Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consis...Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consists of two allocation stages, dominant resource fair(DRF) allocation stage and max-min fairness(MMF) allocation stage. The proposed DMMF scheme exhibits desirable properties, including share incentive, strategy proofness, envy freeness and Pareto optimality. Meanwhile, DMMF can improve the allocation efficiency and reach 100% allocation efficiency.展开更多
A Dominant Resource Fairness (DRF) based scheme for job scheduling in distributed cloud computing systems which was modeled as multi-job scheduling and multi-resource allocation coupling problem is proposed, where t...A Dominant Resource Fairness (DRF) based scheme for job scheduling in distributed cloud computing systems which was modeled as multi-job scheduling and multi-resource allocation coupling problem is proposed, where the resource pool is constructed from a large number of distributed heterogeneous servers, representing different points in the configuration space of resources such as processing, memory, storage and bandwidth. By introducing dominant resource share of jobs and virtual machines, the multi-job scheduling and multi-resource allocation joint mechanism significantly improves the cloud system's resource utilization, yet with a substantial reduction of job completion times. We show through experiments and case studies the superior performance of the algorithms in practice.展开更多
基金supported by the National High-Tech R&D Program (863 Program) No. 2015AA01A705the National Natural Science Foundation of China under Grant No. 61572072+1 种基金the National Science and Technology Major Project No. 2015ZX03001041Fundamental Research Funds for the Central Universities "Research on the System of Personalized Education using Big Data"
文摘Resource allocation is crucial for satellite networks. In this paper, we propose a multi-resource fair allocation scheme, namely Dominant and Max-min Fair(DMMF), to efficiently and fairly allocate resources. It consists of two allocation stages, dominant resource fair(DRF) allocation stage and max-min fairness(MMF) allocation stage. The proposed DMMF scheme exhibits desirable properties, including share incentive, strategy proofness, envy freeness and Pareto optimality. Meanwhile, DMMF can improve the allocation efficiency and reach 100% allocation efficiency.
文摘A Dominant Resource Fairness (DRF) based scheme for job scheduling in distributed cloud computing systems which was modeled as multi-job scheduling and multi-resource allocation coupling problem is proposed, where the resource pool is constructed from a large number of distributed heterogeneous servers, representing different points in the configuration space of resources such as processing, memory, storage and bandwidth. By introducing dominant resource share of jobs and virtual machines, the multi-job scheduling and multi-resource allocation joint mechanism significantly improves the cloud system's resource utilization, yet with a substantial reduction of job completion times. We show through experiments and case studies the superior performance of the algorithms in practice.