A Prioritized Petri Net Model and Its Application in Distributed Multimedia Systems
IEEE Transactions on Computers
Multimedia, network protocols and users—bridging the gap
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
GROUP '99 Proceedings of the international ACM SIGGROUP conference on Supporting group work
Explanation-Based Neural Network Learning: A Lifelong Learning Approach
Explanation-Based Neural Network Learning: A Lifelong Learning Approach
IEEE Internet Computing
Constructing Adaptive Software in Distributed Systems
ICDCS '01 Proceedings of the The 21st International Conference on Distributed Computing Systems
DRoPS: Kernel Support For Runtime Adaptable Protocols
EUROMICRO '98 Proceedings of the 24th Conference on EUROMICRO - Volume 2
Self-Modifiable Color Petri Nets for Modeling User Manipulation and Network Event Handling
IEEE Transactions on Computers
Evolving Dynamic Multi-Objective Optimization Problems with Objective Replacement
Artificial Intelligence Review
An adaptable transport protocol based on Genetic Algorithms
International Journal of Information and Communication Technology
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Incremental multiple objective genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
QoS routing for anycast communications: motivation and an architecture for DiffServ networks
IEEE Communications Magazine
Incremental backpropagation learning networks
IEEE Transactions on Neural Networks
An adaptable transport protocol based on Genetic Algorithms
International Journal of Information and Communication Technology
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In this paper, we present an adaptable protocol, Genetic Algorithm Transport Protocol (GATP) based on Genetic Algorithms (GAs), which evolves and adapts to the network environment to achieve best-effort user-configurable Quality of Services (QoS). The networking environment is an evolutionary playground for data packets that are evolved using a fitness level of QoS achievement. Different fitness functions of weighted, single objectives, and finally multi-objectives are applied to understand the network problem. Experiments are conducted to provide the performance analysis of GATP in an actual network environment. Experimental results also show how this proposed protocol compares with Transmission Control Protocol (TCP) and User Datagram Protocol (UDP).