An Improved Genetic Algorithm for Service Selection under Temporal Constraints in Cloud Computing

摘要

To guarantee the successful execution of service based processes in cloud computing, one important requirement is the QoS-driven selection of candidate services under temporal constraints. In this paper, a new approach based on improved genetic algorithm (HPGA) is proposed where the hamming similarity degree is used to avoid inbreeding and the pheromone strategy is designed with considering not only the individual fitness but also the global information of best chromosomes. Compared with the existing works, this approach is more precise and especially suitable for the service selection of large-scale and complex processes with vast amounts of candidate services.