BIG DATA 2018 - INTERNATIONAL WORKSHOP ON BIG DATA WITH COMPUTATIONAL INTELLIGENCE FOR WIRELESS NETWORKING

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