Abstract
The recent increase in the number of Internet of Things (IoT) devices has led to the generation of a large amount of data. These data are generally processed by cloud servers because of their high scalability and ability to provide resources on demand. However, processing large amounts of data in the cloud is an impractical solution for the strict requirements of IoT services, such as low latency and high bandwidth. Fog computing, which brings computational resources closer to the IoT devices, has emerged as a suitable solution to mitigate these problems. Resource provisioning and application orchestration are two of the key challenges when running IoT applications in a Fog computing environment. In this article, we present ElasticFog, which runs on top of the Kubernetes platform and enables real-time elastic resource provisioning for containerized applications in Fog computing. Specifically, ElasticFog collects network traffic information in real time and allocates computational resources proportionally to the distribution of network traffic. The experimental results prove that ElasticFog achieves a significant improvement in terms of throughput and network latency compared with the default mechanism in Kubernetes.
Highlights
The concept of the Internetof things (IoT), which connects smart devices to each other through the Internet, has become popular over the past few years
We proposed a real-time elastic resource provisioning for applications in container-based Fog computing
ElasticFog is implemented based on the Kubernetes platform, and it collects the network traffic status to provide elastic resource provisioning of the application among geographically distributed Fog nodes in real time
Summary
The concept of the Internetof things (IoT), which connects smart devices to each other through the Internet, has become popular over the past few years. The mechanism is expected to minimize network latency as well as avoid resource wastage in locations with low workload demand To enable this feature, ElasticFog is deployed on top of the Kubernetes platform to collect real-time information regarding network traffic at each Fog node and attempt to allocate resources effectively. The aforementioned studies resolve some challenges in resource provisioning and application orchestration in Fog computing, they have not yet provided a complete solution for the real-time management of application resources based on network traffic information. By leveraging powerful and flexible features of Kubernetes and real-time network traffic from clients accessing the Fog nodes, our proposed approach can effectively allocate and reallocate IoT application resources to adapt to the changes in demands on the application in the Fog computing environment. The scheduling decision is based on the ‘‘hard’’ requirements (e.g., CPU and RAM) in the pod’s configuration and diverse ‘‘soft’’ requirements (e.g., spreading the pods and balanced resource allocation) to find the best fit node for the pod to run on
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