Abstract — For service management systems the early recog-nition of situations that necessitate a rebinding or a migration of services is an important task. To describe these situations on differing levels of detail and to allow their recognition even if only incomplete information is available, we employ the ontology language OWL 2 and the reasoning services defined for it. In this paper we provide a case study on the performance of state of the art OWL 2 reasoning systems for answering class queries and conjunctive queries modeling the relevant situations for service rebinding or migration in the differing OWL 2 profiles. I.

Abstract—The adoption of server virtualization and cloud computing has enabled high flexibility of service execution in the Internet. It also promises the efficient use of resources including power. At present, the cloud infrastructure (physical machines and cloud platforms) and the services employing the infrastructure are managed by independent entities. As a result, it is difficult to jointly configure hardware and software resources, which may introduce significant inefficiency of resource utilization. Often infrastructure providers over provision resources to accommodate a growing demand, but the cost of such inefficiency is gradually being felt by both parties. This paper experimentally examines the effect of system configuration (concurrency) on the power consumption and latency of a video hosting server. We find that the usefulness of concurrency is greatly influenced by the interplay of underlying leased resources and by the interaction of virtual machines with these resources. However, the exact nature of this interplay is difficult to quantitatively establish and, therefore, it is not presented to service providers. Our study encourages the scientific community to pay attention to this aspect and to undertake a more rigorous investigation based on practical observations. Index Terms—Concurrency, parallel programs, power consumption, server power consumption, processor power consumption, virtual machines, latency, performance, virtualized environment I.