Search Results (3)

In the past twenty years, the IT industry has moved away from using physical servers for workload management to workloads consolidated via virtualization and, in the next iteration, further consolidated into containers. Later, container workloads based on Docker and Podman were orchestrated via Kubernetes or OpenShift. On the other hand, high-performance computing (HPC) environments have been lagging in this process, as much work is still needed to figure out how to apply containerization platforms for HPC. Containers have many advantages, as they tend to have less overhead while providing flexibility, modularity, and maintenance benefits. This makes them well-suited for tasks requiring a lot of computing power that are latency- or bandwidth-sensitive. But they are complex to manage, and many daily operations are based on command-line procedures that take years to master. This paper proposes a different architecture based on seamless hardware integration and a user-friendly UI (User Interface). It also offers dynamic workload placement based on real-time performance analysis and prediction and Machine Learning-based scheduling. This solves a prevalent issue in Kubernetes: the suboptimal placement of workloads without needing individual workload schedulers, as they are challenging to write and require much time to debug and test properly. It also enables us to focus on one of the key HPC issues—energy efficiency. Furthermore, the application we developed that implements this architecture helps with the Kubernetes installation process, which is fully automated, no matter which hardware platform we use—x86, ARM, and soon, RISC-V. The results we achieved using this architecture and application are very promising in two areas—the speed of workload scheduling and workload placement on a correct node. This also enables us to focus on one of the key HPC issues—energy efficiency. Full article

Background: The concept of Hyperconnected Megacity Parcel Logistics (HMPL) was introduced in 2018 and aims to enhance the efficiency, responsiveness, resilience, and sustainability of parcel movements in megacities. However, evaluating such fundamental solutions presents challenges and requires a comprehensive understanding of all stakeholders and decisions involved. Methods: This study introduces a discrete-event agent-based simulation platform that encompasses critical stakeholders and addresses various levels of decision-making. This platform provides an opportunity to evaluate key decisions within an HMPL structure. Results: To demonstrate the capability of the simulator, we assess the impact of package routing and consolidation strategies facilitated by HMPL compared to traditional practices. Preliminary findings suggest that increased interconnection among nodes in HMPL reduces transit times, thereby enabling tighter customer delivery services. However, examining different consolidation heuristics reveals potential trade-offs between handling and shipping costs under fixed shipment schedules, prompting further investigation into dynamic shipment services. Conclusions: The findings of this study suggest that the benefits of innovative approaches in a complex environment, such as parcel logistics, cannot be evaluated in isolation from other decisions. Accurate assessment of the ultimate outcomes and underlying trade-offs requires multi-faceted models that incorporate all key variables. Full article

The virtualization technology has a great potential to improve the manageability and scalability of industrial control systems, as it can host and consolidate computing resources very efficiently. There accordingly have been efforts to utilize the virtualization technology for industrial control systems, but the research for virtualization of traditional industrial real-time networks, such as Controller Area Network (CAN), has been done in a very limited scope. Those traditional fieldbuses have distinguished characteristics from well-studied Ethernet-based networks; thus, it is necessary to study how to support their inherent functions transparently and how to guarantee Quality-of-Service (QoS) in virtualized environments. In this paper, we suggest a lightweight CAN virtualization technology for virtual controllers to tackle both functionality and QoS issues. We particularly target the virtual controllers that are containerized with an operating-system(OS)-based virtualization technology. In the functionality aspect, our virtualization technology provides virtual CAN interfaces and virtual CAN buses at the device driver level. In the QoS perspective, we provide a hierarchical real-time scheduler and a simulator, which enable the adjustment of phase offsets of virtual controllers and tasks. The experiment results show that our CAN virtualization has lower overheads than an existing approach up to 20%. Moreover, we show that the worst-case end-to-end delay could be reduced up to 78.7% by adjusting the phase offsets of virtual controllers and tasks. Full article