Cooperative Service Placement and Scheduling in Edge Clouds: A Deadline-Driven Approach
Yuqing Li, Wenkuan Dai, Xiaoying Gan, Haiming Jin, Luoyi Fu, Huadóng Ma, Xinbing Wang · IEEE Transactions on Mobile Computing · 2021
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 pursuessocial cost minimizationover time while ensuring diverse user demands. Our main contribution is a novel perspective on cost reduction by exploiting thespatial-temporal diversitiesinworkload and resource costamong federated ECs. To build a practical edge cloud federation system, we have to consider two major challenges:user deadline preferenceandECs’ 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-baseddeadline-drivenjoint cooperative mechanism under the scenario where the workload and resource information of ECs are known for one-shot global cost minimization. Theservice priorityimposed 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 elicittruthful bidson workload and resource cost. Rigorous theoretical analysis and extensive simulations are performed, validating the efficiency of JCPS in realizing cost reduction and user satisfaction.