In distributed systems, where several deployments of a specific service exist, it is a crucial task to select and combine concrete deployments to build an executable workflow. Non-functional properties such as performance and availability are taken into account in such selection processes that are designed to reach certain objectives while meeting constraints. In this paper, a concrete data-intensive application scenario from a High-Energy Physics experiment comprising a deployment selection challenge is introduced. A generic model for distributed systems is presented based on which a formal model representing the individual components of the system is derived. The optimization problem is approached both from the angle of the user and the angle of the system provider. Moreover the dynamic aspects of the underlying system are taken into account. This results in a dynamic multi-objective optimization problem for which an explicit memory-based genetic algorithm is proposed.
Peer review is used as an effective quality assurance measure in many contexts, including science, business, programming or education. In education, several studies confirmed the positive effects of peer reviewing on student learning. Based on recent research concerning the role of media in the peer review process this study investigates how students perceive the process, content and effects of peer reviews. We also analyze students' opinions on different modes of peer reviewing activities, e.g. online vs. faceto-face reviewing. In the context of a computer science course on scientific writing, these research questions were addressed by administering an online questionnaire (n=38) and analysis using quantitative and qualitative methods. Results indicate that students value the peer review activity, take peer reviews seriously and provide comprehensive and constructive reviews. Findings also show that students prefer written online reviews with the possibility of oral follow-up questions to reviewers.
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