The current interest in both Artificial Intelligence (AI) and Machine Learning (ML) techniques in the context of network management has come about due to the requirement to address the complex management of software defined infrastructures, including slices, SDN, NFV, and SFC features, which are beyond the reasonable input, scope and ability for direct human interaction. Progress in both the performance of CPUs as well and the performance and accuracy of machine learning methods such as neural networks, has made Artificial Intelligence and Machine Learning realistic approaches for use in network management.
The AIMLEM workshop addresses both the advances and challenges related to Artificial Intelligence and Machine Learning techniques for enhanced network management of network elements and services in current and future highly dynamic and highly scalable 5G environments.
AIMLEM aims at providing an international forum for researchers and practitioners from academia, industry, network operators, and service providers to discuss and address the challenges deriving from such emerging scenarios where AI and ML systems, processes, and workflows used in both service and network domains. The workshop welcomes contributions from both computing and network-oriented research communities, with the aim of facilitating discussion, cross-fertilization and exchange of ideas and practices, and successfully promote innovative solutions toward a real use of AI and ML. Contributions that discuss lessons learnt and best practices, describe practical AI and ML deployment and implementation experiences, and demonstrate innovative AI and ML use-cases are especially encouraged for presentation and publication.
Submitted papers must be original work, not under review at other journals/conferences, and may comprise a maximum of 6 A4 (210 mm x 297 mm) pages in 2-column IEEE conference style with a minimum font size of 10 pt. Papers should be submitted electronically using the EDAS online submission system. All accepted papers must be presented by one of the authors.
Papers accepted for AIMLEM 2019 will be included in the conference proceedings and IEEE Xplore. The IEEE reserves the right to remove any paper from IEEE Xplore if the paper is not presented at the workshop.
The AIMLEM workshop is technically sponsored by the EU NECOS project (http://www.h2020-necos.eu)