Guest Editors
Prof. Dr. Hsin-Hung Cho
Email: hhcho@niu.edu.tw
Affiliation: Department of Computer Science and Information Engineering, National Ilan University, Ilan, Taiwan
Homepage:
Research Interests: wireless sensor network, mobile networks, cloud computing, artificial intelligence, metaheuristics
Prof. Dr. Gwanggil Jeon
Email: gjeon@incheon.ac.kr
Affiliation: Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea
Homepage:
Research Interests: artificial intelligence, networking, internet of things
Summary
The special issue, Heuristic Algorithms for Optimizing Network Technologies: Innovations and Applications, delves into state-of-the-art heuristic techniques and their impact on optimizing diverse aspects of modern network systems. This issue covers a wide array of topics, including heuristic-based routing optimization, resource scheduling in cloud and edge computing, and security enhancements in software-defined networking (SDN). It highlights advancements in swarm intelligence, particle swarm optimization, and hybrid algorithms for load balancing, particularly in large-scale and dynamic environments such as 5G, IoT, and distributed systems. Contributions also explore energy-efficient routing, multi-objective optimization, and the deployment of Intelligent Reflecting Surfaces (IRS). The focus is on practical solutions that reduce latency, enhance security, and improve spectrum allocation, offering valuable insights for both academic research and industrial applications in telecommunications and IT. Researchers and practitioners are invited to submit innovative heuristic approaches that address key challenges in network optimization and design.
· Potential submission topics for the special issue could include, but are not limited to:
· Heuristic optimization for networks
· Particle swarm optimization for networks
· Swarm intelligence for networks
· Resource scheduling in cloud/edge computing
· Heuristic approaches to minimizing latency in networks
· Metaheuristic optimization for network design
· Energy-efficient routing using swarm intelligence
· Hybrid algorithms for load balancing in distributed systems
· Heuristics for enhancing security in software-defined networking (SDN)
· Multi-objective heuristic algorithms for network optimization
· Network traffic prediction using machine learning and heuristic techniques
· Dynamic spectrum allocation in networks via heuristic methods
· Optimization of the deployment of Intelligent Reflecting Surfaces (IRS)
· Advanced applications based on network optimization
Keywords
Heuristic algorithms, swarm intelligence, particle swarm optimization, network optimization, routing, resource allocation, 5G, IoT, hybrid heuristics, network protocols, real-time optimization, software-defined networking, network traffic prediction, network design, intelligent reflecting surfaces
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