Journal Information
Computer Networks (CN)
Impact Factor:

Call For Papers
Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.


The topics covered by the journal but not limited to these are:

1. Communication Network Architectures:
New design contributions on Local Area Networks (LANs), Metropolitan Area Networks (MANs), Wide Area Networks (WANs) including Wired, Wireless, Mobile, Cellular, Sensor, Optical, IP, ATM, and other related network technologies, as well as new switching technologies and the integration of various networking paradigms.

2. Communication Network Protocols:
New design contributions on all protocol layers except the Physical Layer, considering all types of networks mentioned above and their performance evaluation; novel protocols, methods and algorithms related to, e.g., medium access control, error control, routing, resource discovery, multicasting, congestion and flow control, scheduling, multimedia quality of service, as well as protocol specification, testing and verification.

3. Network Services and Applications:
Web, Web caching, Web performance, Middleware and operating system support for all types of networking, electronic commerce, quality of service, new adaptive applications, and multimedia services.

4. Network Security and Privacy:
Security protocols, authentication, denial of service, anonymity, smartcards, intrusion detection, key management, viruses and other malicious codes, information flow, data integrity, mobile code and agent security.

5. Network Operation and Management:
Including network pricing, network system software, quality of service, signaling protocols, mobility management, power management and power control algorithms, network planning, network dimensioning, network reliability, network performance measurements, network modeling and analysis, and overall system management.

6. Discrete Algorithms and Discrete Modeling
Algorithmic and discrete aspects in the context of computer networking as well as mobile and wireless computing and communications. Fostering cooperation among practitioners and theoreticians in this field.


The primary purpose of the journal is to publish original and complete papers covering a specific topic or project in the above mentioned areas in sufficient detail and depth to be of practical use to interested readers. The readers should benefit from the novel solutions and analyses presented in the papers. Enhanced, extended versions of quality papers presented at conferences or workshops can be submitted to our journal for review. Note that papers which were already published with the same contents or simultaneous submission of the same paper to other journals or conferences will not be considered for publication in our journal and will be immediately rejected.
Last updated by Dou Sun in 2019-11-24
Special Issues
Special Issue on Smart Spectrum and Radio Resource Management for Future 5G Networks
Submission Date: 2020-02-29

The last few years have witnessed a significant increase in the use of portable computing devices such as smartphones, tablets and laptops for enhanced Mobile Broadband (eMBB) services in addition to the introduction of machine-type devices interconnected through the Internet of Things (IoT) for massive Machine Type Communications (mMTC) as well as novel services that require Ultra-Reliable Low-Latency Communication (URLLC). The emergence of this range of innovative mobile applications and online services pose unprecedented challenges to the fifth generation of mobile networks (5G), which are thus required to introduce new solutions and mechanisms to optimise the use of the finite radio spectrum resources. Some of the key enabling technologies to overcome this challenging scenario include the introduction of a New Radio (NR) interface in millimetre-wave (mmWave) bands, which embraces recent techniques such as massive Multiple-Input Multiple-Output (massive MIMO) and beamforming. While these techniques are foreseen as key solutions to optimize the use of the 5G spectrum and enable the envisaged use-case scenarios, mmWave links are highly vulnerable and unreliable and therefore some advanced solutions are required, possibly including some form of back-up at more reliable sub-6 GHz bands, based on Dynamic Spectrum Access (DSA) methods enabled by the Cognitive Radio (CR) paradigm. Moreover, over the last years, the industrial, academic and regulatory communities have addressed the problem of efficiently exploiting existing and available spectrum radio resources in order to meet the 5G performance requirements and thus facilitate the 5G network concept. In addition to the new requirements of increased network capacity, reliability and latency, future networks are still expected to meet requirements of energy efficiency and heterogeneity of user terminals and Quality of Service/Experience (QoS/QoE) demands. In this context, a key challenge is to develop novel and smart spectrum and radio resource management paradigms for an efficient spectrum exploitation taking into account the abovementioned aspects. The purpose of this special issue is to gather the latest developments and recent advances in the field of smart spectrum and radio resource management for future 5G networks. Prospective authors are invited to submit original manuscripts that advance the state of the art on topics including, but not limited to: Smart radio resource allocation mechanisms for spectrum and energy efficiency in 5G networks Network cooperation techniques for 5G networks Network architectures and protocols for efficient exploitation of spectrum resources in 5G Self-configuring and self-organizing DSA/CR-based devices for 5G Cooperative spectrum sensing algorithms for 5G AI and machine learning for radio resource management in 5G networks Game-theory based resource allocation schemes in 5G networks Interference management and cancelation techniques for 5G Smart cross-layer access node allocation mechanisms in 5G networks Energy management in 5G networks QoS/QoE provisioning methods in 5G networks Software Defined Network and Network Function Virtualization for efficient exploitation of spectrum resources in 5G Modelling and simulation for exploitation of spectrum resources in 5G networks Experimental results and deployment experiences in outdoor community-scale platforms
Last updated by Dou Sun in 2019-11-12
Special Issue on Intelligent Green Communication Networks for IoT
Submission Date: 2020-04-30

Green communication networks, with a focus on energy efficiency, is an emerging technological trend of great significance. These networks can significantly enhance sustainability for Internet of Things (IoT) with regard to power resources and environmental conditions. IoT is an ecosystem of connected physical objects that are accessible through the Internet. IoT involves creation of smart communication environment between smart homes, smart transportation, and smart healthcare systems with the help of several devices in a network that enables transmission of data within these devices such as Wireless Sensor Network (WSN), Radio Frequency Identification (RFID), cloud services, Near Field Communication (NFC), gateways, data storage and analytics, and visualization elements. The exponentially increasing number of nodes in the IoT ecosystem will lead to significant energy consumption. Thus, reducing carbon footprint in green communication networks is a key challenge facing researchers in academia and industry. Due to the growing use of artificial intelligence (AI) in this area, several green communication approaches are entering a more mature phase, with exciting applications in various networks. Moreover, the information sharing and intelligent decision-making capabilities help recent green communication networks play an important role in improving not only energy efficiency but also network performance. For instance, a simple and effective green communication solution is to place a node in intelligent sleep mode; this is achieved with the help of various MAC protocols with broad applications in wireless networks. However, it is essential to investigate the trade-off between the energy efficiency for green communication networks, and the IoT requirements. Moreover, it is crucial to evaluate the performance concerning the energy consumption, the throughput, and the response time, regarding IoT ecosystem. This special issue solicits submissions of high-quality and unpublished articles that aim to address the technical problems and challenges concerning green communications networks. In particular, we seek submissions, which efficiently integrate novel AI approaches, focusing on IoT ecosystem performance evaluation across existing green communication solutions. Both theoretical and experimental studies for such scenarios are encouraged. The topics of interest include, but are not limited to: • Power consumption trends and reduction in intelligent communications for IoT. • Machine learning approaches for energy-aware green wireless communication networks for IoT. • AI based modeling and analysis for green communications for IoT applications. • AI based green wireless sensor networks. • AI based green cognitive radio networks. • Carbon-neutral intelligent communication networks for IoT. • Architectures and models for smart green communication networks for IoT. • Quality of service in smart green communication networks for IoT ecosystem. • Intelligent green communication network designs and implementations for IoT ecosystem. • Experimental test-beds and results for intelligent green communication networks.
Last updated by Dou Sun in 2019-11-24
Special Issue on Recent Advances in AI-based Mobile Multimedia Computing for Data-Smart Processing
Submission Date: 2020-06-20

Mobile multimedia computing is becoming more and more critical in the area of wireless communication. In the face of increasingly complex tasks, the scale of multimedia data has become massive. Obviously, the real time data processing is the major problem for mobile multimedia computing. In recent years, deep learning has made significant breakthroughs in many areas of artificial intelligence, including CNN, RNN, and GAN. However, the traditional model needs uploading and handling data at the cloud end, which cannot meet the requirements of timeliness and mobility. Edge computing is proposed as a new computing paradigm where resources like computation and storage are placed closer to data and information source. On the one hand, edge computing helps cloud to extend its services to the edge of the network, which improves the response time and user experience. On the other hand, the developing of the mobile app leads to the huge amount of data generated on the user side, and there are also a lot of smart devices available, it is a natural way to process data on edge. In a word, edge computing paradigm greatly saves the bandwidth of the backbone network and improves the end-to-end latency. It brings new possibilities for complex applications, intelligent services, novel security, and privacy solutions, especially for the researches, which depend on the huge amount of data. We aim to point out that mobile multimedia computing shall be paid attention to use edge computing. It means that all the mobile devices that can handle multimedia data for smart processing. This special issue focuses on recent advances in architecture, algorithms, Optimization, and models for AI-based Mobile Multimedia Computing for Data-Smart Processing. Original, unpublished contributions and invited articles, reflecting various aspects of mobile computing are encouraged. The topics of interest for the special issue include, but are not limited to: AI-based Mobile multimedia networking framework AI-based Fault tolerance/Formal Verification/Testing under mobile multimedia computing AI-based Algorithms, schemes, and techniques in mobile multimedia computing systems AI-based Parallel computing in mobile multimedia computing systems AI-based Optimization and distributed control of mobile multimedia AI-based Large-scale data analysis for mobile multimedia AI-based Distributed infrastructures, parallelization for mobile multimedia computing AI-based Resource allocation and scheduling AI-based Data management and preprocessing AI-based Security and privacy in mobile multimedia computing systems Surveys of AI-based mobile multimedia computing
Last updated by Dou Sun in 2020-01-11
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