Journal Information
Ad Hoc Networks
http://www.journals.elsevier.com/ad-hoc-networks/
Impact Factor:
3.151
Publisher:
ELSEVIER
ISSN:
1570-8705
Viewed:
10282
Tracked:
24

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Call For Papers
The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to:

    Mobile and Wireless Ad Hoc Networks
    Sensor Networks
    Wireless Local and Personal Area Networks
    Home Networks
    Ad Hoc Networks of Autonomous Intelligent Systems
    Novel Architectures for Ad Hoc and Sensor Networks
    Self-organizing Network Architectures and Protocols
    Transport Layer Protocols
    Routing protocols (unicast, multicast, geocast, etc.)
    Media Access Control Techniques
    Error Control Schemes
    Power-Aware, Low-Power and Energy-Efficient Designs
    Synchronization and Scheduling Issues
    Mobility Management
    Mobility-Tolerant Communication Protocols
    Location Tracking and Location-based Services
    Resource and Information Management
    Security and Fault-Tolerance Issues
    Hardware and Software Platforms, Systems, and Testbeds
    Experimental and Prototype Results
    Quality-of-Service Issues
    Cross-Layer Interactions
    Scalability Issues
    Performance Analysis and Simulation of Protocols
Last updated by Dou Sun in 2018-11-11
Special Issues
Special Issue on Artificial Intelligence for Wireless Networks (AI4WN)
Submission Date: 2019-12-01

The focus of this Special Issue is on Artificial Intelligence (AI) for Wireless Networks. AI applications are quickly finding their way into everyday life - whether it's eal-time traffic data, sensor data from self-driving cars, or Netflix entertainment recommendations. All of these wireless network applications generate extreme volumes of data that must be collected and processed in real time. The advantages of AI are numerous, most notably are learning from examples, experience, scalability, adaptability, and the ability to extract rules without the need for detailed or precise mathematical modeling. In general, the advantages of pursuing this line of research have been proven worthy. The goal of the Special Issue is to publish the most recent results in the development of AI for wireless networks. Researchers and practitioners working in this area are expected to take this opportunity to discuss and express their views on the current trends, challenges, and state of the art solutions addressing various issues in AI for wireless networks. Review papers on this topic are also welcome. Topics to be covered in this Special Issue include the following topics, but are not limited to: Deep Learning and Neural Networks for Wireless Networks Machine Learning for Wireless Networks Computer Vision in Wireless Networks Reinforcement Learning for Wireless Networks Knowledge Driven Wireless Networks Decision Making for Wireless Networks Fuzzy Systems for Wireless Networks Evolutionary Computing for Wireless Networks Human-Inspired Learning and Computing for Wireless Networks Data Mining in Wireless Networks AI for Wireless Sensor Networks AI for Internet of Things
Last updated by Dou Sun in 2019-07-27
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