An approach based on fuzzy inference system and ant colony optimization for improving the performance of routing protocols in Wireless Sensor Networks.
Ricardo A. L. RabêloJosé V. V. SobralHarilton da S. AraujoRodrigo A. R. S. BaluzRaimir Holanda FilhoPublished in: IEEE Congress on Evolutionary Computation (2013)
Keyphrases
- ant colony optimization
- routing protocol
- fuzzy inference system
- wireless sensor networks
- routing algorithm
- metaheuristic
- ad hoc networks
- fuzzy logic
- sensor networks
- energy efficient
- swarm intelligence
- energy aware
- multi hop
- ant colony
- energy consumption
- energy efficiency
- fuzzy rules
- data transmission
- mobile ad hoc networks
- input output
- neuro fuzzy
- aco algorithm
- traveling salesman problem
- network lifetime
- particle swarm optimization
- ant colonies
- aco algorithms
- routing scheme
- nature inspired
- membership functions
- biological inspired
- artificial ants
- ant colony algorithm
- neural network
- sensor nodes
- fuzzy systems
- genetic algorithm
- fuzzy controller
- wireless communication
- base station
- mobile nodes
- fuzzy model
- rule base
- particle swarm optimization pso
- optimization problems
- search space
- artificial intelligence
- fuzzy sets