A New Approach for Evaluating the Performance of Distributed Latency-Sensitive Services

TL;DR

This paper introduces five novel latency metrics designed to better evaluate distributed latency-sensitive services, addressing limitations of traditional metrics by capturing SLA violations and latency recovery times, validated through large-scale experiments.

Contribution

The paper proposes five new latency metrics that enhance performance evaluation of modern distributed services, focusing on SLA breaches and latency recovery, which are not covered by traditional metrics.

Findings

Proposed metrics provide deeper insights into SLA violations.

Large-scale experiments validate the usefulness of the new metrics.

New metrics outperform traditional ones in assessing latency behavior.

Abstract

Conventional latency metrics are formulated based on a broad definition of traditional monolithic services, and hence lack the capacity to address the complexities inherent in modern services and distributed computing paradigms. Consequently, their effectiveness in identifying areas for improvement is restricted, falling short of providing a comprehensive evaluation of service performance within the context of contemporary services and computing paradigms. More specifically, these metrics do not offer insights into two critical aspects of service performance: the frequency of latency surpassing specified Service Level Agreement (SLA) thresholds and the time required for latency to return to an acceptable level once the threshold is exceeded. This limitation is quite significant in the frame of contemporary latency-sensitive services, and especially immersive services that require deterministic low latency that behaves in a consistent manner. Towards addressing this limitation, the authors of this work propose 5 novel latency metrics that when leveraged alongside the conventional latency metrics manage to provide advanced insights that can be potentially used to improve service performance. The validity and usefulness of the proposed metrics in the frame of providing advanced insights into service performance is evaluated using a large-scale experiment.