CFP: International Journal of Research and Reviews in Computer Science - Special Issue on “Nature-Inspired Optimization in Networking”

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Computer networking has become an active research fields in the last few decades and many products have been realized through successful networking research. Due to our demands for higher data rate and more seamless connectivity, new technologies keep being developed and merchandised, including wireless sensor networks, wireless mesh networks, social networks, smart grid communications, etc. Therefore, many new problems have been proposed and most of which can be formulated as optimizationproblems. However, many such optimization problems do not have the corresponding good algorithms developed or they are so hard (usually classified as NP-hard) that no algorithm is available to find the optimal solution in polynomial time.

Although it may be difficult to find the optimal solutions for these problems, we can still approximate the best solutions with reasonably good ones. When we focus on NP-hard problems and computation time is our concern, approximate algorithms are the good choice. Since the evolutionary computational approaches were developed in the past few decades, many works rely on the nature-inspiredalgorithms to do optimization. The relatively classical ones are Genetic Algorithm, Simulated Annealing, Artificial Immune System, Ant Colony Optimization, and Particle Swarm Optimization, etc. Some recently proposed algorithms include Harmony Search, Bee Algorithm, Bacterial Foraging Optimization, Group Search Optimization, Biogeography-based Optimization, Chemical ReactionOptimization, etc.

This special issue is focused on highlighting the nature-inspired techniques to solve optimization for designing computer networks. They should demonstrate advantages or improvements in some aspects over the existing methods. The goal is to developnature-inspired approaches which enhance the adaptability, autonomicity, and scalability of any kinds of computer networks. We also welcome submissions that demonstrate real-world experience in and theoretical works on applying nature-inspired optimizationtechniques to networking research problems.


Topics related to computer networks to be covered in this special issue include but are not limited to:
• P2P audio and video streaming
• Grid and cluster computing
• Cloud systems
• Social networks
• Infrastructure-based and ad hoc cognitive radio systems
• Topology control and management
• Cross-layer design and interactions
• Centralized/distributed radio resource management in wireless mesh networks
• Service-oriented and QoS support for smart grid
• Energy-efficient transmission switching and routing for smart grid communications
• Multicast for smart grid
• Green computing systems

Topics related to nature-inspired techniques to be covered in this special issue include but are not limited to:
• Genetic Algorithms
• Simulated Annealing
• Ant Colony Optimization
• Particle Swarm Optimization
• Artificial Immune Systems
• Harmony Search
• Bees Algorithm
• Biogeography-based Optimization
• Group Search Optimization
• Bacterial Foraging Optimization
• Chemical Reaction Optimization


Guest Editors:
• Dr. Albert Y.S. Lam, The University of Hong Kong, Hong Kong, ayslam@eee.hku.hk
• Dr. Yanhui Geng, The University of Hong Kong, Hong Kong, yhgeng@eee.hku.hk
• Dr. Ka-Cheong Leung, The University of Hong Kong, Hong Kong, kcleung@eee.hku.hk


Important dates:
Manuscript submission deadline: September 1, 2010
Acceptance Notification: November 1, 2010
Final manuscripts: December 15, 2010
Publication: March, 2011


Submission procedure:
Authors should follow IJRRCS research paper manuscript format described at the journal website: http://scholarlyexchange.org/ojs/index.php/IJRRCS/about/submissions#authorGuidelines. Manuscripts should be submitted to the guest editors with the following email addresses: ayslam@eee.hku.hk, yhgeng@eee.hku.hk, and kcleung@eee.hku.hk.



For more information, please visit the journal website: http://scholarlyexchange.org/ojs/index.php/IJRRCS/announcement/view/119