A software architecture for the analysis of large sets of data streams in cloud infrastructures

System management algorithms in private andpublic cloud infrastructures have to work with literally thousands of data streams generated from resource, applicationand event monitors. This cloud context opens two novel issuesthat we address in this paper: how to design a softwarearchitecture that is able to gather and analyze all informationwithin real-time constraints; how it is possible to reduce theanalysis of the huge collected data set to the investigationof a reduced set of relevant information. The application ofthe proposed architecture is based on the most advancedsoftware components, and is oriented to the classification of thestatistical behavior of servers and to the analysis of significantstate changes. These results guide model-driven managementsystems to investigate only relevant servers and to applysuitable decision models considering the deter

Real-time adaptive algorithm for resource monitoring

In large scale systems, real-time monitoring of hardware and software resources is a crucial means for any management purpose. In architectures consisting of thousands of servers and hundreds of thousands of component resources, the amount of data monitored at high sampling frequencies represents an overhead on system performance and communication, while reducing sampling may cause quality degradation. We present a real-time adaptive algorithm for scalable data monitoring that is able to adapt the frequency of sampling and data updating for a twofold goal: to minimize computational and communication costs, to guarantee that reduced samples do not affect the accuracy of information about resources. Experiments carried out on heterogeneous data traces referring to synthetic and real environments confirm that the proposed adaptive approach reduces utilization and communication overhead without penalizing the quality of data with respect to existing monitoring algorithms

Adaptive, scalable and reliable monitoring of big data on clouds

Real-time monitoring of cloud resources is crucial for a variety of tasks such as performance analysis, workload management, capacity planning and fault detection. Applications producing big data make the monitoring task very difficult at high sampling frequencies because of high computational and communication overheads in collecting, storing, and managing information. We present an adaptive algorithm for monitoring big data applications that adapts the intervals of sampling and frequency of updates to data characteristics and administrator needs. Adaptivity allows us to limit computational and communication costs and to guarantee high reliability in capturing relevant load changes. Experimental evaluations performed on a large testbed show the ability of the proposed adaptive algorithm to reduce resource utilization and communication overhead of big data monitoring without penalizing the quality of data, and demonstrate our improvements to the state of the art.Real-time monitoring of cloud resources is crucial for a variety of tasks such as performance analysis, workload management, capacity planning and fault detection. Applications producing big data make the monitoring task very difficult at high sampling frequencies because of high computational and communication overheads in collecting, storing, and managing information. We present an adaptive algorithm for monitoring big data applications that adapts the intervals of sampling and frequency of updates to data characteristics and administrator needs. Adaptivity allows us to limit computational and communication costs and to guarantee high reliability in capturing relevant load changes. Experimental evaluations performed on a large testbed show the ability of the proposed adaptive algorithm to reduce resource utilization and communication overhead of big data monitoring without penalizing the quality of data, and demonstrate our improvements to the state of the art

Monitoring large cloud-based systems

Large scale cloud-based services are built upon a multitude of hardware and software resources, disseminated in one or multiple data centers. Controlling and managing these resources requires the integration of several pieces of software that may yield a representative view of the data center status. Today’s both closed and open-source monitoring solutions fail in different ways, including the lack of scalability, scarce representativity of global state conditions, inability in guaranteeing persistence in service delivery, and the impossibility of monitoring multi-tenant applications. In this paper, we present a novel monitoring architecture that addresses the aforementioned issues. It integrates a hierarchical scheme to monitor the resources in a cluster with a distributed hash table (DHT) to broadcast system state information among different monitors. This architecture strives to obtain high scalability, effectiveness and resilience, as well as the possibility of monitoring services spanning across different clusters or even different data centers of the cloud provider. We evaluate the scalability of the proposed architecture through a bottleneck analysis achieved by experimental results

Temperature profile of ex-vivo organs during radio frequency thermal ablation by fiber Bragg gratings.

We report on the integration of fiber optic sensors with commercial medical instrumentation for temperature monitoring during radio frequency ablation for tumor treatment. A suitable configuration with five fiber Bragg grating sensors bonded to a bipolar radio frequency (RF) probe has been developed to monitor the area under treatment. A series of experiments were conducted on ex-vivo animal kidney and liver and the results confirm that we were able to make a multipoint measurement and to develop a real-time temperature profile of the area, with a temperature resolution of 0.1°C and a spatial resolution of 5 mm during a series of different and consecutive RF discharges

Effect of electric current stimulation in combination with external fixator on bone healing in a sheep fracture model

Biophysical stimulations with electric and electromagnetic fields have been demonstrated to accelerate the bone-healing rate. This study has been designed to investigate the effects of electricity directly connected with the central pins of an external fixator in an experimental osteotomy model in sheep. Thirty mg/kg of tetracycline chloride were administered on the 30th and on the 45th day after surgery for histomorphometric studies. Plain radiographs were obtained in standard projections every 15 days after surgery and were analyzed with a software program (Corel Photo-Paint Pro X2, Corel Corporation, Ottawa, Canada). The specimens obtained after 60 days were examined with histological analysis. The results show that biophysical treatment with alternating electricity in combination with external fixator enhances new-bone formation. The translational value of this study, due to the similarities between ovine and human species, suggests that this treatment could be useful in speeding the bone-healing rate both in animals and humans

Flood Protection in Venice under Conditions of Sea-Level Rise: An Analysis of Institutional and Technical Measures

It is widely acknowledged that in times of climate change loss of coastal resources and risk for human life can be minimized by implementing adaptation strategies. Such strategies need to encompass a balanced mix of non-structural (institutional) and structural (technical) measures based on sound scientific knowledge. This article discusses measures carried out to protect the city of Venice, Italy from flooding (locally known as “high water”), and reflects on their ability to anticipate a possible acceleration of sea-level rise as induced by climate change. It is based on scientific literature, legislative and policy documents of key institutions, reports and documents of organizations working on Venice issues, newspaper articles, and interviews. Our analysis shows that the synergic action of the hydraulic defense infrastructure under construction is in principle adequate to withstand a broad range of sea-level rise scenarios for the next 100 years. However, when the goal is to use these investments effectively major changes in the existing institutional arrangements will be required in the years to come. The Venice findings point out the difficulties and yet the importance of identifying and implementing both non-structural and structural measures to adapt to climate change

INCB84344-201: Ponatinib and steroids in frontline therapy for unfit patients with Ph+ acute lymphoblastic leukemia

Tyrosine kinase inhibitors have improved survival for patients with Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukemia (ALL). However, prognosis for old or unfit patients remains poor. In the INCB84344-201 (formerly GIMEMA LAL 1811) prospective, multicenter, phase 2 trial, we tested the efficacy and safety of ponatinib plus prednisone in newly diagnosed patients with Ph+ ALL 6560 years, or unfit for intensive chemotherapy and stem cell transplantation. Forty-four patients received oral ponatinib 45 mg/d for 48 weeks (core phase), with prednisone tapered to 60 mg/m2/d from days-14-29. Prophylactic intrathecal chemotherapy was administered monthly. Median age was 66.5 years (range, 26-85). The primary endpoint (complete hematologic response [CHR] at 24 weeks) was reached in 38/44 patients (86.4%); complete molecular response (CMR) in 18/44 patients (40.9%) at 24 weeks. 61.4% of patients completed the core phase. As of 24 April 2020, median event-free survival was 14.31 months (95% CI 9.30-22.31). Median overall survival and duration of CHR were not reached; median duration of CMR was 11.6 months. Most common treatment-emergent adverse events (TEAEs) were rash (36.4%), asthenia (22.7%), alanine transaminase increase (15.9%), erythema (15.9%), and \u3b3-glutamyltransferase increase (15.9%). Cardiac and vascular TEAEs occurred in 29.5% (grade 653, 18.2%) and 27.3% (grade 653, 15.9%), respectively. Dose reductions, interruptions, and discontinuations due to TEAEs occurred in 43.2%, 43.2%, and 27.3% of patients, respectively; 5 patients had fatal TEAEs. Ponatinib and prednisone showed efficacy in unfit patients with Ph+ ALL; however, a lower ponatinib dose may be more appropriate in this population. This trial was registered at www.clinicaltrials.gov as #NCT01641107

Stability of the Jupiter Southern Polar Vortices Inspected Through Vorticity Using Juno/JIRAM Data

The Jovian InfraRed Auroral Mapper (JIRAM) onboard the NASA Juno mission monitored the evolution of Jupiter’s polar cyclones since their first observation ever in February 2017. Data acquired by JIRAM have revealed cloudy cyclones organized in a complex, yet stable geometrical pattern at both poles. Several studies have investigated the dynamics and the structure of these cyclones, to understand the physical mechanisms behind their formation and evolution. In this work, we present vorticity maps deduced from the wind fields for the region poleward of ∼−80°, which has been extensively covered over the last four years of observations. The cyclonic features related to the stable polar cyclones are embedded in a slightly, but diffused anticyclonic circulation, in which short-living anticyclones emerge with respect to the surroundings. Although the general stability of both the cyclones and the whole system is strongly confirmed by this work, variations in the shape of the vortices, as well as changes in the local structures, have been observed

Five Years of Observations of the Circumpolar Cyclones of Jupiter

The regular polygons of circumpolar cyclones, discovered by Juno in 2017, are one of the most puzzling features of Jupiter. Here we show new recent global pictures of the North polar cyclones' structure. These are the first simultaneous images of the whole structure since 2017, and we find that it remained almost unperturbed, just like the South one. The observation of these long-lasting structures poses questions regarding the formation mechanism of cyclones, and on their vertical structure. Data by Juno/JIRAM infrared camera collected over the last 5 years show that cyclones migrate around what may seem like equilibrium positions, with timescales of a few months but, aside from that, the cyclones systems are very stable. Our analysis of the observations shows that the motion of cyclones around their equilibrium position is uncorrelated with their position if a barotropic approximation (β-drift) is assumed. Thus, a different dynamical explanation than the barotropic β-drift is needed to explain the stability of the observed features. Each cyclone has a peculiar morphology, which differs from the others and is stable over the observed lapse of time in most cases