Genetic algorithm based heuristics for the mapping problem
Computers and Operations Research - Special issue on genetic algorithms
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Using Architecture Models for Runtime Adaptability
IEEE Software
QoS-aware Service Composition Based on Tree-Coded Genetic Algorithm
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 01
Middleware support for the deployment of ubiquitous software components
Personal and Ubiquitous Computing - Special Issue: Selected Papers of the ARCS06 Conference
Using genetic algorithm to implement cost-driven web service selection
Multiagent and Grid Systems - Special Issue on Nature inspired systems for parallel, asynchronous and decentralised environments
A novel genetic algorithm for qos-aware web services selection
DEECS'06 Proceedings of the Second international conference on Data Engineering Issues in E-Commerce and Services
QoS-aware service composition in dynamic service oriented environments
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
QoS-aware service composition in dynamic service oriented environments
Middleware'09 Proceedings of the ACM/IFIP/USENIX 10th international conference on Middleware
Architectures & infrastructure
Service research challenges and solutions for the future internet
QoS-based service optimization using differential evolution
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Optimization techniques for qos-aware workflow realization in web services context
RED'10 Proceedings of the Third international conference on Resource Discovery
Adaptive MOEA/D for QoS-based web service composition
EvoCOP'13 Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization
QoS decomposition for service composition using genetic algorithm
Applied Soft Computing
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Services running on mobile systems must be able to adapt themselves to changing user needs and availability of resources. We propose to use Genetic Algorithms to search for the best service variant in the current context. The chosen service composition is then deployed on a set of available nodes in an optimal way. We illustrate that Genetic Algorithms provide a scalable and self-organizing solution to service composition and deployment. We argue that the approach meets some main requirements demanded by services running on mobile systems. A motivating scenario is presented in which a distributed server allows users to share content and run applications in mobile ad-hoc networks.