Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Out of control: the new biology of machines, social systems, and the economic world
Out of control: the new biology of machines, social systems, and the economic world
Ant-like agents for load balancing in telecommunications networks
AGENTS '97 Proceedings of the first international conference on Autonomous agents
A Swarm Approach for Emission Sources Localization
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Firefly-inspired sensor network synchronicity with realistic radio effects
Proceedings of the 3rd international conference on Embedded networked sensor systems
Unified layer-2 triggers and application-aware motifications
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Adaptive channel allocation spectrum etiquette for cognitive radio networks
Mobile Networks and Applications
CrossTalk: cross-layer decision support based on global knowledge
IEEE Communications Magazine
Optimizing programs with intended semantics
Proceedings of the 24th ACM SIGPLAN conference on Object oriented programming systems languages and applications
From biological and social network metaphors to coupled bio-social wireless networks
International Journal of Autonomous and Adaptive Communications Systems
Full length article: Minority game for cognitive radios: Cooperating without cooperation
Physical Communication
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In recent years, various types of control algorithms have been proposed for cognitive radios (CR), ranging from algorithms coordinated by centralized control to ones coordinated in a distributed manner. These algorithms, however, all require communication to either peer nodes or a master node, thus creating communication overhead and potential vulnerability. We introduce a new class of control algorithms to the area of CRs derived from observations of emergent design in nature. Specifically, we introduce an algorithmic approach based on swarm behavior to the task of configuration management in CR networks. Without requiring the exchange of information among peers or a central authority, CRs equipped with such an algorithm are able to globally optimize the configuration of a CR network in the presence of interference and jammers, while only relying on local information, thus providing a fast and efficient way for configuration management especially for large networks.