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arXiv · 2006.03720

Skedulix: Hybrid Cloud Scheduling for Cost-Efficient Execution of Serverless Applications

Anirban Das·Andrew Leaf·Carlos A. Varela·Stacy Patterson
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Abstract

We present a framework for scheduling multifunction serverless applications over a hybrid public-private cloud. A set of serverless jobs is input as a batch, and the objective is to schedule function executions over the hybrid platform to minimize the cost of public cloud use, while completing all jobs by a specified deadline. As this scheduling problem is NP-Hard, we propose a greedy algorithm that dynamically determines both the order and placement of each function execution using predictive models of function execution time and network latencies. We present a prototype implementation of our framework that uses AWS Lambda and OpenFaaS, for the public and private cloud, respectively. We evaluate our prototype in live experiments using a mixture of compute and I/O heavy serverless applications. Our results show that our framework can achieve a speedup in batch processing of up to 1.92 times that of an approach that uses only the private cloud, at 40.5% the cost of an approach that uses only the public cloud.

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Anirban Das, Andrew Leaf, Carlos A. Varela, Stacy Patterson. 2020-06-05. Skedulix: Hybrid Cloud Scheduling for Cost-Efficient Execution of Serverless Applications. https://arxiv.org/abs/2006.03720

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