Online SLA-Aware Multi-Resource Allocation for Deadline Sensitive Jobs in Edge-Clouds

Abstract

With the explosive growth of mobile applications and high computation burden on each single device, more and more end users demand to offload expensive computing tasks to external sites via job offloading technologies. Due to the fluctuating nature of jobs from end users, traditional cloud computing paradigm, however, has difficulties in accommodating highly dynamic job requests and meeting heterogeneous user requirements. Locating close to mobile users, edge-clouds have the potential to complement the cloud computing platform by acting as an efficient spot to perform users' deadline-sensitive tasks. In this paper, we study the resource allocation problem for accommodating deadline-sensitive jobs in edge-cloud system. We formulate a revenue maximization problem that captures the SLA-oriented property of job execution, and propose an efficient online multi-resource allocation algorithm that achieves low competitive ratio with moderate resource augmentation.