-------- Weitergeleitete Nachricht -------- Betreff: [TCCC-ANNOUNCE] [CFP]- ETT-Data Driven Intelligence in Wireless Networks: Issues, Challenges, and Solution Datum: Thu, 22 Feb 2018 03:35:05 -0500 Von: Muhammad Khalil Afzal muhammad.khalil.afzal@GMAIL.COM Antwort an: Muhammad Khalil Afzal muhammad.khalil.afzal@GMAIL.COM An: tccc-announce@COMSOC.ORG
Call for Paper Transactions on Emerging Telecommunications Technologies (ETT) Data Driven Intelligence in Wireless Networks: Issues, Challenges, and Solution
Aim and Scope: An evolving concept called data driven intelligence is a model for a new viewpoint on gathering vision from a vast pool of data. There are more than 370 Million Internet users worldwide. Number of unique mobile users is almost 5 Billion, with total number of mobile connections exceeding 8 Billion. This indicates that wireless communication is a prevalent field. Different wireless technologies including mobile cellular, fixed line, wireless fidelity (Wi-Fi) and others are widely used for diverse communication purposes. It is estimated that majority of user’s access Internet via a mobile device. Internet traffic is dominated by multimedia content, and its proportion is ever increasing. This increases quality of service/experience (QoS/QoE) requirements. Optimizing multiple, often conflicting goals (delay, throughput, energy etc.) is of fundamental importance in the context. With the spreading of Internet and broadening of its capacity, data is available in abundance. Many fields benefit from data to optimize decisions. A lot of datasets, related to performance and security of different wireless networks are publicly available. Depending on the type of network and application, potential research areas include but not limited to: routing, MAC layer optimizations, mobility optimization, spectrum sensing, signal classification, handover decision, power allocation and rate adaptation, performance prediction, data collection and aggregation, event detection, localization and object tracking, intrusion detection and other security issues. Potential techniques to solve such problems include but not limited to: machine learning (supervised, unsupervised and reinforcement), swarm intelligence, genetic algorithms, artificial immune system, markov decision process, and game theory. Therefore, this special issue is to focus the data driven techniques to solve wireless communication problems (e.g. related to performance, security, and applications etc.). We invite researchers from academia and industry to discuss challenging ideas and novel research contributions, demonstrate results on data driven intelligence in wireless networks and related areas. Topics of Interest: Topics of interest include, but not limited to the following: • Physical layer issues and data driven intelligence • Link layer issues and data driven intelligence • Network layer issues and data driven intelligence • Cross layer data driven optimizations • Wireless sensor networks and data driven intelligence • Cognitive radio networks and data driven intelligence • Vehicular networks and data driven intelligence • Edge/Fog Computing and data driven intelligence • Supervises and unsupervised machine learning techniques for wireless networks • Reinforcement learning techniques and wireless networks • Data driven algorithms for wireless networks
Important Dates
• Manuscript Submission Deadline: April 30, 2018 • Decision Notification: July 15, 2018 • Final Manuscript Submission: Sep 30, 2018 • Publication Date: Nov 2018
Guest Editors of the Special Issue
Muhammad Khalil Afzal, Lead Guest Editor COMSATS Institute of Information Technology, Wah, Pakistan Email: khalilafzal@ciitwah.edu.pk Biography: https://sites.google.com/site/muhammadkhalilafzal/
Mubashir Husain Rehmani Waterford Institute of Technology, Ireland Email: mshrehmani@gmail.com Biography: https://sites.google.com/site/mshrehmani/
Yousaf Bin Zikria Yeungnam University, South Korea. Email: yousafbinzikria@gmail.com Biography: https://sites.google.com/view/ybzikria/
Qiang Ni School of Computing and Communications at Lancaster University, UK Email: q.ni@lancaster.ac.uk Biography: http://www.lancaster.ac.uk/scc/about-us/people/qiang-ni
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