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.

翻译：微服务是未来网络中一项具有前景的技术，目前已有大量研究致力于在云数据中心优化微服务部署。然而，在边缘与网内设备上部署微服务比云端更为昂贵。此外，多数学术工作未考虑微服务架构的核心需求，如服务注册、故障检测以及各微服务专属数据库。本文研究在考虑物理节点故障及与服务注册中心距离的基础上，部署组件（即微服务及其对应数据库）的问题。我们提出了一种面向网络计算云边连续体的组件感知微服务部署方法CaMP-INC，并构建了以成本最小化为目标的整数线性规划模型。鉴于该问题的NP难特性，我们进一步提出了启发式求解方案。数值结果表明，与基准方法相比，所提CaMP-INC方法平均降低总成本15.8%，并在延迟最小化方面展现出更优性能。