No Delay: Latency-Driven, Application Performance-Aware, Cluster Scheduling

TL;DR

This paper introduces NoMora, a cluster scheduling system that improves application performance by considering network latency and migrating tasks to optimize placement within data centers.

Contribution

It proposes a latency-aware scheduling policy that dynamically adjusts task placement based on network conditions, enhancing performance and reducing placement latency.

Findings

Up to 13.4% increase in application performance

Up to 42% performance improvement with preemption

1.79x faster task placement latency

Abstract

Given the network latency variability observed in data centers, applications' performance is also determined by their placement within the data centre. We present NoMora, a cluster scheduling architecture whose core is represented by a latency-driven, application performance-aware, cluster scheduling policy. The policy places the tasks of an application taking into account the expected performance based on the measured network latency between pairs of hosts in the data center. Furthermore, if a tenant's application experiences increased network latency, and thus lower application performance, their application may be migrated to a better placement. Preliminary results show that our policy improves the overall average application performance by up to 13.4% and by up to 42% if preemption is enabled, and improves the task placement latency by a factor of 1.79x and the median algorithm runtime by 1.16x compared to a random policy on the Google cluster workload. This demonstrates that application performance can be improved by exploiting the relationship between network latency and application performance, and the current network conditions in a data center, while preserving the demands of low-latency cluster scheduling.