Present day networks vary in size, scale and heterogeneity. The ever-decreasing cost of bandwidth and ever-increasing number of users are opening new vistas for applications of computer networks. Problems in integrating heterogeneous wired and wireless technologies, ensuring security and quality of service and reliably operating large-scale systems including cloud computing have all emerged as an important topics.
The application of computational intelligence (CI), which includes a set of nature-inspired computational methodologies and population-based methods of optimisation to address the various problems, is relevant when considering these problems. Subsequently, computational intelligence techniques applied to optimising the performance of networking systems has received more attention in recently published volumes and related reports. Based on this context, there is a need for envisioning a key perspective for the current state of practice of computational intelligence techniques to address research issues and challenges in network modelling and quality of services.
This special issue will explore novel theoretical developments and bridge the gap between applications of CI and communication networks. It aims to explore the advantages of CI-based solution (e.g. fuzzy systems, neural networks, evolutionary computation, swarm intelligence, cognitive maps, rough sets, granular computing and other emerging learning or optimisation techniques) and how they may be used to handle the challenges associated with modelling and performance issues of communication networks. The increasing demand for CI applications in different fields entails a serious challenge for improving network performance in order to predict and estimate using imprecise and uncertain information. Hence there is a significant need for sharing research and recent developments in computer networks and CI in conjunction with CI paradigms.
Suitable topics include, but are not limited to:
- Computational intelligence methods in network optimisation
- Heuristic algorithms for near-optimal solutions
- Network architecture and design
- Decomposition and relaxation techniques for large-scale optimisation
- Hybrid optimisation approaches
- Network resilience and cross-layer design
- Optimal scheduling and improving routing performance
- Optimal hand-off decisions and quality of service
- Networking for big data traffic
- Empirical measurements and experimental studies
- Network survivability, resource allocation
- Content and location-aware networking
- Networking aspects of distributed analysis of massive data
- Efficient data delivery in Internet of Things and machine-to-machine systems
Important Dates
Submission deadline: 31 January, 2016
Review notification: 20 March, 2016
Submission of revised papers: 20 April, 2016
Notification of final review results: 1 June, 2016
Review notification: 20 March, 2016
Submission of revised papers: 20 April, 2016
Notification of final review results: 1 June, 2016
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