Thea - a QoS, Privacy, and Power-aware Algorithm for Placing Applications on Federated Edges

Abstract

Federations between Edge Computing infrastructure providers represent a promising approach for improving the applications' Quality of Service (QoS) and the infrastructure's resource usage. At the same time, federated edges impose particular provisioning challenges, as data protection policies implemented by certain providers within a federation may conflict with the privacy requirements of services carrying out sensitive information (e.g., databases). In addition, the popularization of complex software architectures (e.g., composite applications) sets strict latency requirements that narrow the provisioning possibilities even further. Previous research efforts targeting federated edges have focused either on coupling with end-user performance requirements (e.g., latency and privacy) or on satisfying infrastructure providers' objectives (e.g., power consumption reduction), but none on balancing both. This paper presents Thea, a novel approach for provisioning composite applications on federated edges which optimizes applications' latency and privacy while reducing the infrastructure's power consumption. Simulated experiments show that Thea can achieve near-optimal results, reducing application latency and privacy issues by 50% and 42.11% and the infrastructure's power consumption by 18.95% compared to state-of-the-art approaches.