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PI-Edge: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services

Jie Tang, Shaoshan Liu, Yu Bo, Weisong Shi

Year
2018
Citations
17
Access
Open access

Abstract

To simultaneously enable multiple autonomous driving services on affordable embedded systems, we designed and implemented π-Edge, a complete edge computing framework for autonomous robots and vehicles. The contributions of this paper are three-folds: first, we developed a runtime layer to fully utilize the heterogeneous computing resources of low-power edge computing systems; second, we developed an extremely lightweight operating system to manage multiple autonomous driving services and their communications; third, we developed an edge-cloud coordinator to dynamically offload tasks to the cloud to optimize client system energy consumption. To the best of our knowledge, this is the first complete edge computing system of a production autonomous vehicle. In addition, we successfully implemented π-Edge on a Nvidia Jetson and demonstrated that we could successfully support multiple autonomous driving services with only 11 W of power consumption, and hence proving the effectiveness of the proposed π-Edge system.

Keywords

Enhanced Data Rates for GSM EvolutionEdge computingPower (physics)Computer scienceEdge deviceTelecommunicationsOperating systemPhysics

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