Stringent latency requirements in advanced Internet of Things (IoT) applications as well as an increased load on cloud data centers have prompted a move towards a more decentralized approach, bringing storage and processing of IoT data closer to the end-devices through the deployment of multi-purpose IoT gateways. However, the resource constrained nature and diversity of these gateways pose a challenge in developing applications that can be deployed widely. This challenge can be overcome with containerization, a form of lightweight virtualization, bringing support for a wide range of hardware architectures and operating system agnostic deployment of applications on IoT gateways. This paper discusses the architectural aspects of containerization, and studies the suitability of available containerization tools for multi-container deployment in the context of IoT gateways. We present containerization in the context of AGILE, a multi-container and micro-service based open source framework for IoT gateways, developed as part of a Horizon 2020 project. Our study of containerized services to perform common gateway functions like device discovery, data management and cloud integration among others, reveal the advantages of having a containerized environment for IoT gateways with regard to use of base image hierarchies and image layering for in-container and cross-container performance optimizations. We illustrate these results in a set of benchmark experiments in this paper.
Several articles in existing literature present applications of IoT based on containerization in different use cases. The authors of @cite_11 demonstrate a distributed and layered architecture for Industrial IoT based applications with deployment of docker containers on end devices, the gateway and the cloud. Chesov et. al @cite_6 present a multi-tier approach to containerize different functionalities in the smart cities context like data aggregation, business analytics and user interaction with data and deploy the containers on the cloud. Kovatsch et. al simplify programmability of IoT applications by exposing scripts and configurations using a RESTful CoAP interface from a deployed container @cite_1 .
@cite_1 @cite_6 @cite_11
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Programming Internet of Things (IoT) applications is challenging because developers have to be knowledgeable in various technical domains, from low-power networking, over embedded operating systems, to distributed algorithms. Hence, it will be challenging to find enough experts to provide software for the vast number of expected devices, which must also be scalable and particularly safe due to the connection to the physical world. To remedy this situation, we propose an architecture that provides Web-like scripting for low-end devices through Cloud-based application servers and a consistent, RESTful programming model. Our novel runtime container Actinium (Ac) exposes scripts, their configuration, and their lifecycle management through a fully RESTful programming interface using the Constrained Application Protocol (CoAP). We endow the JavaScript language with an API for direct interaction with mote-class IoT devices, the CoapRequest object, and means to export script data as Web resources. With Actinium, applications can be created by simply mashing up resources provided by CoAP servers on devices, other scripts, and classic Web services. We also discuss security considerations and show the suitability of this architecture in terms of performance with our publicly available implementation. This paper describes the containerization of a multi-tier client-server architecture based on LXC isolation technology for Smart Cities application layer. Multi-tier client-server architecture was used as a single node. Implementation classes and containerization management classes have been designed and implemented in C++. The approach proposed in this paper allowed to create a homogeneous environment in which the control nodes are built using the same technology as the controlled nodes to manage devices in Smart Cities The use of virtualization technologies in different contexts - such as Cloud Environments, Internet of Things (IoT), Software Defined Networking (SDN) - has rapidly increased during the last years. Among these technologies, container-based solutions own characteristics for deploying distributed and lightweight applications. This paper presents a performance evaluation of container technologies on constrained devices, in this case, on Raspberry Pi. The study shows that, overall, the overhead added by containers is negligible. Cloud technology is moving towards multi-cloud environments with the inclusion of various devices. Cloud and IoT integration resulting in so-called edge cloud and fog computing has started. This requires the combination of data centre technologies with much more constrained devices, but still using virtualised solutions to deal with scalability, flexibility and multi-tenancy concerns. Lightweight virtualisation solutions do exist for this architectural setting with smaller, but still virtualised devices to provide application and platform technology as services. Containerisation is a solution component for lightweight virtualisation solution. Containers are furthermore relevant for cloud platform concerns dealt with by Platform-as-a-Service (PaaS) clouds like application packaging and orchestration. We demonstrate an architecture for edge cloud PaaS. For edge clouds, application and service orchestration can help to manage and orchestrate applications through containers. In this way, computation can be brought to the edge of the cloud, rather than data from the Internet-of-Things (IoT) to the cloud. We show that edge cloud requirements such as cost-efficiency, low power consumption, and robustness can be met by implementing container and cluster technology on small single-board devices like Raspberry Pis. This architecture can facilitate applications through distributed multi-cloud platforms built from a range of nodes from data centres to small devices, which we refer to as edge cloud. We illustrate key concepts of an edge cloud PaaS and refer to experimental and conceptual work to make that case.