Scheduling Distributed Resources in Heterogeneous Private Clouds

2017/05/17 by George Kesidis, Yuquan Shan, Kesidis, George +9
Computer Science · #Cloud Computing and Resource Management #Distributed systems and fault tolerance #FOS: Computer and information sciences #Optimization and Search Problems #Performance (cs.PF)

paper · pdf · doi:10.48550/arxiv.1705.06102

openalex publication_date 2017/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We first consider the static problem of allocating resources to ( i.e. , scheduling) multiple distributed application framework s, possibly with different priorities and server preferences , in a private cloud with heterogeneous servers. Several fai r scheduling mechanisms have been proposed for this purpose. We extend pr ior results on max-min and proportional fair scheduling to t his constrained multiresource and multiserver case for generi c fair scheduling criteria. The task efficiencies (a metric r elated to proportional fairness) of max-min fair allocations found b y progressive filling are compared by illustrative examples . They show that "server specific" fairness criteria and those that are b ased on residual (unreserved) resources are more efficient.

Citations

• Online Scheduling of Spark Workloads with Mesos using Different Fair Allocation Algorithms

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