Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
KidSim: programming agents without a programming language
Communications of the ACM
Mobile wireless network system simulation
MobiCom '95 Proceedings of the 1st annual international conference on Mobile computing and networking
Artificial life meets entertainment: lifelike autonomous agents
Communications of the ACM
GloMoSim: a library for parallel simulation of large-scale wireless networks
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Routing in telecommunications networks with ant-like agents
IATA '98 Proceedings of the second international workshop on Intelligent agents for telecommunication applications
On agent-based software engineering
Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Software Agents for Future Communication Systems
Software Agents for Future Communication Systems
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
A Multi-agent System for Resource Management in Wireless Mobile Multimedia Networks
DSOM '00 Proceedings of the 11th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Services Management in Intelligent Networks
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Wireless Communications
Radio Resource Management for Multimedia Qos Support in Wireless Networks
Radio Resource Management for Multimedia Qos Support in Wireless Networks
Wireless Communications
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
KES-AMSTA '07 Proceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
MAMECTIS'08 Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems
MAMECTIS'08 Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems
ICCOM'08 Proceedings of the 12th WSEAS international conference on Communications
An architecture for adaptive intelligent systems
Artificial Intelligence
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
J-Sim: a simulation and emulation environment for wireless sensor networks
IEEE Wireless Communications
An adaptive bandwidth reservation scheme for high-speed multimedia wireless networks
IEEE Journal on Selected Areas in Communications
Hi-index | 0.00 |
Finding suitable channels to allocate in order to serve increasing user demands in a cellular network, which is a dynamical system, constitute the most important issue in terms of network performance since they define the bandwidth management methodology. In modern cellular networks these strategies become challenging issues especially when advanced services are applied. The effectiveness of decision making for channel allocation in a cellular network is strongly connected to current traffic and wireless environment conditions. Moreover, in large scale environments, network states change dynamically and the network performance prediction is a hard task. In the recent literature, the network adaptation to current real user needs seems it could be achieved through computational intelligence based channel allocation schemes mainly involving genetic algorithms. In this paper, a quite new approach for communication channels decision making, based on ant colony optimization, which is a special form of swarm intelligence, modelled through multi agent methodology is presented. The main novelty of this research lies on modelling this optimization scheme through multi agent systems. The simulation model architecture which includes network and ant agents are also presented as well as the performance results based on the above techniques. Finally, the current study, also, shows that there is a great field of research concerning intelligent techniques modelled through multi-agent methodologies focused on channels decision making and bandwidth management in wireless communication systems.