Managing Latency in Edge-Cloud Environment

TL;DR

This paper introduces a method to predict and guarantee the response time upper bounds for services in edge-cloud environments, ensuring real-time performance without requiring special programming models.

Contribution

It presents a novel approach for real-time response time prediction in cloud and edge-cloud services that is developer-friendly and compatible with high-level programming languages.

Findings

Provides soft real-time guarantees for cloud services

Predicts upper bounds of response times accurately

Minimizes developer effort without special programming models

Abstract

Modern Cyber-physical Systems (CPS) include applications like smart traffic, smart agriculture, smart power grid, etc. Commonly, these systems are distributed and composed of end-user applications and microservices that typically run in the cloud. The connection with the physical world, which is inherent to CPS, brings the need to operate and respond in real-time. As the cloud becomes part of the computation loop, the real-time requirements have to be also reflected by the cloud. In this paper, we present an approach that provides soft real-time guarantees on the response time of services running in cloud and edge-cloud (i.e., cloud geographically close to the end-user), where these services are developed in high-level programming languages. In particular, we elaborate a method that allows us to predict the upper bound of the response time of a service when sharing the same computer with other services. Importantly, as our approach focuses on minimizing the impact on the developer of such services, it does not require any special programming model nor limits usage of common libraries, etc.