In an edge-cloud multi-tier network, datacenters provide services to mobile users, with each service having specific latency constraints and computational requirements. Deploying such a variety of services while matching their requirements with the available computing resources is challenging. In addition, time-critical services may have to be migrated as the users move, to keep fulfilling their latency constraints. Unlike previous work relying on an orchestrator with an always-updated global view of the available resources and the users' locations, this work envisions a distributed solution to the above problems. In particular, we propose a distributed asynchronous framework for service deployment in the edge-cloud that increases the system resilience by avoiding a single point of failure, as in the case of a central orchestrator. Our solution ensures cost-efficient feasible placement of services, while using negligible bandwidth. Our results, obtained through trace-driven, large-scale simulations, show that the proposed solution provides performance very close to those obtained by state-of-the-art centralized solutions, and at the cost of a small communication overhead.

翻译：在边缘-云多级网络中，数据中心为移动用户提供各类服务，每种服务均具有特定的延迟约束和计算需求。在匹配可用计算资源的同时部署如此多样化的服务极具挑战性。此外，当用户移动时，时间敏感型服务可能需要迁移以满足其延迟约束。与依赖持续更新全局资源视图和用户位置的中心化编排器的现有工作不同，本文针对上述问题提出了分布式解决方案。具体而言，我们提出了一种用于边缘-云服务部署的分布式异步框架，该框架通过避免中心化编排器可能导致的单点故障来增强系统弹性。我们的方案能够在占用可忽略不计带宽的情况下，实现经济高效的可满足服务放置。通过基于真实轨迹的大规模仿真实验，结果表明所提方案的性能与现有最先进的集中式解决方案高度接近，且仅引入了极小的通信开销。