Energy-efficient Multi-task Scheduling Based on MapReduce for Cloud Computing

For the problem that the energy efficiency of the cloud computing data center is low, from the point of view of the energy efficiency of the servers, we propose a new energy-efficient multi-task scheduling model based on Google's massive data processing framework. To solve this model, we design a practical encoding and decoding method for the individuals, and construct an overall energy efficiency function of the servers as the fitness value of the individual. Meanwhile, in order to accelerate the convergent speed and enhance the searching ability of our algorithm, a local search operator is introduced. Finally, the experiments show that the proposed algorithm is effective and efficient.