架构、协议设计与验证、通讯软件、网络控制、信令与管理、网络实施（包括局域网、城域网和广域网）以及微主机通信等领域。

IEEE Network

Future communication networks will require increased flexibility, scalability, and data computation capabilities to adequately respond to the growing number of service demands. Advanced mixed-integer network resource optimization models and algorithms are required to meet these requirements. The purpose of this article is to introduce a hybrid quantum-classical computing framework for addressing future network resource optimization issues. We begin by discussing the fundamentals of quantum computing and its parallelism. Following that, we discuss in detail the hybrid quantum-classical computing paradigm. Then, we discuss the potential applications of the proposed paradigm for network resource optimization, including network function virtualization (NFV), multi-access edge computing/fog/cloud computing, and cloud radio access networks (C-RANs). Finally, we discuss the difficulties associated with the design and implementation of hybrid quantum-classical algorithms.

Lei Fan

Zhu Han

Hybrid Quantum-Classical Computing for Future Network Optimization

With the fast growing demand for underwater applications such as marine environmental monitoring, undersea resource exploration, disaster prevention and monitoring, assisted localization and navigation, and security monitoring, the IoUT is proposed to enable a new network framework to connect underwater smart things in rivers and oceans. Conventional UWSNs are perceived as the fundamental infrastructure of IoUT. However, the high cost of underwater devices, high energy consumption of data aggregation, and low localization accuracy limit their further development. AUV brings the mobility property into network designs, which improves localization accuracy, data transmission rate, and data aggregation efficiency. However, it also brings new challenges for localization, path planning and coordination of AUVs. In this article, we briefly introduce the architecture of AUV-aided UWSNs and summarize their advantages based on the current research. Several significant issues when designing localization algorithms and coordination schemes for AUV-aided UWSNs are investigated in detail. We also analyze the main challenges under different scenarios such as the interaction between AUV and sensor nodes and communications among multiple AUVs. Based on these discussions, we conclude the article with the future research directions of AUV-aided UWSNs.

Ruoyu Su

Dengyin Zhang

Cheng Li

Zijun Gong

R. Venkatesan

Fan Jiang

Localization and Data Collection in AUV-Aided Underwater Sensor Networks: Challenges and Opportunities

Chang Liu

Xiaohui Xie

Xinggong Zhang

Yong Cui

Large Language Models for Networking: Workflow, Advances and Challenges

用于网络的大语言模型：工作流程、进展与挑战

The rapid evolution of network technologies and the growing complexity of network tasks necessitate a paradigm shift in how networks are designed, configured, and managed. With a wealth of knowledge and expertise, large language models (LLMs) are one of the most promising candidates. This paper aims to pave the way for constructing domain-adapted LLMs for networking. Firstly, we present potential LLM applications for vertical network fields and showcase the mapping from natural language to network language. Then, several enabling technologies are investigated, including parameter-efficient finetuning and prompt engineering. The insight is that language understanding and tool usage are both required for network LLMs. Driven by the idea of embodied intelligence, we propose the ChatNet, a domain-adapted network LLM framework with access to various external network tools. ChatNet can reduce the time required for burdensome network planning tasks significantly, leading to a substantial improvement in efficiency. Finally, key challenges and future research directions are highlighted.

Huang Yudong

Du Hongyang

Zhang Xinyuan

Niyato Dusit

Kang Jiawen

Xiong Zehui

Wang Shuo

Huang Tao

Large Language Models for Networking: Applications, Enabling Techniques, and Challenges

用于网络的大语言模型：应用、支撑技术与挑战

The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are spurring worldwide activities focused on defining the next-generation 6G wireless system that can truly integrate far-reaching applications ranging from autonomous systems to extended reality. Despite recent 6G initiatives (one example is the 6Genesis project in Finland), the fundamental architectural and performance components of 6G remain largely undefined. In this article, we present a holistic, forward-looking vision that defines the tenets of a 6G system. We opine that 6G will not be a mere exploration of more spectrum at high-frequency bands, but it will rather be a convergence of upcoming technological trends driven by exciting, underlying services. In this regard, we first identify the primary drivers of 6G systems, in terms of applications and accompanying technological trends. Then, we propose a new set of service classes and expose their target 6G performance requirements. We then identify the enabling technologies for the introduced 6G services and outline a comprehensive research agenda that leverages those technologies. We conclude by providing concrete recommendations for the roadmap toward 6G. Ultimately, the intent of this article is to serve as a basis for stimulating more out-of-the-box research around 6G.

Walid Saad

Mehdi Bennis

Mingzhe Chen

A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

短名	IEEE Netw.
Journal Impact	7.00
国际分区	TELECOMMUNICATIONS(Q1)
期刊索引	SCI Q1中科院 2 区

ISSN	0890-8044, 1558-156X
h-index	151
国内分区	计算机科学(2区)计算机科学计算机硬件(1区)计算机科学计算机信息系统(2区)计算机科学工程电子与电气(2区)计算机科学电信学(2区)

涉及主题	计算机科学计算机网络工程类电信操作系统计算机安全万维网政治学法学经济生物物理分布式计算
出版信息	出版商: Institute of Electrical and Electronics Engineers Inc.，出版周期: Bimonthly，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 1986，原创研究文献占比: 100.00%，自引率:2.90%， Gold OA占比: 0.00%
平均审稿周期	网友分享经验：>12周，或约稿
平均录用比例	网友分享经验：较易

IEEE Network

期刊引文格式

有 1 位以上作者的期刊

有 2 位作者的期刊

有 3 位作者的期刊

有 5 位以上作者的期刊

书籍引用格式

学位论文引用格式

网页引用格式

专利引用格式

手工熬夜修改参考文献？研飞自动匹配期刊，一键轻松成稿，支持 Word/WPS

投稿经验分享

Hybrid Quantum-Classical Computing for Future Network Optimization

Localization and Data Collection in AUV-Aided Underwater Sensor Networks: Challenges and Opportunities

Large Language Models for Networking: Workflow, Advances and Challenges

Large Language Models for Networking: Applications, Enabling Techniques, and Challenges

A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

Editor’s Note

Tactile Internet for a Cyber-Physical Continuum

Goal-Oriented Semantic Communication and Networking

Scanning The Literature/Edited by Xiaohua Tian

Scanning the Literature/Edited by Xiaohua Tian