Workrs: Fault Tolerant Horizontal Computation Offloading
Alexander Droob, Daniel Morratz, Frederik Langkilde Jakobsen, Jacob, Carstensen, Magnus Mathiesen, Rune Bohnstedt, Michele Albano, Sergio, Moreschini, Davide Taibi

TL;DR
Workrs is a fault-tolerant system for offloading jobs from edge devices, using Docker checkpointing to enable resumption after faults, with an optimized checkpointing strategy based on job forecast times.
Contribution
This paper introduces Workrs, a scalable, fault-tolerant offloading system for edge devices that employs Docker checkpointing and a mathematical model for checkpoint optimization.
Findings
Checkpointing improves job completion in fault-prone scenarios.
The prototype demonstrates benefits when job times exceed forecast fault rates.
The system is scalable with no single point of failure.
Abstract
The broad development and usage of edge devices has highlighted the importance of creating resilient and computationally advanced environments. When working with edge devices these desiderata are usually achieved through replication and offloading. This paper reports on the design and implementation of Workrs, a fault tolerant service that enables the offloading of jobs from devices with limited computational power. We propose a solution that allows users to upload jobs through a web service, which will be executed on edge nodes within the system. The solution is designed to be fault tolerant and scalable, with no single point of failure as well as the ability to accommodate growth, if the service is expanded. The use of Docker checkpointing on the worker machines ensures that jobs can be resumed in the event of a fault. We provide a mathematical approach to optimize the number of…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Age of Information Optimization · Cloud Computing and Resource Management
