Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Two divergent ways to manage HR and to get to the top: an exploratory study in micro firms

Aim of the paper: The purpose of this paper is to examine human resources management practices (HRM practices) in small firms and to improve the understanding of the relationship between this kind of practices and business growth. This exploratory study is based on the resource-based view of the firm and empirical work carried out in two small firms by relating HRM practices with the firms’ results. Contribution to the literature: This is an in-depth study of HRM practices and its impact on performance growth in micro firms, isolating and controlling for most of the contextual and internal variables considered in the literature that relate HRM to growth. Firm growth analysis was broadened by the use of several dependent variables: employment growth and operational and financial performance growth. Some hypotheses for further research in identifying HRM practices in small business and its relation with firm growth are suggested. Methodology: Case study methodology was used to study two firms. The techniques used to collect data were semi-structured interviews to the owner and all the employees, unstructured observation at the firms’ facilities (during two days), entrepreneur profile definition (survey answer) and document data collection (on demographic characterization and performance results). Data was analyzed through content analysis methodology, and categories derived from the interviews’ protocols and literature. Results and implications: Results revealed that despite the firms’ organizational characteristics similarities, they differ significantly in owners’ motivation to grow, HRM practices and organizational performance and growth. Future studies should pay special attention to owner willingness to grow, to firms’ years of experience in business, to staff’s years of experience in their field of work and turnover. HRM practices in micro/small firms should be better defined and characterized. The external image of management posture relating to longitudinal financial results and growth should also be explored.