Abstract
Heuristic schemes and algorithms are successfully used for solving optimization problems. A great challenge in large-scale wireless networks is the channel allocation adaptability to dynamic network traffic conditions, which can be
formulated as a discrete optimization problem. Several approaches such as genetic algorithms and multi-agent techniques have been applied so far in the literature for solving the resource management problem focusing mainly on network base-stations representation. A very promising intelligent approach known as ant colony optimization (ACO) which constitutes a special form of swarm intelligence has been used for solving routing problems. This approach has been introduced by the authors for improving the channel allocation in large-scale wireless networks, focusing on network procedures as the basic model component and not on network nodes as so far found in the literature. A comprehensive intelligent model architecture based on multi-agent systems technology and ACO for channel allocation in cellular networks is herein analysed and proposed. Moreover, the decision making for channel allocation is presented as well as the network-ant agent communication model. The new methodology for integrating ACO schemes and decision making regarding spectrum reuse in a multi-agent framework, through a novel agent negotiation approach, is the main contribution of this research. Finally, the simulation results show the large-scale wireless network performance improvement in
terms of efficient resource management.
formulated as a discrete optimization problem. Several approaches such as genetic algorithms and multi-agent techniques have been applied so far in the literature for solving the resource management problem focusing mainly on network base-stations representation. A very promising intelligent approach known as ant colony optimization (ACO) which constitutes a special form of swarm intelligence has been used for solving routing problems. This approach has been introduced by the authors for improving the channel allocation in large-scale wireless networks, focusing on network procedures as the basic model component and not on network nodes as so far found in the literature. A comprehensive intelligent model architecture based on multi-agent systems technology and ACO for channel allocation in cellular networks is herein analysed and proposed. Moreover, the decision making for channel allocation is presented as well as the network-ant agent communication model. The new methodology for integrating ACO schemes and decision making regarding spectrum reuse in a multi-agent framework, through a novel agent negotiation approach, is the main contribution of this research. Finally, the simulation results show the large-scale wireless network performance improvement in
terms of efficient resource management.
Original language | English |
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Title of host publication | Wireless Communications, Networking and Applications |
Subtitle of host publication | proceedings of WCNA 2014 |
Editors | Q.-A. Zeng |
Place of Publication | India |
Publisher | Springer |
Pages | 783-798 |
Number of pages | 16 |
Volume | 348 |
ISBN (Print) | 978-81-322-2579-9 |
DOIs | |
Publication status | Published - 29 Oct 2015 |
Event | International Conference on Wireless Communications, Networking and Applications (WCNA 2014) - Shenzhen, China Duration: 27 Dec 2014 → 28 Dec 2014 |
Publication series
Name | Lecture Notes in Electrical Engineering |
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Publisher | Springer |
ISSN (Print) | 1876-1100 |
Conference
Conference | International Conference on Wireless Communications, Networking and Applications (WCNA 2014) |
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Country/Territory | China |
City | Shenzhen |
Period | 27/12/14 → 28/12/14 |
Keywords
- Wireless communications
- Resource management
- Multi-agent systems
- Cellular networks
- Swarm intelligence
- Spectrum reuse
- Channel allocation