ROSE : Cluster Resource Scheduling via Speculative Over-subscription

Sun, Xiaoyang and Hu, Chunming and Yang, Renyu and Garraghan, Peter and Wo, Tianyu and Xu, Jie and Zhu, Jianyong and Li, Chao (2018) ROSE : Cluster Resource Scheduling via Speculative Over-subscription. In: 38th IEEE International Conference on Distributed Systems Computing Systems :. 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) . IEEE, pp. 949-960. ISBN 9781538668719

[thumbnail of ROSE: Cluster Resource Scheduling via Speculative Over-subscription - Camera Ready Version]
Preview
PDF (ROSE: Cluster Resource Scheduling via Speculative Over-subscription - Camera Ready Version)
ICDCS_Camera_Ready.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (2MB)

Abstract

A long-standing challenge in cluster scheduling is to achieve a high degree of utilization of heterogeneous resources in a cluster. In practice there exists a substantial disparity between perceived and actual resource utilization. A scheduler might regard a cluster as fully utilized if a large resource request queue is present, but the actual resource utilization of the cluster can be in fact very low. This disparity results in the formation of idle resources, leading to inefficient resource usage and incurring high operational costs and an inability to provision services. In this paper we present a new cluster scheduling system, ROSE, that is based on a multi-layered scheduling architecture with an ability to over-subscribe idle resources to accommodate unfulfilled resource requests. ROSE books idle resources in a speculative manner:instead of waiting for resource allocation to be confirmed by the centralized scheduler,it requests intelligently to launch tasks within machines according to their suitability to oversubscribe resources. A threshold control with timely task rescheduling ensures fully-utilized cluster resources without generating potential tasks tragglers. Experimental results show that ROSE can almost double the average CPU utilization, from 36.37% to 65.10%, compared with a centralized scheduling scheme, and reduce the workload makespan by 30.11%, with an 8.23% disk utilization improvement over other scheduling strategies.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
125028
Deposited By:
Deposited On:
08 May 2018 08:32
Refereed?:
Yes
Published?:
Published
Last Modified:
20 Sep 2024 23:54