The 17th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt 2019) will take place from June 03 to 07 , 2019 in Avignon, France.
The 17th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks solicits high-quality contributions. It welcomes different perspectives, including performance analysis, protocol design, wireless communication, and optimization theory. Contributions to this symposium should improve the state-of-the-art in design, analysis, dimensioning and operations of wireless network by providing insights into theoretical aspects as well as providing practical methods and tools. All forms of wireless networks are of interest: from cellular wide-area and local-area networks to dense and sparse Ad Hoc networks; domain specific vehicular, public-transport and personal-area networks as well as application-specific sensor networks.
WiOpt 2019 will be technically co-sponsored by Institute of Electrical and Electronics Engineers (IEEE) and International Federation for Information Processing (IFIP). The copyright of published papers belongs to IFIP. The published papers will appear in both IEEE Xplore, the Digital Library of IFIP.
We are pleased to list here the technical awards for outstanding contributions to WiOpt 2019:
Hereafter you can also find the other Runner Ups:
- Best Student Paper Award: Elastic Multi-resource Network Slicing: Can Protection Lead to Improved Performance?
Jiaxiao Zheng and Gustavo de Veciana (The University of Texas at Austin, USA)
- Best Paper Award: Sampling for Remote Estimation through Queues: Age of Information and Beyond.
Tasmeen Zaman Ornee and Yin Sun (Auburn University, USA)
- Optimization and Learning Algorithms for Stochastic and Adversarial Power Control.
Harsh Gupta, Niao He and R. Srikant (University of Illinois at Urbana-Champaign, USA)
- On the Credibility of Information Flows in Real-time Wireless Networks.
Daojing Guo and I-Hong Hou (Texas A&M University, USA)
- Multi-agent Deep Reinforcement Learning based Power Control for Large Energy Harvesting Networks.
Mohit K. Sharma and Alessio Zappone (CentraleSupelec, France); Mérouane Debbah (Huawei, France)
and Mohamad Assaad (CentraleSupelec, France).