CaMP-INC: Components-aware Microservices Placement for In-Network Computing Cloud-Edge Continuum

TL;DR

This paper introduces CaMP-INC, a novel placement strategy for microservices and databases in cloud-edge environments that considers failure, distance, and architecture requirements, optimizing cost and latency.

Contribution

It formulates an ILP model for component placement considering failure and distance, and proposes a heuristic solution for the NP-hard problem.

Findings

CaMP-INC reduces total cost by 15.8% on average.

It outperforms benchmarks in latency minimization.

The heuristic provides efficient solutions for complex placement problems.

Abstract

Microservices are a promising technology for future networks, and many research efforts have been devoted to optimally placing microservices in cloud data centers. However, microservices deployment in edge and in-network devices is more expensive than the cloud. Additionally, several works do not consider the main requirements of microservice architecture, such as service registry, failure detection, and each microservice's specific database. This paper investigates the problem of placing components (i.e. microservices and their corresponding databases) while considering physical nodes' failure and the distance to service registries. We propose a Components-aware Microservices Placement for In-Network Computing Cloud-Edge Continuum (CaMP-INC). We formulate an Integer Linear Programming (ILP) problem with the objective of cost minimization. Due to the problem's NP-hardness, we propose a heuristic solution. Numerical results demonstrate that our proposed solution CaMP-INC reduces the total cost by 15.8 % on average and has a superior performance in terms of latency minimization compared to benchmarks.