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BeeHive: An efficient fault-tolerant routing algorithm inspired by honey bee behavior

Horst F. Wedde, +2 more
- pp 83-94
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TLDR
This paper presents a novel routing algorithm, BeeHive, which has been inspired by the communicative and evaluative methods and procedures of honey bees and achieves a similar or better performance compared to state-of-the-art algorithms.
Abstract
Bees organize their foraging activities as a social and communicative effort, indicating both the direction, distance and quality of food sources to their fellow foragers through a ”dance” inside the bee hive (on the ”dance floor”). In this paper we present a novel routing algorithm, BeeHive, which has been inspired by the communicative and evaluative methods and procedures of honey bees. In this algorithm, bee agents travel through network regions called foraging zones. On their way their information on the network state is delivered for updating the local routing tables. BeeHive is fault tolerant, scalable, and relies completely on local, or regional, information, respectively. We demonstrate through extensive simulations that BeeHive achieves a similar or better performance compared to state-of-the-art algorithms.

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Citations
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Journal ArticleDOI

A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

TL;DR: Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm that is used for optimizing multivariable functions and the results showed that ABC outperforms the other algorithms.
Journal ArticleDOI

On the performance of artificial bee colony (ABC) algorithm

TL;DR: The simulation results show that the performance of ABC algorithm is comparable to those of differential evolution, particle swarm optimization and evolutionary algorithm and can be efficiently employed to solve engineering problems with high dimensionality.
Journal ArticleDOI

A comparative study of Artificial Bee Colony algorithm

TL;DR: Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.
Journal ArticleDOI

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

TL;DR: This work presents a comprehensive survey of the advances with ABC and its applications and it is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.
Journal ArticleDOI

A survey on optimization metaheuristics

TL;DR: The components and concepts that are used in various metaheuristics are outlined in order to analyze their similarities and differences and the classification adopted in this paper differentiates between single solution based metaheURistics and population based meta heuristics.
References
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Book

Genetic algorithms in search, optimization, and machine learning

TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.

Genetic algorithms in search, optimization and machine learning

TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Journal ArticleDOI

A note on two problems in connexion with graphs

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
BookDOI

Swarm intelligence: from natural to artificial systems

TL;DR: This chapter discusses Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks, and its application to Data Analysis and Graph Partitioning.
Book

The dance language and orientation of bees

TL;DR: The Dance Language and Orientation of Bees as discussed by the authors is a seminal work in the field of honeybee behavior that describes in non-technical language what he discovered in a lifetime of study about honeybees - their methods of orientation, their sensory faculties, and their remarkable ability to communicate with one another.