Cost-Effective Traffic Scheduling and Resource Allocation for Edge Service Provisioning

The multi-access edge computing (MEC) paradigm has emerged as a critical solution to address the exponential growth in mobile web services and devices. By implementing an edge-based service provisioning system (EPS) with servers located at the network's edge, both transmission and computation efficiency can be significantly enhanced. Nevertheless, it is also essential to carefully consider the resource allocation for services, the traffic management of requests, and the path arrangement for data delivery to ensure the cost-effective operation of the EPS. Therefore, we investigate and quantify the relationship between the performance and cost of the EPS in this paper, and model the cost-effective service provisioning problem as a multi-phase convex optimization problem. An online algorithm whose name is RDC based on the Lyapunov framework is proposed to decompose this problem into several sub-problems.Additionally, a heuristic approach that partitions edge servers into several clusters, called RDC-NeP and based on RDC, has also been proposed to reduce computational complexity. A series of experiments were conducted to evaluate the proposed approach. The results demonstrate that RDC can effectively balance expense and performance, while RDC-NeP significantly simplifies the processing of RDC when the problem scale increases.