Edge cloud solutions that bring the cloud closer to the sensors can be very useful to meet the low latency requirements of many Internet-of-Things (IoT) applications. However, IoT traffic can also be intermittent, so running applications constantly can be wasteful. Therefore, having a serverless edge cloud that is responsive and provides low-latency features is a very attractive option for a resource and cost-efficient IoT application environment.In this paper, we discuss the key components needed to support IoT traffic in the serverless edge cloud and identify the critical challenges that make it difficult to directly use existing serverless solutions such as Knative, for IoT applications. These include overhead from heavyweight components for managing the overall system and software adaptors for communication protocol translation used in off-the-shelf serverless platforms that are designed for large-scale centralized clouds. The latency imposed by ‘cold start’ is a further deterrent.To address these challenges we redesign several components of the Knative serverless framework. We use a streamlined protocol adaptor to leverage the MQTT IoT protocol in our serverless framework for IoT event processing. We also create a novel, event-driven proxy based on the extended Berkeley Packet Filter (eBPF), to replace the regular heavyweight Knative queue proxy. Our preliminary experimental results show that the event-driven proxy is a suitable replacement for the queue proxy in an IoT serverless environment and results in lower CPU usage and a higher request throughput.
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Supporting IoT Applications with Serverless Edge Clouds
Cloud computing has grown because of lowered costs due to economies of scale and multiplexing. Serverless computing exploits multiplexing in cloud computing however, for low latency required by IoT applications, the cloud should be moved nearer to the IoT device and the cold start problem should be addressed. Using a real-world dataset, we showed through implementation in an open-source cloud environment based on Knative that a serverless approach to manage IoT traffic is feasible, uses less resources than a serverfull approach and traffic prediction with prefetching can mitigate the cold start delay penalty. However applying the Knative framework directly to IoT traffic without considering the execution context gives unnecessary overhead.
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- Award ID(s):
- 1763929
- NSF-PAR ID:
- 10299327
- Date Published:
- Journal Name:
- 2020 IEEE 9th International Conference on Cloud Networking (CloudNet)
- Page Range / eLocation ID:
- 1 to 4
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CloudNet51028.2020.9335805
