Aim and scope
Nowadays, we are facing an explosive data growth from wireless networks. These data can be highly dimensional, heterogeneous, complex, unstructured and unpredictable. On the other hand, the design and the operation of a wireless network can benefit from data collected from widely deployed sensors, network devices, user behaviours, and other sources. The challenges in analysing “wireless big data” call for fundamental techniques and technologies. At the same time, the big data analysis has created new opportunities for both industries and academia.
Computational intelligence (CI) enables agents (or decision makers), for example, the computers and the smart devices, to computationally process and analyse the captured data and subsequently identify and explain the underlying patterns, as well as to efficiently learn the specific tasks. CI covers a broad range of nature-inspired, multidisciplinary and computational methodologies, such as fuzzy logic, artificial neural networks, evolutionary computing, learning theory, probabilistic methods, and so on. CI technologies are expected to provide efficient and powerful tools that scale well with data volume for wireless big data analytics and process, while addressing the challenges brought by the massive amount of data.
This workshop will focus on the technical challenges and applications of CI in big data for wireless networking. We envision that the combination of wireless big data with a large collection of CI algorithms will reach the level of true artificial intelligence in wireless networks.
Topics of Interest
The areas of interests include, but are not limited to, the following:
- Data-driven wireless networking with CI
- Big data and CI for wireless networking
- Big data and CI for mobile edge computing
- Fuzzy logic for wireless big data analysis
- Artificial neural networks for wireless big data analysis
- Evolutionary computing for wireless big data analysis
- Learning theory for wireless big data analysis
- Probabilistic methods for wireless big data analysis
- Machine learning for wireless big data analysis
- Fuzzy-based models for wireless big data
- Evolutionary models for wireless big data
Honggang Zhang, Zhejiang University, China, Email: firstname.lastname@example.org
Celimuge Wu, The University of Electro-Communications, Japan, Email: email@example.com
Xianfu Chen, VTT Technical Research Centre of Finland, Finland, Email: firstname.lastname@example.org
Carlos Tavares Calafate, Technical University of Valencia, Spain. Email: email@example.com
November 2, 2017 extended November 12, 2017
Acceptance notification: December 15, 2017
Camera-ready version: January 12, 2018
The workshop follows the formatting guidelines of IEEE WCNC 2018. Submissions should be original and limited to 6 double-column pages in IEEE paper templates. All submissions should be written in English using 10-point font. Authors are invited to submit their manuscripts in PDF format through EDAS conference system (https://edas.info/newPaper.php?c=24102&track=87486).