Essential variables for air quality estimation

Within this survey we describe the conceptual architecture of the infrastructure to measure PM2.5/PM10 concentration in the atmosphere over the Kyiv city using modern monitoring instruments. We define the requirements for information tools and network for informing Kyiv city community on the state of PM pollutions that will be created. This infrastructure will provide long-term PM2.5/PM10 observations that could be included in the AirBase network. The comprehensive review of in-situ and satellite measurements of PM2.5/PM10 is provided as well as the description current state-of-the-art for Air Quality monitoring with intelligent sensors and systems in Ukraine as-awhole and in Kyiv in particular. It is proposed to apply the concept of essential variables (EVs) used in Earth Observation to identify the variables that should be measured in priority when designing, deploying and maintaining observation systems. In this study we use and validate the global air quality products from Copernicus Atmosphere Monitoring Service obtained from modeling by GEOS-Chem model and other sources. The influence of PM and aerosols on a human health is estimated in terms of possible diseases and dangerous concentrations

Kubernetes cluster optimization using hybrid shared-state scheduling framework

This paper presents a novel approach for scheduling the workloads in a Kubernetes cluster, which are sometimes unequally distributed across the environment or deal with fluctuations in terms of resources utilization. Our proposal looks at a hybrid shared-state scheduling framework model that delegates most of the tasks to the distributed scheduling agents and has a scheduling correction function that mainly processes the unscheduled and unprioritized tasks. The scheduling decisions are made based on the entire cluster state which is synchronized and periodically updated by a master-state agent. By preserving the Kubernetes objects and concepts, we analyzed the proposed scheduler behavior under different scenarios, for instance we tested the failover/recovery behavior in a deployed Kubernetes cluster. Moreover, our findings show that in situations like collocation interference or priority preemption, other centralized scheduling frameworks integrated with the Kubernetes system might not perform accordingly due to high latency derived from the calculation of load spreading. In a wider context of the existing scheduling frameworks for container clusters, the distributed models lack of visibility at an upper-level scheduler might generate conflicting job placements. Therefore, our proposed scheduler encompasses the functionality of both centralized and distributed frameworks. By employing a synchronized cluster state, we ensure an optimal scheduling mechanism for the resources utilization.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Network Architectures and Service