STOIC: Serverless TeleOperable Hybrid Cloud for Machine Learning Applications on Edge Device
Serverless computing is a promising new event- driven programming model that was designed by cloud vendors to expedite the development and deployment of scalable web services on cloud computing systems. Using the model, developers write applications that consist of simple, independent, stateless functions that the cloud invokes on-demand (i.e. elastically), in response to system-wide events (data arrival, messages, web requests, etc.). In this work, we present STOIC (Serverless TeleOperable HybrId Cloud), an application scheduling and deployment system that extends the serverless model in two ways. First, it uses the model in a distributed setting and schedules application functions across multiple cloud systems. Second, STOIC sup- ports serverless function execution using hardware acceleration (e.g. GPU resources) when available from the underlying cloud system. We overview the design and implementation of STOIC and empirically evaluate it using real-world machine learning applications and multi-tier (e.g. edge-cloud) deployments. We find that STOIC’s combined use of edge and cloud resources is able to outperform using either cloud in isolation for the applications and datasets that we consider.
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10164154
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International Workshop on Smart Edge Computing and Networking
4. Serverless computing platforms have gained popularity because they allow easy deployment of services in a highly scalable and cost-effective manner. By enabling just-in-time startup of container-based services, these platforms can achieve good multiplexing and automatically respond to traffic growth, making them particularly desirable for edge cloud data centers where resources are scarce. Edge cloud data centers are also gaining attention because of their promise to provide responsive, low-latency shared computing and storage resources. Bringing serverless capabilities to edge cloud data centers must continue to achieve the goals of low latency and reliability. The reliability guarantees provided by serverless computing however are weak, with node failures causing requests to be dropped or executed multiple times. Thus serverless computing only provides a best effort infrastructure, leaving application developers responsible for implementing stronger reliability guarantees at a higher level. Current approaches for providing stronger semantics such as exactly once'' guarantees could be integrated into serverless platforms, but they come at high cost in terms of both latency and resource consumption. As edge cloud services move towards applications such as autonomous vehicle control that require strong guarantees for both reliability and performance, these approaches may no longer be sufficient. In this paper we evaluatemore »