EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX

With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling.

SDN-based dynamic resource management and scheduling for cognitive industrial IoT

PurposeIn recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.Design/methodology/approachIn this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.FindingsThe result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.Originality/valueThe authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.

Dynamic Resource Management in High Throughput Satellite with Multi Port Amplifier (MPA)

The demand for data capacity has been growing, especially in the aviation and maritime industries and is expected to continue to grow in the foreseeable future. The satellite industry is moving to High Throughput Satellite (HTS) that are characterized by large numbers of small spot beams, frequency reuse, higher Equivalent Isotropically Radiated Power (EIRP) and higher Gain to Noise Temperature (G/T) to meet growing capacity demand. Multi-Port Amplifiers (MPA) increase the flexibility of HTS systems by allowing capacity to be allocated dynamically based on changing demand. This will allow capacity requirements to be planned based on the sum of the requirements across all beams rather than the peaks in each HTS beam. The authors propose a ground based solution that will maximize resource utilization of an HTS with an MPA and deliver the capacity dynamically based on demand. Maritime, commercial aviation, satellite based cellular backhaul, and disaster recovery services are the main applications that can benefit from the solution they propose. The authors' results show significant reduction in the overall capacity requirements because of the more efficient utilization of the satellite resources.