Interactive digital signage is an important Internet of things application and has been becoming a common type of human-machine interface for multiple users. By integrating with wireless sensor networks, a digital signage system can provide smart features and on-demand contents to users. However, the performance of current interactive digital signage systems depends heavily on the server. An increasingly high number of digital signage clients and sensor devices attached to the system generating a huge amount of traffic flowed to the server may create bottleneck, management and scalability issues at the server, especially in large-scale digital signage systems. In addition, the current system requires application installation and configuration at the client side, thus leading to a high cost and complexity of deployment as well as management. This article proposes and implements a container-based distributed virtual client architecture for interactive digital signage to solve the above issues. In the proposed architecture, a number of digital signage clients and Internet of things devices are virtualized and managed by a container-based middleware. Each container-based middleware is responsible to manage and process data for a cluster of digital signage clients and corresponding Internet of things devices to (1) reduce load to server and improve the service performance and (2) enable lightweight clients to reduce cost and complexity in deployment as well as management. Implementation and obtained analysis results show the advantages of the proposed architecture.

For many vertical Internet of Things (IoT) applications, the high availability is very important. In traditional cloud systems, services are usually implemented with the same level of availability in which the fault detection and fault recovery mechanisms are not aware of service characteristics. In IoT-cloud, various services are provided with different service characteristics and availability requirements. Therefore, the existing cloud system is inefficient to optimize the availability method and resources to meet service requirements. To address this issue, this paper proposes a high availability architecture that is capable of dynamically optimizing the availability method based on service characteristics. The proposed architecture was verified through an implementation system based on OpenStack, and it was demonstrated that the system was able to achieve the target availability while optimizing resources, in contrast with existing architectures that use predefined availability methods.

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The container-based cloud is used in various service infrastructures as it is lighter and more portable than a virtual machine (VM)-based infrastructure and is configurable in both bare-metal and VM environments. The Internet-of-Things (IoT) cloud-computing infrastructure is also evolving from a VM-based to a container-based infrastructure. In IoT clouds, the service availability of the cloud infrastructure is more important for mission-critical IoT services, such as real-time health monitoring, vehicle-to-vehicle (V2V) communication, and industrial IoT, than for general computing services. However, in the container environment that runs on a VM, the current fault detection method only considers the container’s infra, thus limiting the level of availability necessary for the performance of mission-critical IoT cloud services. Therefore, in a container environment running on a VM, fault detection and recovery methods that consider both the VM and container levels are necessary. In this study, we analyze the fault-detection architecture in a container environment and designed and implemented a Fast Fault Detection Manager (FFDM) architecture using OpenStack and Kubernetes for realizing fast fault detection. Through performance measurements, we verified that the FFDM can improve the fault detection time by more than three times over the existing method.

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