COSTREAM: Learned Cost Models for Operator Placement in Edge-Cloud Environments

arXiv:2403.08444v1 Announce Type: cross
Abstract: In this work, we present COSTREAM, a novel learned cost model for Distributed Stream Processing Systems that provides accurate predictions of the execution costs of a streaming query in an edge-cloud environment. The cost model can be used to find an initial placement of operators across heterogeneous hardware, which is particularly important in these environments. In our evaluation, we demonstrate that COSTREAM can produce highly accurate cost estimates for the initial operator placement and even …

abstract arxiv cloud cloud environments cost costs cs.db cs.dc cs.lg distributed edge environment environments novel operators placement predictions processing query streaming stream processing systems type work