Información de la conferencia
LANMAN 2024: International Symposium on Local and Metropolitan Area Networks
https://lanman2024.ieee-lanman.org/
Día de Entrega:
2024-04-14
Fecha de Notificación:
2024-05-16
Fecha de Conferencia:
2024-07-10
Ubicación:
Boston, Massachusetts, USA
Años:
30
CORE: c   QUALIS: b2   Vistas: 17089   Seguidores: 7   Asistentes: 6

Solicitud de Artículos
IEEE LANMAN has an established tradition as a forum for presenting and discussing the latest technical advances in local and metropolitan area networking. Cutting-edge papers spanning both theory and experimentation are solicited in all areas of networking. In keeping with the heritage of the symposium, there will be a central theme, and in 2024 the theme is “Emerging Technologies for Future Networks.”

The Internet is lately experiencing an unprecedented growth in size and use. Now, more than ever there is a need for building networks that allow for low-latency and high throughput communications, in order to support emerging applications such as Virtual Reality, Artificial Intelligence, and autonomous driving, to name a few. This trend poses new challenges in the operations of networks. Here, recent advances in emerging wireless technologies, encompassing high and very high frequencies, combined with new technologies such as Reconfigurable Intelligent surfaces, Massive-MIMO, and Cell-free systems, provide new opportunities for designing innovative solutions that allow new applications with ever-increasing constraints in terms of end-to-end response time and available bandwidth to run smoothly.

The intimate single-track format of the symposium encourages stimulating exchanges between researchers. The event is expected to be a forum for discussion of new and interdisciplinary ideas on network access protocols, network management and control, services and applications. 

Papers are solicited on any topic in networking, including, but not limited to:

    AI and machine learning for local and metropolitan area networking
    AI and machine learning for network measurement and traffic analysis
    Self-learning network architectures
    Networking designs for AI and machine learning
    Networking for online education and entertainment
    Networking protocols and architectures for the IoTs
    Machine-to-machine communication
    Cloud, edge and fog computing integration
    Co-existence and heterogeneity support at the edge (HetNets)
    Energy efficiency for local and metropolitan area networking
    5G and 6G cellular data networking
    Information security for local and metropolitan area networking
    Intelligent routing, forwarding, and scheduling
    Network and transport mechanisms for latency reduction
    Network virtualization in local and metropolitan areas
    Performance and reliability of local and metropolitan area networks
    Software-defined networking in local and metropolitan areas
    Information-centric networking in local and metropolitan areas

IEEE LANMAN 2024 solicits paper submissions of papers up to 6 pages. Some regular paper submissions may be accepted as short papers (2 pages) by the TPC. The page limits include all figures, tables, and references. All papers must be electronically submitted in PDF according to the guidelines in the symposium website http://www.ieee-lanman.org. The proceedings will be published in IEEE Xplore and will include both short and regular papers presented at the symposium. A best paper award will be awarded.

In addition to the regular paper track, we will organize a demonstration session. The aim is to foster interactive discussions on work-in-progress, new problem statements, and ideas for future development related to LANMAN topics, and display innovative prototypes. Authors of accepted papers will be encouraged to submit demo proposals as a further chance to showcase their papers.
Última Actualización Por Dou Sun en 2024-03-31
Coeficiente de Aceptación
AñoEnviadosAceptadosAceptados(%)
2015471838.3%
2014371643.2%
2013321443.8%
2011392153.8%
2010382360.5%
2008361541.7%
2007603050%
20051103632.7%
20041094743.1%
1999635384.1%
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