Model-driven development of data intensive applications over cloud resources

The proliferation of sensors over the last years has generated large amounts of raw data, forming data streams that need to be processed. In many cases, cloud resources are used for such processing, exploiting their flexibility, but these sensor streaming applications often need to support operational and control actions that have real-time and low-latency requirements that go beyond the cost effective and flexible solutions supported by existing cloud frameworks, such as Apache Kafka, Apache Spark Streaming, or Map-Reduce Streams. In this paper, we describe a model-driven and stepwise refinement methodological approach for streaming applications executed over clouds. The central role is assigned to a set of Petri Net models for specifying functional and non-functional requirements. They support model reuse, and a way to combine formal analysis, simulation, and approximate computation of minimal and maximal boundaries of non-functional requirements when the problem is either mathematically or computationally intractable. We show how our proposal can assist developers in their design and implementation decisions from a performance perspective. Our methodology allows to conduct performance analysis: The methodology is intended for all the engineering process stages, and we can (i) analyse how it can be mapped onto cloud resources, and (ii) obtain key performance indicators, including throughput or economic cost, so that developers are assisted in their development tasks and in their decision taking. In order to illustrate our approach, we make use of the pipelined wavefront array

Undetected displacement of a subcutaneous implantable cardioverter-defibrillator lead

Background: In recent years, subcutaneous implantable cardioverter-defibrillator (S-ICD) implants have progressively increased and have been shown to be safe and highly successful, affording low reintervention rates regardless of the technique used. Case summary: We present a case of S-ICD implantation in a patient diagnosed with idiopathic ventricular fibrillation. In the first follow-up consultation the patient showed appropriate detection parameters in the three configurations. However, chest X-ray revealed lead displacement with a tip migration from the manubrium area of the sternum to the xiphoid process. Discussion: This case highlights the importance of performing at least one chest X-ray during the first weeks after S-ICD implantation, allowing the detection of a problem such as lead displacement, which can lead to undersensing of ventricular arrhythmias or S-ICD oversensing

A Specification Language for Performance and Economical Analysis of Short Term Data Intensive Energy Management Services

Requirements of Energy Management Services include short and long term processing of data in a massively interconnected scenario. The complexity and variety of short term applications needs methodologies that allow designers to reason about the models taking into account functional and non-functional requirements. In this paper we present a component based specification language for building trustworthy continuous dataflow applications. Component behaviour is defined by Petri Nets in order to translate to the methodology all the advantages derived from a mathematically based executable model to support analysis, verification, simulation and performance evaluation. The paper illustrates how to model and reason with specifications of advanced dataflow abstractions such as smart grids

Pluviometric regionalization of Catalunya: a compositional data methodology

The aim of this paper is to introduce a methodology for de¯ning groups from regionalized com- positional data, through a hierarchical clustering algorithm aware of both the spatial dependence and the compositional character of the data set. This method is used to de¯ne a regionalization of Catalunya (NE Spain) with respect to its precipitation patterns in the Winter season. This region is characterized by a highly contrasted topography, which plays a dominant role in the spatial distribution of precipitation. Each rain gauge station is characterized by the relative frequencies of occurrence of six intervals of daily precipitation amount (classes ranging from \no rain" for precipitation below 3 mm, to \heavy storm" above 50 mm). Recognizing that frequencies are com-positional data, the spatial dependence of this data set has been characterized by variograms of the set of all pair-wise log-ratios, in the fashion of the variation matrix. Then, a Mahalanobis distance between stations has been de¯ned using these variograms to ensure that gauges with high spatial correlation get smaller distances. This spatially-dependent distance criterion has been used in a Ward hierarhical cluster method to de¯ne the regions. Results reveal 5 quite homogeneous groups of stations, which can be mostly ascribed a physical meaning. Finally, possible links to regional circulation patterns are discussed.Postprint (published version

Principal balances

Principal balances are de ned as a sequence of orthonormal balances which maximize successively the explained variance in a data set. Apparently, computing principal balances requires an exhaustive search along all possible sets of orthogonal balances. This is una ordable for even a small number of parts. Three suboptimal, but feasible, alternatives are explored. The approach is illustrated using a data-set of geochemical composition of glacial sediments

Pluviometric regionalization of Catalunya: a compositional data methodology

The aim of this paper is to introduce a methodology for de¯ning groups from regionalized com- positional data, through a hierarchical clustering algorithm aware of both the spatial dependence and the compositional character of the data set. This method is used to de¯ne a regionalization of Catalunya (NE Spain) with respect to its precipitation patterns in the Winter season. This region is characterized by a highly contrasted topography, which plays a dominant role in the spatial distribution of precipitation. Each rain gauge station is characterized by the relative frequencies of occurrence of six intervals of daily precipitation amount (classes ranging from \no rain" for precipitation below 3 mm, to \heavy storm" above 50 mm). Recognizing that frequencies are com- positional data, the spatial dependence of this data set has been characterized by variograms of the set of all pair-wise log-ratios, in the fashion of the variation matrix. Then, a Mahalanobis distance between stations has been de¯ned using these variograms to ensure that gauges with high spatial correlation get smaller distances. This spatially-dependent distance criterion has been used in a Ward hierarhical cluster method to de¯ne the regions. Results reveal 5 quite homogeneous groups of stations, which can be mostly ascribed a physical meaning. Finally, possible links to regional circulation patterns are discussed

Principal balances

Principal balances are defined as a sequence of orthonormal balances which maximize successively the explained variance in a data set. Apparently, computing principal balances requires an exhaustive search along all possible sets of orthogonal balances. This is unaffordable for even a small number of parts. Three suboptimal, but feasible, alternatives are explored. The approach is illustrated using a data-set of geochemical composition of glacial sediments.Peer ReviewedPostprint (published version

Enforcing QoS in scientific workflow systems enacted over Cloud infrastructures

AbstractThe ability to support Quality of Service (QoS) constraints is an important requirement in some scientific applications. With the increasing use of Cloud computing infrastructures, where access to resources is shared, dynamic and provisioned on-demand, identifying how QoS constraints can be supported becomes an important challenge. However, access to dedicated resources is often not possible in existing Cloud deployments and limited QoS guarantees are provided by many commercial providers (often restricted to error rate and availability, rather than particular QoS metrics such as latency or access time). We propose a workflow system architecture which enforces QoS for the simultaneous execution of multiple scientific workflows over a shared infrastructure (such as a Cloud environment). Our approach involves multiple pipeline workflow instances, with each instance having its own QoS requirements. These workflows are composed of a number of stages, with each stage being mapped to one or more physical resources. A stage involves a combination of data access, computation and data transfer capability. A token bucket-based data throttling framework is embedded into the workflow system architecture. Each workflow instance stage regulates the amount of data that is injected into the shared resources, allowing for bursts of data to be injected while at the same time providing isolation of workflow streams. We demonstrate our approach by using the Montage workflow, and develop a Reference net model of the workflow

Un Drame en Livonie et l´Affaire Dreyfus, faux-semblant et réalité

Un Drame en Livonie et l’Affaire Dreyfus : faux-semblant et réalité D'une part, une histoire réelle qui marqua la société française de l’époque: l’Affaire Dreyfus. D'autre part, une création littéraire, notamment le premier roman policier de Jules Verne, Un drame en Livonie. Apparemment fort éloignés l'un de l'autre, le fait historique et le roman s’entrecroisent de données, cibles de notre analyse, qui semblent être dans certains aspects des copies conformes. Certes, le roman, paru en 1904, semble être influencé directement du fait divers qui touche la société française de l'époque. Cependant, Jules Verne l'aurait composé avant août 1894, mais l'importance croissante de l'Affaire a mené l'auteur à ne point faire paraître son drame. C'est pourquoi il devient nécessaire de nous demander si Un drame en Livonie serait, comme certains le prétendent, un roman influencé directement par ce fait divers si touchant, s’il aurait été écrit avant ou simultanément au fait historique en question et que, Jules Verne, en vue du déroulement des événements et le sort infligé à certains intellectuels, aurait décidé de retarder sa date de parution, ou, si au contraire, comme bon visionnaire qu’il a toujours été, il aurait su voir l’Affaire Dreyfus bien avant son éclosion et Un drame en Livonie serait la preuve de cette prémonition . En effet, nous assistons à l’affrontement de deux Frances et de deux Livonies, à une lutte acharnée, dans ces pays, entre les mêmes forces, les unes employant toutes les arguties pour garder leurs privilèges et leur pouvoir, les autres, se sentant prêtes et préparées, se battant, avec d’humbles moyens, pour reconquérir leurs droits légitimes. Entre ces deux Frances et ces deux Livonies, imprégnées de morales politiques distinctes et de valeurs humaines opposées, les contrastes sont si évidents que nous n’avons aucun mal à déceler les hommes de bien et les hommes de mal, les dignes représentants de l’honnêteté et ceux de la perversité. Nous sommes témoins d'une forte haine raciale entre Slaves et Germaniques, et d'une croissante haine religieuse en France, contre les Juifs. Nous percevons encore la presse rallumer le feu de blessures mi- éteintes, fomenter et animer les bagarres entre Français et Livoniens, prêcher un antisémitisme odieux. Enfin, nous sentons surtout la présence de deux êtres humains accusés à tort, incapables, à eux seuls, de démonter cette toile d’araignée qui les cerne et de démontrer leur innocence, incapables de comprendre la raison de cette erreur, de saisir l’acharnement avec lequel le pouvoir agit contre eux, de réaliser pourquoi la foule les insulte et les condamne alors qu’ils n’ont même pas été jugés ; nous les voyons impuissants et désarmés face à ces forces sociales, la justice, l’armée, la police, le pouvoir, capables de commettre des crimes d’État pour cacher leur incompétence et nourrir leur ego personnel