A Model for the Remote Deployment, Update, and Safe Recovery for Commercial Sensor-Based IoT Systems

Abstract

Internet of Things (IoT) systems deployments are becoming both ubiquitous and business critical in numerous business verticals, both for process automation and data-driven decision-making based on distributed sensors networks. Beneath the simplicity offered by these solutions, we usually find complex, multi-layer architectures—from hardware sensors up to data analytics systems. These rely heavily on software running on the on-location gateway devices designed to bridge the communication between the sensors and the cloud. This will generally require updates and improvements—raising deployment and maintenance challenges. Especially for large scale commercial solutions, a secure and fail-safe updating system becomes crucial for a successful IoT deployment. This paper explores the specific challenges for infrastructures dedicated to remote application deployment and management, addresses the management challenges related to IoT sensors systems, and proposes a mathematical model and a methodology for tackling this. To test the model’s efficiency, we implemented it as a software infrastructure system for complete commercial IoT products. As proof, we present the deployment of 100 smart soda dispensing machines in three locations. Each machine relies on sensors monitoring its status and on gateways controlling its behaviour, each receiving 133 different remote software updates through our solution. In addition, 80% of the machines ran non-interrupted for 250 days, with 20% failing due to external factors; out of the 80%, 30% experienced temporary update failures due to reduced hardware capabilities and the system successfully performed automatic rollback of the system, thus recovering in 100% of the temporary failures.