A Self-Adaptive Strategy of Data Streams Scheduling on Heterogeneous Cluster

Data streams scheduling is a typical NP-complete problem.To solve the problem of data streams scheduling on heterogeneous cluster effectively,a self-adaptive strategy based on improved particle swarm optimization is proposed.Inspired by the gene theory,a transgenic operator is designed to keep the best individual and improve the ability of local solution.The mutation operator is built into the proposed strategy to maintain population diversity and improve the ability of global exploration.Simulation results show that the proposed strategy gives a good balance between local solution and global exploration and has excellent efficiency in data streams scheduling.