With the development of networking technology, the computing system has evolved towards the multi-tier paradigm gradually. However, challenges, such as multi-resource heterogeneity of devices, resource competition of services, and networked system dynamics, make it difficult to guarantee service-level agreement (SLA) for the applications. In this paper, we propose a multi-tier edge-cloud computing framework, EdgeMatrix, to maximize the throughput of the system while guaranteeing different SLA priorities. First, in order to reduce the impact of physical resource heterogeneity, EdgeMatrix introduces the Networked Multi-agent Actor-Critic (NMAC) algorithm to re-define physical resources with the same quality of service as logically isolated resource units and combinations, i.e., cells and channels. In addition, a multi-task mechanism is designed in EdgeMatrix to solve the problem of Joint Service Orchestration and Request Dispatch (JSORD) for matching the requests and services, which can significantly reduce the optimization runtime. For integrating above two algorithms, EdgeMatrix is designed with two time-scales, i.e., coordinating services and resources at the larger time-scale, and dispatching requests at the smaller time-scale. Realistic trace-based experiments proves that the overall throughput of EdgeMatrix is 36.7% better than that of the closest baseline, while the SLA priorities are guaranteed still.

翻译：随着网络技术的发展，计算系统逐步向多层范式演进。然而，设备的多资源异构性、服务间的资源竞争以及网络化系统的动态特性等问题，使得应用的服务等级协议（SLA）保障面临挑战。本文提出多层边缘-云计算框架EdgeMatrix，在保障不同SLA优先级的同时最大化系统吞吐量。首先，为降低物理资源异构性的影响，EdgeMatrix引入网络化多智能体Actor-Critic（NMAC）算法，将具有相同服务质量的物理资源重定义为逻辑隔离的资源单元与组合（即单元与信道）。此外，EdgeMatrix设计了多任务机制以解决联合服务编排与请求调度（JSORD）问题，通过匹配请求与服务显著缩短优化运行时间。为整合上述两种算法，EdgeMatrix采用双时间尺度设计：在大时间尺度上协调服务与资源，在小时间尺度上调度请求。基于真实轨迹的实验证明，EdgeMatrix的整体吞吐量比最优基线方法提升36.7%，同时仍能保证SLA优先级。