Abstract
To improve the service quality of cloud computing, and aiming at the characteristics of resource scheduling optimization problems, this paper proposes a hybrid multi-objective bat algorithm. To prevent the algorithm from falling into a local minimum, the bat population is classified. The back-propagation algorithm based on the mean square error and the conjugate gradient method is used to increase the loudness in the search direction and the pulse emission rate. In addition, the random walk based on lévy flight is also used to improve the optimal solution, thereby improving the algorithm’s global search capability. The simulation results prove that the multi-objective bat algorithm proposed in this paper is superior to the multi-objective ant colony optimization algorithm, genetic algorithm, particle swarm algorithm, and cuckoo search algorithm in terms of makespan, degree of imbalance, and throughput. The cost is also slightly better than the multi-objective ant colony optimization algorithm and the multi-objective genetic algorithm.
Highlights
As a new type of computing model, cloud computing has fundamentally changed the delivery method of computing services and the convenience of resources provided through the Internet
To make it distinguished from the original bat algorithm and other meta-heuristic algorithms, the algorithm proposed in this paper is named the hybrid multi-objective bat algorithm
In IaaS cloud computing, the MOBA algorithm is compared with other meta-heuristic algorithms, and a set of parameters is selected, including makespan, throughput, imbalance, cost, and performance improvement rate
Summary
As a new type of computing model, cloud computing has fundamentally changed the delivery method of computing services and the convenience of resources provided through the Internet. With the continuous development and complexity of cloud computing, this problem has become more challenging. One of the urgent problems to be solved is how to make cloud resource scheduling achieve a balance between availability and low cost, that is, to meet the availability of methods and technologies at a low cost. This requires optimizing load balance, improving scheduling performance, and improving resource utilization, while reducing costs and increasing cost-effectiveness, so as to save energy and achieve good and fast sustainable development
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