Volumen 43 (2018): Heft 2 (June 2018)

This paper addresses the issue of selecting a suitable location for a fire station in canton of Fribourg, as a result of a fire brigades’ merger, by applying Multiple Criteria Decision Analysis (MCDA) methods. Solving the problem of determining fire station locations through various methods has been analyzed in-depth by researchers. However, a different approach, based on application of ELECTRE I and ELECTRE II methods is advanced in this paper. The selection of the most suitable fire station site is obtained by applying the designated methods to five distinctive alternatives (called scenarios), taking into consideration the relatively limited information and specifics, and the extensive number of relevant criteria that summed up to sixty-one. Taking the merger of the three local fire departments as an example, the proposed methods for selecting a suitable location for the fire station demonstrate and justify the reason behind this choice. Research shows that the applied methods have been proven to be useful and powerful tools that exhibited acceptable levels of consistency when selecting the best project. The main finding is that one scenario in particular proved to be preferred over the others and most suitable in determining the fire station location.

Many fields of modern science rely more and more on the immense computing power of supercomputers. Modern, multi-thousand node systems can consume megawatts of electrical energy in highly uneven manner, challenging the data center infrastructure, both power and cooling coils. The traditional way of managing the infrastructure makes each subsystem of a data center (e.g. cooling) independent from all other in the way it relies only on local sensors to manage the infrastructure. The erratic nature of computing in a large data center makes this approach suboptimal. In the paper we show that by challenging the traditional split between the infrastructure and the computing equipment, one can gain significant boost in energy efficiency of the entire ecosystem. A solution that predicts cooling power demand basing on the information from a supercomputer resource manager, and then sets up the parameters of the cooling loop, is presented along with potential benefits in terms of reduction of the power draw.

Reliability is one of the bigest challenges faced by service-oriented systems. Therefore, to solve this problem, we have proposed ReServE - Reliable Service Environment. ReServE increases fault-tolerance of SOA systems and ensures consistent processing despite failures. However, the proposed environment imposes also the performance overhead. Thus, in this paper, we extended ReServE and added a monitoring feature provided by the M³ service. As a consequence, the extended environment can adjust appropriately the load of its modules to the changing interaction and behaviour patterns of service oriented systems. We have experimentally shown that the proposed solution, while providing the required level of reliability, decreases significantly the performance overhead.

Today, many efforts have been made to implement information systems for supporting research evaluation activities. To produce a good framework for research evaluation, the selection of appropriate measures is important. Quality aspects of the systems’ implementation should also not be overlooked. Incomplete or faulty data should not be used and metric computation formulas should be discussed and valid. Correctly integrated data from different information sources provide a complete picture of the scientific activity of an institution. Knowledge from the data integration field can be adapted in research information management. In this paper, we propose a research information system for bibliometric indicator analysis that is incorporated into the adaptive integration architecture based on ideas from the data warehousing framework for change support. A data model of the integrated dataset is also presented. This paper also provides a change management solution as a part of the data integration framework to keep the data integration process up to date. This framework is applied for the implementation of a publication data integration system for excellence-based research analysis at the University of Latvia.