A Multi-Dimensional Resource Scheduling Strategy Based on Multilateral Complementarity

The diversification of computing resources and the increasing complexity of resource demand from applications in terms of type, granularity, and quantity call for more efficiency in resource scheduling. To meet this challenge, this paper proposes a resource description model based on a quantized polygon. It explores the theoretical basis for the multilateral complementarity strategy (MCS), analyzes the basic mechanisms and application architecture of the MCS, and, finally, proposes the multi-dimensional quantized polygon (MQP) algorithm-a multi-dimensional resource scheduling algorithm based on multilateral complementarity (MC-MDRS algorithm). The experiments show that the multi-dimensional resource scheduling strategy based on the MQP, when implemented in an environment in which multi-dimensional ( 3\leq {d}\leq6 ) computing resources are provisioned, can effectively respond to the requests for various computing resources by granular services and facilitate the deployment of granular application services arriving in batches. The analysis of the experimental results indicates that the MQP algorithm outperforms other multi-dimensional resource scheduling algorithms by 2%-5% in node utilization.