Cooperative Service Placement and Scheduling in Edge Clouds: A Deadline-Driven Approach

Mobile edge computing enables resource-limited edge clouds (ECs) in federation to help each other with resource-hungry yet delay-sensitive service requests. Contrary to common practice, we acknowledge that mobile services are heterogeneous and the limited storage resources of ECs allow only a subset of services to be placed at the same time. This paper presents a jointly optimized design of cooperative placement and scheduling framework, named JCPS, that pursues social cost minimization over time while ensuring diverse user demands. Our main contribution is a novel perspective on cost reduction by exploiting the spatial-temporal diversities in workload and resource cost among federated ECs. To build a practical edge cloud federation system, we have to consider two major challenges: user deadline preference and ECs’ strategic behaviors . We first formulate and solve the problem of spatially strategic optimization without deadline awareness, which is proved $\mathcal {NP}$ -hard. By leveraging user deadline tolerance, we develop a Lyapunov-based deadline-driven joint cooperative mechanism under the scenario where the workload and resource information of ECs are known for one-shot global cost minimization. The service priority imposed by deadline urgency drives time-critical placement and scheduling, which, combined with cooperative control, enables workloads migrated across different times and ECs. Given selfishness of individual ECs, we further design an auction-based cooperative mechanism to elicit truthful bids on workload and resource cost. Rigorous theoretical analysis and extensive simulations are performed, validating the efficiency of JCPS in realizing cost reduction and user satisfaction.