Mobility support in industrial edge computing for latency critical applications

Abstract

During the last decade, Industry 4.0 has gained increasing attention. Mainly two factors drive this enormous growth, firstly the pressing need for novel use cases in manufacturing industries and secondly the rapid progress of aiding technologies in wireless communication. The most prominent use cases that shape the future of manufacturing involve batch-size-one production, predictive maintenance, and AI-based quality monitoring. The devices and applications that majorly constitute these use cases are Augmented Reality devices (AR), Autonomous Guided Vehicle (AGV), and Collaborative Robots (CR). These applications have stringent requirements in terms of the amount of data that needs to be processed and the duration within which it needs to be processed. The devices running these applications are mobile in nature. Therefore, they have a small form factor and are resource constrained. Thus, these applications can be offloaded to computers with high resource availability. Cloud Computing (CC) has already paved its way into manufacturing to resolve some of the resource and accessibility issues. However, it is not a viable solution for Industry 4.0 applications due to the latency requirements as well as security concerns. Edge Computing (EC) is a novel paradigm proposed to alleviate the latency-related issues in many commercial use cases. Thus, EC is explored in this work for its viability in Industry 4.0 use cases to identify the challenges and examine their practicality in manufacturing infrastructure. In EC, the computing entities called Edge Servers (ES) are advised to be placed as close as possible to the source of data generation to reduce the latencies involved in communication. Since the backend network infrastructure in factories has limited capacity, and also over-provisioning it is expensive, the placement of ESs centrally at the factory data center creates an extensive load on the network. Therefore, a distributed EC is necessary ideally at the first hop of the communication channel. The first hop is catered by wireless technologies with high data transmission rates, such as 5G. However, the devices considered in Industry 4.0 use cases are highly mobile and the corresponding applications offloaded are stateful. Thus, to avoid data traffic over the backend network, the application on the ES needs to be migrated to a suitable ES closer to the mobile client. The downtime experienced during the migration process influences the quality of experience of the clients. Additionally, depending on the number of mobile devices present in the system, the number of migration triggers increases. Accordingly, a new ES needs to be selected for all the clients that experience response time violation. Moreover, the migration triggers need to be orchestrated to avoid congesting the backend network with the migration data. The state-of-the-art does not offer a complete mobility support solution for Industry 4.0 scenario. Thus, this work makes two major contributions to provide a practical approach for mobility support in industrial edge computing for latency critical applications. Firstly, it proposes a novel stateful migration scheme that reduces the downtime during the migration by a factor of 4−7 compared to an established state-of-the-art migration scheme. Subsequently, an extension of this migration schemed to further reduce the downtime to "zero". Secondly, it proposes a scheduling scheme to orchestrate multiple simultaneous migration triggers, that in turn reduces the total amount of data migrated by 64.15%. All the statements are backed by thorough evaluations done using an NS3-simulation environment.