FogROS2-Config: Optimizing Latency and Cost for Multi-Cloud Robot Applications
arxiv(2023)
摘要
Cloud service providers provide over 50,000 distinct and dynamically changing
set of cloud server options. To help roboticists make cost-effective decisions,
we present FogROS2-Config, an open toolkit that takes ROS2 nodes as input and
automatically runs relevant benchmarks to quickly return a menu of cloud
compute services that tradeoff latency and cost. Because it is infeasible to
try every hardware configuration, FogROS2-Config quickly samples tests a small
set of edge case servers. We evaluate FogROS2-Config on three robotics
application tasks: visual SLAM, grasp planning. and motion planning.
FogROS2-Config can reduce the cost by up to 20x. By comparing with a Pareto
frontier for cost and latency by running the application task on feasible
server configurations, we evaluate cost and latency models and confirm that
FogROS2-Config selects efficient hardware configurations to balance cost and
latency.
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