Grid Global Behavior Prediction

Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach

Novel connection between newborn granule neurons and the hippocampal CA2 field

© 2014 Elsevier Inc. Newborn neurons are continuously added to the hippocampal dentate gyrus (DG) throughout life. Mature and immature granule neurons are believed to send their axonal projections exclusively to the hippocampal CA3 field. However, recent data point to an alternative trisynaptic circuit, involving a direct axonal projection from mature granule neurons to the CA2 field. Whether this circuit takes place only in mature granule neurons or, on the contrary, whether immature granule neurons also contribute to this novel connection is unknown. We used various retroviral vectors to show that immature granule neurons send axonal processes to and establish synaptic contacts with CA2 pyramidal neurons and that axonal growth follows a similar time course to that described for CA3 innervation. In addition, we provide experimental evidence demonstrating that the pathway connecting newborn granule neurons and the CA2 field can be modulated by physiological and deleterious stimuli.Spanish Ministry of Health (SAF 2006-02424, BFU-2008-03980, BFU-2010-21507), the Comunidad de Madrid (SAL/0202/2006), the Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, ISCIII) (CB401), and the Fundación R. ArecesPeer Reviewe

Using Global Behavior Modeling to Improve QoS in Cloud Data Storage Services

The cloud computing model aims to make large-scale data-intensive computing affordable even for users with limited financial resources, that cannot invest into expensive infrastructures necesssary to run them. In this context, MapReduce is emerging as a highly scalable programming paradigm that enables high-throughput data-intensive processing as a cloud service. Its performance is highly dependent on the underlying storage service, responsible to efficiently support massively parallel data accesses by guaranteeing a high throughput under heavy access concurrency. In this context, quality of service plays a crucial role: the storage service needs to sustain a stable throughput for each individual accesss, in addition to achieving a high aggregated throughput under concurrency. In this paper we propose a technique to address this problem using component monitoring, application-side feedback and behavior pattern analysis to automatically infer useful knowledge about the causes of poor quality of service and provide an easy way to reason in about potential improvements. We apply our proposal to Blob Seer, a representative data storage service specifically designed to achieve high aggregated throughputs and show through extensive experimentation substantial improvements in the stability of individual data read accesses under MapReduce workloads

GMonE: a complete approach to cloud monitoring

The inherent complexity of modern cloud infrastructures has created the need for innovative monitoring approaches, as state-of-the-art solutions used for other large-scale environments do not address specific cloud features. Although cloud monitoring is nowadays an active research field, a comprehensive study covering all its aspects has not been presented yet. This paper provides a deep insight into cloud monitoring. It proposes a unified cloud monitoring taxonomy, based on which it defines a layered cloud monitoring architecture. To illustrate it, we have implemented GMonE, a general-purpose cloud monitoring tool which covers all aspects of cloud monitoring by specifically addressing the needs of modern cloud infrastructures. Furthermore, we have evaluated the performance, scalability and overhead of GMonE with Yahoo Cloud Serving Benchmark (YCSB), by using the OpenNebula cloud middleware on the Grid’5000 experimental testbed. The results of this evaluation demonstrate the benefits of our approach, surpassing the monitoring performance and capabilities of cloud monitoring alternatives such as those present in state-of-the-art systems such as Amazon EC2 and OpenNebula

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations

Direct Evidence of Internalization of Tau by Microglia in Vitro and in Vivo

The microtubule-associated protein (MAP) tau plays a critical role in the pathogenesis of tauopathies. Excess tau can be released into the extracellular medium in a physiological or pathological manner to be internalized by surrounding neurons' a process that contributes to the spread of this protein throughout the brain. Such spreading may correlate with the progression of the abovementioned diseases. In addition to neurons, tau can be internalized into other cells. Here we demonstrate that microglia take up tau in vitro and in vivo. In this regard, microglia from primary cultures internalized soluble (human recombinant tau42) and insoluble (homogenates derived from human AD brain) tau in vitro. Furthermore, using stereotaxic injection of tau in mice in vivo, we show that murine microglia internalize human tau. In addition, we demonstrate, for the first time, that microglia colocalize with various forms of tau in postmortem brain tissue of patients with Alzheimer's disease and non-demented control subjects. Our data reveal a potential role of microglia in the internalization of tau that might be relevant for the design of strategies to enhance the clearance of extracellular tau in neurodegenerative diseases characterized by the accumulation of this protein.Spanish Ministry of Health, the Comunidad de Madrid, the Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED, ISCIII), and the Alzheimer’s Association.Peer Reviewe