LASSY: a Latency-Aware SLOs-Sufficing Scheduling System for the Cloud/Edge Continuum

Cao, Yinan;Riviere, Etienne;Sadre, Ramin
(2025) The 25th IEEE International Symposium on Cluster, Cloud, and Internet Computing — Location: Tromso, Norway (19.May.2025)

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Despite the advancements in cloud computing, cloud-hosted applications face significant network latency challenges, particularly for users distant from data centers. Edge computing has emerged as a solution to mitigate these issues by decentralizing processing, thereby reducing latency and enhancing user experience. However, the limited resources of edge data centers require careful scheduling of application instances to preserve the benefits of edge computing. This paper presents the Latency-Aware SLO-Sufficing Scheduling System (LASSY), a novel approach that considers network and queueing latencies in scheduling decisions for cloud/edge continuum environments. LASSY utilizes queueing theory to predict the tail latency experienced by users of latency-sensitive services such as Edge AI and optimizes service deployment across cloud and edge nodes to meet Service Level Objectives (SLOs). Our contributions include detailed latency modeling, an optimization algorithm that minimizes resource costs while ensuring SLO compliance, comprehensive experiments conducted on a testbed under realistic network emulation, and comparison with a state-of-the-art scheduling model. We evaluated LASSY under real-world latency conditions using two applications: a picture thumbnailing service and an Edge AI OCR service. We demonstrate LASSY’s ability to achieve the desired service quality by effectively managing latency and resource allocation.
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Cao, Y., Riviere, E., & Sadre, R. (2025). LASSY: a Latency-Aware SLOs-Sufficing Scheduling System for the Cloud/Edge Continuum. Proceedings of CCGrid2025. Published. The 25th IEEE International Symposium on Cluster, Cloud, and Internet Computing, Tromso, Norway. https://hdl.handle.net/2078.5/256335