scholarly journals TOWARDS A SCALABLE SCIENTIFIC DATA GRID MODEL AND SERVICES

2010 ◽  
Vol 10 (2) ◽  
pp. 97-107
Author(s):  
Azizol Abdullah
Keyword(s):  
Large Scale ◽  
Large Data ◽  
Data Grid ◽  
Scientific Data ◽  
Success Rates ◽  
Distributed Resources ◽  
Grid Model ◽  
Grid Simulation ◽  
Geographically Distributed ◽  
The Impact

Scientific Data Grid mostly deals with large computational problems. It provides geographically distributed resources for large-scale data-intensive applications that generate large scientific data sets. This required the scientist in modern scientific computing communities involved in managing massive amounts of a very large data collections that are geographically distributed. Research in the area of grid has given various ideas and solutions to address these requirements. However, nowadays the number of participants (scientists and institutions) that are involved in this kind of environment is increasing tremendously. This situation has lead to a problem of scalability. In order to overcome this problem we need a data grid model that can scale well with the increasing number of users. Peer-to-peer (P2P) is one of the architectures that is a promising scale and dynamism environment. In this paper, we present a P2P model for Scientific Data Grid that utilizes the P2P services to address the scalability problem. By using this model, we study and propose various decentralized discovery strategies that intend to address the problem of scalability. We also investigate the impact of data replication that addresses the data distribution and reliability problem for our Scientific Data Grid model on the propose discovery strategies. For the purpose of this study, we have developed and used our own data grid simulation written using PARSEC. We illustrate our P2P Scientific Data Grid model and our data grid simulation used in this study. We then analyze the performance of the discovery strategies with and without the existence of replication strategies relative to their success rates, bandwidth consumption and average number of hop.

Load Balancing to Increase the Consistency of Replicas in Data Grids

2012 ◽  
pp. 42-57
Author(s):  
Ghalem Belalem ◽  
Naima Belayachi ◽  
Radjaa Behidji ◽  
Belabbes Yagoubi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Data Grids ◽  
Distributed Resources ◽  
Data Set ◽  
Large Scale Systems ◽  
Consistency Management ◽  
Geographically Distributed ◽  
Replication Technique ◽  
Improve Service Quality

Data grids are current solutions to the needs of large scale systems and provide a set of different geographically distributed resources. Their goal is to offer an important capacity of parallel calculation, ensure a data effective and rapid access, improve the availability, and tolerate the breakdowns. In such systems, however, these advantages are possible only by using the replication technique. The use of this technique raises the problem of maintaining consistency of replicas of the same data set. In order to guarantee replica set reliability, it is necessary to have high coherence. This fact, however, penalizes performance. In this paper, the authors propose studying balancing influence on replica quality. For this reason, a service of hybrid consistency management is developed, which combines the pessimistic and optimistic approaches and is extended by a load balancing service to improve service quality. This service is articulated on a hierarchical model with two levels.

scholarly journals Distributed Meta-Brokering P2P Overlay for Scheduling in Cloud Federation

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 852 ◽  
Author(s):  
Sajid Latif ◽  
Syed Mushhad Gilani ◽  
Rana Liaqat Ali ◽  
Misbah Liaqat ◽  
Kwang-Man Ko
Keyword(s):  
Resource Management ◽  
Service Provision ◽  
Large Scale ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Distributed Resources ◽  
Proposed Model ◽  
Geographically Distributed ◽  
Application Programming

The interconnected cloud (Intercloud) federation is an emerging paradigm that revolutionizes the scalable service provision of geographically distributed resources. Large-scale distributed resources require well-coordinated and automated frameworks to facilitate service provision in a seamless and systematic manner. Unquestionably, standalone service providers must communicate and federate their cloud sites with other vendors to enable the infinite pooling of resources. The pooling of these resources provides uninterpretable services to increasingly growing cloud users more efficiently, and ensures an improved Service Level Agreement (SLA). However, the research of Intercloud resource management is in its infancy. Therefore, standard interfaces, protocols, and uniform architectural components need to be developed for seamless interaction among federated clouds. In this study, we propose a distributed meta-brokering-enabled scheduling framework for provision of user application services in the federated cloud environment. Modularized architecture of the proposed system with uniform configuration in participating resource sites orchestrate the critical operations of resource management effectively, and form the federation schema. Overlaid meta-brokering instances are implemented on the top of local resource brokers to keep the global functionality isolated. These instances in overlay topology communicate in a P2P manner to maintain decentralization, high scalability, and load manageability. The proposed framework has been implemented and evaluated by extending the Java-based CloudSim 3.0.3 simulation application programming interfaces (APIs). The presented results validate the proposed model and its efficiency to facilitate user application execution with the desired QoS parameters.

scholarly journals Are Phage Lytic Proteins the Secret Weapon To Kill Staphylococcus aureus?

mBio ◽  
2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Diana Gutiérrez ◽  
Lucía Fernández ◽  
Ana Rodríguez ◽  
Pilar García
Keyword(s):  
Staphylococcus Aureus ◽  
Large Scale ◽  
Bacterial Resistance ◽  
Antibiotic Use ◽  
Legal Framework ◽  
Scientific Data ◽  
Scale Production ◽  
Health Authorities ◽  
Prophylactic Measures ◽  
The Impact

ABSTRACT Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most threatening microorganisms for global human health. The current strategies to reduce the impact of S. aureus include a restrictive control of worldwide antibiotic use, prophylactic measures to hinder contamination, and the search for novel antimicrobials to treat human and animal infections caused by this bacterium. The last strategy is currently the focus of considerable research. In this regard, phage lytic proteins (endolysins and virion-associated peptidoglycan hydrolases [VAPGHs]) have been proposed as suitable candidates. Indeed, these proteins display narrow-spectrum antimicrobial activity and a virtual lack of bacterial-resistance development. Additionally, the therapeutic use of phage lytic proteins in S. aureus animal infection models is yielding promising results, showing good efficacy without apparent side effects. Nonetheless, human clinical trials are still in progress, and data are not available yet. This minireview also analyzes the main obstacles for introducing phage lytic proteins as human therapeutics against S. aureus infections. Besides the common technological problems derived from large-scale production of therapeutic proteins, a major setback is the lack of a proper legal framework regulating their use. In that sense, the relevant health authorities should urgently have a timely discussion about these new antimicrobials. On the other hand, the research community should provide data to dispel any doubts regarding their efficacy and safety. Overall, the appropriate scientific data and regulatory framework will encourage pharmaceutical companies to invest in these promising antimicrobials.

Load Balancing to Increase the Consistency of Replicas in Data Grids

2010 ◽  
Vol 1 (4) ◽  
pp. 42-57 ◽  
Author(s):  
Ghalem Belalem ◽  
Naima Belayachi ◽  
Radjaa Behidji ◽  
Belabbes Yagoubi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Data Grids ◽  
Distributed Resources ◽  
Data Set ◽  
Large Scale Systems ◽  
Consistency Management ◽  
Geographically Distributed ◽  
Replication Technique ◽  
Improve Service Quality

Data grids are current solutions to the needs of large scale systems and provide a set of different geographically distributed resources. Their goal is to offer an important capacity of parallel calculation, ensure a data effective and rapid access, improve the availability, and tolerate the breakdowns. In such systems, however, these advantages are possible only by using the replication technique. The use of this technique raises the problem of maintaining consistency of replicas of the same data set. In order to guarantee replica set reliability, it is necessary to have high coherence. This fact, however, penalizes performance. In this paper, the authors propose studying balancing influence on replica quality. For this reason, a service of hybrid consistency management is developed, which combines the pessimistic and optimistic approaches and is extended by a load balancing service to improve service quality. This service is articulated on a hierarchical model with two levels.

scholarly journals Towards a scalable Scientific Data Grid model and services

2008 ◽  
Author(s):  
Azizol Abdullah ◽  
Mohamed Othman ◽  
Md Nasir Sulaiman ◽  
Hamidah Ibrahim ◽  
Abu Talib Othman
Keyword(s):  
Data Grid ◽  
Scientific Data ◽  
Grid Model

scholarly journals Bad Tools Hurt: Lessons for teaching computer security skills to undergraduates

2021 ◽  
Vol 5 (2) ◽  
pp. 74-92
Author(s):  
Jonathan Sharman ◽  
Claudia Acemyan ◽  
Philip Kortum ◽  
Dan Wallach
Keyword(s):  
Computer Security ◽  
Undergraduate Students ◽  
Large Scale ◽  
Web Applications ◽  
Success Rates ◽  
Testing Tool ◽  
Programming Skills ◽  
The Impact ◽  
Positive Effect ◽  
Cross Site Request Forgery

Understanding why developers continue to misuse security tools is critical to designing safer software, yet the underlying reasons developers fail to write secure code are not well understood. In order to better understand how to teach these skills, we conducted two comparatively large-scale usability studies with undergraduate CS students to assess factors that affect success rates in securing web applications against cross-site request forgery (CSRF) attacks. First, we examined the impact of providing students with example code and/or a testing tool. Next, we examined the impact of working in pairs. We found that access to relevant secure code samples gave significant benefit to security outcomes. However, access to the tool alone had no significant effect on security outcomes, and surprisingly, the same held true for the tool and example code combined. These results confirm the importance of quality example code and demonstrate the potential danger of using security tools in the classroom that have not been validated for usability. No individual differences predicted one’s ability to complete the task. We also found that working in pairs had a significant positive effect on security outcomes. These results provide useful directions for teaching computer security programming skills to undergraduate students.

scholarly journals Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative

2021 ◽  
Vol 8 ◽  
Author(s):  
Maria de Fátima Brito ◽  
Carla Torre ◽  
Beatriz Silva-Lima
Keyword(s):  
Large Scale ◽  
Individual Variability ◽  
Scientific Data ◽  
World Health ◽  
Scale Production ◽  
Patient Centered ◽  
Clinical Endpoints ◽  
Large Scale Production ◽  
New Biomarkers ◽  
The Impact

Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.

scholarly journals Evaluating the Effects of a Programming Error on a Virtual Environment Measure of Spatial Navigation Behavior

2021 ◽  
Author(s):  
Steven Marc Weisberg ◽  
Victor Roger Schinazi ◽  
Andrea Ferrario ◽  
Nora Newcombe
Keyword(s):  
Virtual Environment ◽  
Large Scale ◽  
Spatial Navigation ◽  
Large Data ◽  
Published Data ◽  
Data Sets ◽  
Data Set ◽  
Technical Errors ◽  
Programming Error ◽  
The Impact

Relying on shared tasks and stimuli to conduct research can enhance the replicability of findings and allow a community of researchers to collect large data sets across multiple experiments. This approach is particularly relevant for experiments in spatial navigation, which often require the development of unfamiliar large-scale virtual environments to test participants. One challenge with shared platforms is that undetected technical errors, rather than being restricted to individual studies, become pervasive across many studies. Here, we discuss the discovery of a programming error (a bug) in a virtual environment platform used to investigate individual differences in spatial navigation: Virtual Silcton. The bug resulted in storing the absolute value of an angle in a pointing task rather than the signed angle. This bug was difficult to detect for several reasons, and it rendered the original sign of the angle unrecoverable. To assess the impact of the error on published findings, we collected a new data set for comparison. Our results revealed that the effect of the error on published data is likely to be minimal, partially explaining the difficulty in detecting the bug over the years. We also used the new data set to develop a tool that allows researchers who have previously used Virtual Silcton to evaluate the impact of the bug on their findings. We summarize the ways that shared open materials, shared data, and collaboration can pave the way for better science to prevent errors in the future.

Impact of COVID-19 on Nuclear Medicine in Germany, Austria and Switzerland: An International Survey in April 2020

2020 ◽  
Vol 59 (04) ◽  
pp. 294-299 ◽  
Author(s):  
Lutz S. Freudenberg ◽  
Ulf Dittmer ◽  
Ken Herrmann
Keyword(s):  
Nuclear Medicine ◽  
Health Systems ◽  
Personal Protective Equipment ◽  
Large Scale ◽  
Diagnostic Procedures ◽  
Protective Equipment ◽  
Current Crisis ◽  
Web Based ◽  
Public Versus Private ◽  
The Impact

Abstract Introduction Preparations of health systems to accommodate large number of severely ill COVID-19 patients in March/April 2020 has a significant impact on nuclear medicine departments. Materials and Methods A web-based questionnaire was designed to differentiate the impact of the pandemic on inpatient and outpatient nuclear medicine operations and on public versus private health systems, respectively. Questions were addressing the following issues: impact on nuclear medicine diagnostics and therapy, use of recommendations, personal protective equipment, and organizational adaptations. The survey was available for 6 days and closed on April 20, 2020. Results 113 complete responses were recorded. Nearly all participants (97 %) report a decline of nuclear medicine diagnostic procedures. The mean reduction in the last three weeks for PET/CT, scintigraphies of bone, myocardium, lung thyroid, sentinel lymph-node are –14.4 %, –47.2 %, –47.5 %, –40.7 %, –58.4 %, and –25.2 % respectively. Furthermore, 76 % of the participants report a reduction in therapies especially for benign thyroid disease (-41.8 %) and radiosynoviorthesis (–53.8 %) while tumor therapies remained mainly stable. 48 % of the participants report a shortage of personal protective equipment. Conclusions Nuclear medicine services are notably reduced 3 weeks after the SARS-CoV-2 pandemic reached Germany, Austria and Switzerland on a large scale. We must be aware that the current crisis will also have a significant economic impact on the healthcare system. As the survey cannot adapt to daily dynamic changes in priorities, it serves as a first snapshot requiring follow-up studies and comparisons with other countries and regions.

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