Call for Posters / Demos
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 2023 the theme is “Programmable Network Edge.”
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 edge computing (e.g., the ability to run services closer to the users) and programmable network devices (e.g., P4, Network Function Virtualization) 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.
This year, LANMAN will feature a poster and demo session to offer authors the opportunity to present their initial findings from recently performed and unreported research, as well as to demonstrate their novel technologies and applications by means of original interactive showcases. The goal of this session is to focus on work-in-progress, upcoming research challenges, and new directions in the field of interdisciplinary ideas on network access protocols, network management and control, services and applications. Preliminary studies reporting measurements from real-life networks and testbeds are particularly encouraged.
The topics of the poster and demo session coincide with the LANMAN 2023 main track. They include but are 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
Important Dates:
Poster/Demo Paper Submission: May 30, 2023 (23:59 EDT)
Poster/Demo Acceptance Notification: June 7, 2023 (23:59 EDT)
Poster/Demo Camera-Ready Submission: June 14, 2023 (23:59 EDT)
Submission Instructions:
Authors are invited to submit extended abstracts no longer than 2 single-spaced, double-column pages with font-size of 10-point. Extended abstracts must be submitted electronically as PDF files, via EDAS. The standard IEEE template for Microsoft Word or LaTeX formats can be found at IEEE manuscript templates page. Specifically, the extended abstract should briefly state the addressed problem and its relation to the IEEE LANMAN 2023 research topics, the approach taken to solve the problem, and a summary of findings or features to be presented during the LANMAN 2023 poster and demo session. For demo submissions, it is also strongly recommended to provide the URL to download the demo software or a video of the demo, if any. In case of acceptance of the demo papers, the authors should produce a poster supporting the demo.
Accepted and presented abstracts of the poster and demo submissions will be published in the conference proceedings.