Anmerkungen:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Beschreibung:
The use of virtualisation allows to share physical resources in a data centre among multiple tenants in parallel. Cloud Computing became the de facto standard in modern data centre management. Yet, resource interferences and non-ideal placement decisions can hinder an equally distributed and fair shared data centre utilisation for the participants, the data centre provider and the customers. Related work is improving virtualisation and isolation, works on resource management in data centres, addresses green computing aspects to improve the ecological aspects of data centres, reviews and improves data centre monitoring, and works on time series analysis. The popular data centre management modes are Cloud Computing or High Performance Computing. Both have in common to consist of a centralised management component, which schedules and allocates resources, based on static criteria. A dynamic resource allocation is more complex and expensive, since utilisation-aware scheduling requires monitoring and processing to express resource demands as profiles to resource management components. This thesis presents solutions for the monitoring and profiling, to build a distributed dynamic resource allocation for large-scale data centres. The designed and implemented distributed monitoring for virtualised nodes in shared data centres works cross-layer while being non-intrusive, elastic and robust. The DisResc Monitoring proposed here considers static and dynamic metrics of physical and virtual layer with multi-tenancy awareness, and introduces a flexible and scalable communication model. The DisResc communication uses a distributed message bus with publish-subscribe, to allow fully distributed, hierarchical, or centralised setups. The kvmtop collector, as proof of concept implementation, transmits comprehensive static and dynamic metrics for virtual machines on KVM hypervisors, including runtime overhead and with awareness of overbooking. The evaluation shows that this black box monitoring approach produces accurate ...