Journal Information
Computer Networks (CN)
http://www.journals.elsevier.com/computer-networks/
Impact Factor:
3.030
Publisher:
Elsevier
ISSN:
1389-1286
Viewed:
12794
Tracked:
46

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.

SUBJECT COVERAGE

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.

TYPES OF CONTRIBUTIONS CONSIDERED

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 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
Special Issue on Artificial Intelligence Techniques for Autonomous Moving Platforms (AMP) in 5G and Beyond
Submission Date: 2020-10-15

Autonomous Moving Platforms (AMP) have gained a lot of popularity in the recent times due to their usage in wide range of applications in modern smart cities including healthcare, transportation, disaster management, crowd sensing, surveillance, object localization and identification, service delivery to name a few. AMP include unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), autonomoussurface vehicles (ASVs) as well as autonomous land vehicles (ALVs). It has been observed from the literature that AMPs applications are not limited to aerial traffic management but these are being used in water, and on earth surface in various applications as mentioned above. For providing QoS and QoE for all these applications, an efficient communication infrastructure support is required so that information can be transferred on time. With an advent of 5G communications, AMPs are expected to extend their usage in a wide range of applications in domestic as well as commercial fields in years to come. For example, in a report released by US Federation Aviation Administration, the number of AMPs is expected to increase to 2.4 million by 2022 which can be used in many emerging applications. Also, the commercial AMPs market is anticipated to reach 17 billion by the year 2024. These insights have fuelled the use of AMPs in various domains. However, for smooth delivery of services to the end users, a strong backbone architecture support is required which can influence the delivered QoS and QoE. So, to augment the potential usage of AMPs, it is important to integrate 5G backbone infrastructure in AMP using 5G based heterogeneous networks which provides minimum latency. 5G wireless network is an emerging technology which includes high data rates, low latency in transmission results in an increase in the reliability of service. There is a considerable difference in QoS provisions from the currently available 4G networks due to the limited capacity of base stations. There are two ways in which the AMP can be integrated into 5G networks. First, by making it a user itself using the cellular network for mission exclusive applications. Second, by making them aerial base stations for the cellular operator. AMP communication is categorized into three domains viz AMP - to- AMP, AMP - to- ground stations and AMP - to- satellite stations. However, eertain problems such as collision among the aerial devices, resource allocation/management, managing the huge amount of data in real-time, transmission delay due to atmospheric hindrance and susceptibility to security breaches need to be handled efficiently. We envision that artificial intelligence techniques can play an important role in providing possible solutions to the problems mentioned above. As compared to existing algorithms artificial intelligence are capable of processing enormous amounts of heterogeneous raw data using automatic hierarchical feature extraction mechanisms. Thus, they can achieve refined information and reduce pre-processing efforts. If used in wireless communication, especially in the 5G environment, artificial intelligence can overcome the limitations of existing traditional problem-solving approaches. This proposed special invited proposals from researchers, academicians, industry professionals, and scholars in the related areas to share their valuable insights and state-of-the-art results on usage of artificial intelligence and 5G enabled for AMP communications. Prospective authors are invited to submit articles on topics including, but not limited to: Artificial Intelligence Techniques for signal processing in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for traffic monitoring in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for Spatio-temporal data mining in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for Data collection, analysis, processing and delivery in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for Distributed caching and security in 5G-enabled in Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for Energy-efficiency in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for UAV path planning in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for resource allocation in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for object detection and localization in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for security and privacy preservation in 5G-enabled Autonomous Moving Platforms (AMP) Artificial Intelligence Techniques for network management in 5G-enabled Autonomous Moving Platforms (AMP)
Last updated by Dou Sun in 2020-05-25
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