DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling

The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches.Comment: Submitted to Springer Computin

The cytochrome chain of mitochondria exhibits variable H+/e− stoichiometry

AbstractA study is presented of the ←H+/e− stoichiometry for H+ pumping by the cytochrome chain in isolated rat liver mitochondria under level-flow and steady-state conditions. It is shown that the ←H+/e− stoichiometry for the cytochrome chain varies under the influence of the flow rate and transmembrane ΔμH+. The rate-dependence is shown to be associated with cytochrome c oxidase, whose ←H+/e− ratio varies from 0 to 1, whilst the ←H+/c− ratio for the span covered by cytochrome c reductase is invariably 2

The human coronaviruses (HCoVs) and the molecular mechanisms of SARS-CoV-2 infection

In humans, coronaviruses can cause infections of the respiratory system, with damage of varying severity depending on the virus examined: ranging from mild-to-moderate upper respiratory tract diseases, such as the common cold, pneumonia, severe acute respiratory syndrome, kidney failure, and even death. Human coronaviruses known to date, common throughout the world, are seven. The most common-and least harmful-ones were discovered in the 1960s and cause a common cold. Others, more dangerous, identified in the early 2000s and cause more severe respiratory tract infections. Among these the SARS-CoV, isolated in 2003 and responsible for the severe acute respiratory syndrome (the so-called SARS), which appeared in China in November 2002, the coronavirus 2012 (2012-nCoV) cause of the Middle Eastern respiratory syndrome (MERS) from coronavirus, which exploded in June 2012 in Saudi Arabia, and actually SARS-CoV-2. On December 31, 2019, a new coronavirus strain was reported in Wuhan, China, identified as a new coronavirus beta strain ß-CoV from group 2B, with a genetic similarity of approximately 70% to SARS-CoV, the virus responsible of SARS. In the first half of February, the International Committee on Taxonomy of Viruses (ICTV), in charge of the designation and naming of the viruses (i.e., species, genus, family, etc.), thus definitively named the new coronavirus as SARS-CoV-2. This article highlights the main knowledge we have about the biomolecular and pathophysiologic mechanisms of SARS-CoV-2

Informatics Higher Education in Europe: A Data Portal and Case Study

A discussion on the need for coordinated, governed, data-driven computing education initiatives of the future

A UML Profile for the Design, Quality Assessment and Deployment of Data-intensive Applications

Big Data or Data-Intensive applications (DIAs) seek to mine, manipulate, extract or otherwise exploit the potential intelligence hidden behind Big Data. However, several practitioner surveys remark that DIAs potential is still untapped because of very difficult and costly design, quality assessment and continuous refinement. To address the above shortcoming, we propose the use of a UML domain-specific modeling language or profile specifically tailored to support the design, assessment and continuous deployment of DIAs. This article illustrates our DIA-specific profile and outlines its usage in the context of DIA performance engineering and deployment. For DIA performance engineering, we rely on the Apache Hadoop technology, while for DIA deployment, we leverage the TOSCA language. We conclude that the proposed profile offers a powerful language for data-intensive software and systems modeling, quality evaluation and automated deployment of DIAs on private or public clouds

Model based control for multi-cloud applications

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Fate of the predictions in Galle-Unawatuna mangroves, Sri Lanka: A validation after 10 years using satellite (IKONOS) and ground-truth data

Validation of earlier predictions is a challenging but significant contribution to ecological research. The present study tests the predications made 10 years ago by Dahdouh-Guebas et al. (2000) on the evolution of mangrove forest in Galle-Unawatuna, Sri Lanka. The ground inventory carried out in five Sectors covering the entire forest (Point Centred Quarter Method - PCQM) (Cintron and Schaeffer Novelli, 1984) revealed that the adult species composition is dominated by Rhizophora apiculata, Excoecaria agallocha, Bruguiera gymnorrhiza and B. sexangula, with their total density of 216-267 stems 0.1ha-1 and basal area 1.19-1.44m2 0.1ha-1. However, both young and juvenile vegetation in the most Sectors was dominated solely by B. gymnorrhiza (128-869 stems and 356-1482 propagules 0.1ha-1). According to Dahdouh-Guebas et al. (2000), the transition of an E. agallocha forest into a B. gymnorrhiza dominated one or at least their co-dominance in the Sectors 1 and 2 is possible, whereas Sector 3 being dominated by adult and juvenile R. apiculata will persist. Overall, the possible transition to a Bruguiera dominated forest in Galle-Unawatuna area was forecasted. The recent decadal changes between 1994 and 2004 through the integration of IKONOS satellite imagery of 2004 with ground-truth information confirmed many of the predictions and showed dynamic shifts in young/adult vegetation by B. gymnorrhiza. Both E. agallocha and R. apiculata continue to be dominant in Sectors 2 and 3, although the adult turnover by B. gymnorrhiza has not yet occurred, probably due to the small time interval between the two investigations. Confirming in part with the earlier prediction on R. apiculata in Sector 3, present study also revealed the abundance of B. gymnorrhiza as young and juvenile vegetation. Viewing the present dynamic shifts and sheer dominance as young vegetation by B. gymnorrhiza with a mean height of 5.8m in most Sectors, it is still possible to anticipate the mangroves being dominated by this species, and actually now validates the predictions made 10 years ago. Because of apparent changes in the mangrove vegetation structure, it could be concluded that the ‘moving mosaic’ pattern of mangrove species distribution reported earlier for Galle-Unawatuna still persists

The break-up of Ekman theory in a flow subjected to background rotation and driven by a non-conservative body force

We present an experimental/numerical study of a dipolar flow structure in a shallow layer of electrolyte driven by electromagnetic forcing and subjected to background rotation. The aim of this study is to determine the influence of a non-conservative body force on the range of applicability of the classical Ekman boundary layer theory in rapidly rotating systems. To address this question, we study the response of the flow to the three control parameters: the magnitude of the forcing, the rotation rate of the system, and the shallowness of the layer. This response is quantified taking into account the magnitude of the flow velocity (represented by the Reynolds number), the symmetry between both vortex cores, and the vertical profile of the horizontal velocity. As in the case without background rotation, the response of the flow exhibits two scaling regimes (a linear and a nonlinear regime) in which the flow exhibits different vertical profiles of velocity. The transition between the two regimes occurs when the convective acceleration becomes of the same order as the viscous damping. This suggests that the applicability of the Ekman theory depends on the existence of a balance between the forcing and the damping due to the Ekman layers and does not depend solely on the value of the Rossby number as for decaying flows. On the other hand, the cyclone/anticyclone asymmetry is governed exclusively by the Rossby number. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4766818

A constraint-based approach to quality assurance in service choreographies.

Knowledge about the quality characteristics (QoS) of service com- positions is crucial for determining their usability and economic value. Ser- vice quality is usually regulated using Service Level Agreements (SLA). While end-to-end SLAs are well suited for request-reply interactions, more complex, decentralized, multiparticipant compositions (service choreographies) typ- ically involve multiple message exchanges between stateful parties and the corresponding SLAs thus encompass several cooperating parties with interde- pendent QoS. The usual approaches to determining QoS ranges structurally (which are by construction easily composable) are not applicable in this sce- nario. Additionally, the intervening SLAs may depend on the exchanged data. We present an approach to data-aware QoS assurance in choreographies through the automatic derivation of composable QoS models from partici- pant descriptions. Such models are based on a message typing system with size constraints and are derived using abstract interpretation. The models ob- tained have multiple uses including run-time prediction, adaptive participant selection, or design-time compliance checking. We also present an experimen- tal evaluation and discuss the benefits of the proposed approach