Thomas Rausch, TU Wien; Waldemar Hummer and Vinod Muthusamy, IBM Research AI; Alexander Rashed and Schahram Dustdar, TU Wien
This paper proposes a serverless platform for building and operating edge AI applications. We analyze edge AI use cases to illustrate the challenges in building and operating AI applications in edge cloud scenarios. By elevating concepts from AI lifecycle management into the established serverless model, we enable easy development of edge AI workflow functions. We take a deviceless approach, i.e., we treat edge resources transparently as cluster resources, but give developers fine-grained control over scheduling constraints. Furthermore, we demonstrate the limitations of current serverless function schedulers, and present the current state of our prototype.
Open Access Media
USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.
author = {Thomas Rausch and Waldemar Hummer and Vinod Muthusamy and Alexander Rashed and Schahram Dustdar},
title = {Towards a Serverless Platform for Edge {AI}},
booktitle = {2nd USENIX Workshop on Hot Topics in Edge Computing (HotEdge 19)},
year = {2019},
address = {Renton, WA},
url = {https://www.usenix.org/conference/hotedge19/presentation/rausch},
publisher = {USENIX Association},
month = jul
}
