Serverless computing has increased in popularity as a programming model for “Internet of Things” (IoT) applications that amalgamate IoT devices, edge-deployed computers and systems, and the cloud to interoperate. In this paper, we present Laminar – a dataflow pro- gram representation for distributed IoT application programming – and describe its implementation based on a network-transparent, event-driven, serverless computing infrastructure that uses append- only log storage to store all program state. We describe the initial implementation of Laminar, discuss some useful properties we obtained by leveraging log-based data structures and triggered com- putations of the underlying serverless runtime, and illustrate its performance and reliability characteristics using a set of benchmark applications.
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PEDaLS: Persisting Versioned Data Structures
In this paper, we investigate how to automatically persist versioned data structures in distributed settings (e.g. cloud + edge) using append-only storage. By doing so, we facilitate resiliency by enabling program state to survive program activations and termination, and program-level data structures and their version information to be accessed programmatically by multiple clients (for replay, provenance tracking, debugging, and coordination avoidance, and more). These features are useful in distributed, failure-prone contexts such as those for heterogeneous and pervasive Internet of Things (IoT) deployments. We prototype our approach within an open-source, distributed operating system for IoT. Our results show that it is possible to achieve algorithmic complexities similar to those of in-memory versioning but in a distributed setting.
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- NSF-PAR ID:
- 10334315
- Date Published:
- Journal Name:
- IEEE International Conference on Cloud Engineering
- Page Range / eLocation ID:
- 179 to 190
- 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/IC2E52221.2021.00033
