Asynchronous replication of metadata across multi-master servers in distributed data storage systems

In recent years, scientific applications have become increasingly data intensive. The increase in the size of data generated by scientific applications necessitates collaboration and sharing data among the nation\u27s education and research institutions. To address this, distributed storage systems spanning multiple institutions over wide area networks have been developed. One of the important features of distributed storage systems is providing global unified name space across all participating institutions, which enables easy data sharing without the knowledge of actual physical location of data. This feature depends on the ``location metadata\u27\u27 of all data sets in the system being available to all participating institutions. This introduces new challenges. In this thesis, we study different metadata server layouts in terms of high availability, scalability and performance. A central metadata server is a single point of failure leading to low availability. Ensuring high availability requires replication of metadata servers. A synchronously replicated metadata servers layout introduces synchronization overhead which degrades the performance of data operations. We propose an asynchronously replicated multi-master metadata servers layout which ensures high availability, scalability and provides better performance. We discuss the implications of asynchronously replicated multi-master metadata servers on metadata consistency and conflict resolution. Further, we design and implement our own asynchronous multi-master replication tool, deploy it in the state-wide distributed data storage system called PetaShare, and compare performance of all three metadata server layouts: central metadata server, synchronously replicated multi-master metadata servers and asynchronously replicated multi-master metadata servers

Architectural Exploration of Data Recomputation for Improving Energy Efficiency

University of Minnesota Ph.D. dissertation. July 2017. Major: Electrical/Computer Engineering. Advisor: Ulya Karpuzcu. 1 computer file (PDF); viii, 99 pages.There are two fundamental challenges for modern computer system design. The first one is accommodating the increasing demand for performance in a tight power budget. The second one is ensuring correct progress despite the increasing possibility of faults that may occur in the system. To address the first challenge, it is essential to track where the power goes. The energy consumption of data orchestration (i.e., storage, movement, communication) dominates the energy consumption of actual data production, i.e., computation. Oftentimes, recomputing data becomes more energy efficient than storing and retrieving pre-computed data by minimizing the prevalent power and performance overhead of data storage, retrieval, and communication. At the same time, recomputation can reduce the demand for communication bandwidth and shrink the memory footprint. In the first half of the dissertation, the potential of data recomputation in improving energy efficiency is quantified and a practical recomputation framework is introduced to trade computation for communication. To address the second challenge, it is needed to provide scalable checkpointing and recovery mechanisms. The traditional method to recover from a fault is to periodically checkpoint the state of the machine. Periodic checkpointing of the machine state makes rollback and restart of execution from a safe state possible upon detection of a fault. The energy overhead of checkpointing, however, as incurred by storage and communication of the machine state grows with the frequency of checkpointing. Amortizing this overhead becomes especially challenging, considering the growth of expected error rates as an artifact of contemporary technology scaling. Recomputation of data (which otherwise would be read from a checkpoint) can reduce both the frequency of checkpointing, the size of the checkpoints and thereby mitigate checkpointing overhead. In the second half, quantitative characterization of recomputation-enabled checkpointing (based on recomputation framework) is provided

Cyber Bullying Victimization of Elementary School Students and Their Reflections on the Victimization

With the use of developing technology, mostly in communication and entertainment, students spend considerable time on the internet. In addition to the advantages provided by the internet, social isolation brings problems such as addiction. This is one of the problems of the virtual violence. Cyber-bullying is the common name of the intensities which students are exposed on the internet. The purpose of this study designed as a qualitative research is to find out the cyber bullying varieties and its effects on elementary school students. The participants of this research are 6th, 7th and 8th grade students of a primary school and 24 students agreed to participate in the study. The students were asked to fill an interview with semi-structured open-ended questions. According to the results obtained in the research, the most important statements determined by the participants are breaking passwords on social networking sites, slang insult to blasphemy and taking friendship offers from unfamiliar people. According to participants from the research, the most used techniques to prevent themselves from cyber bullying are to complain to the site administrator, closing accounts on social networking sites and countercharging. Also, suggestions were presented according to the findings

Designing an Online Case-Based Library for Technology Integration in Teacher Education

The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for interactive case-based library. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology into education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments

Designing an Online Case-Based Library for Technology Integration in Teacher Education

The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for interactive case-based library. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology into education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments

Bio-realistic Neural Network Implementation on Loihi 2 with Izhikevich Neurons

In this paper, we presented a bio-realistic basal ganglia neural network and its integration into Intel's Loihi neuromorphic processor to perform simple Go/No-Go task. To incorporate more bio-realistic and diverse set of neuron dynamics, we used Izhikevich neuron model, implemented as microcode, instead of Leaky-Integrate and Fire (LIF) neuron model that has built-in support on Loihi. This work aims to demonstrate the feasibility of implementing computationally efficient custom neuron models on Loihi for building spiking neural networks (SNNs) that features these custom neurons to realize bio-realistic neural networks

Serum Presepsin Levels Are Not Elevated in Patients with Controlled Hypertension

Introduction. Hypertension (HT) is a common serious condition associated with cardiovascular morbidity and mortality. The pathogenesis of HT is multifactorial and has been widely investigated. Besides the vascular, hormonal, and neurological factors, inflammation plays a crucial role in HT. Many inflammatory markers such as C-reactive protein, cytokines, and adhesion molecules have been studied in HT, which supported the role of inflammation in the pathogenesis of HT. Presepsin (PSP) is a novel biomarker of inflammation. Therefore, the potential relationship between PSP and HT was investigated in this study. Methods. Forty-eight patients with controlled HT and 48 controls without HT were included in our study. Besides routine clinical and laboratory data, PSP levels were measured in peripheral venous blood samples from all the participants. Results. PSP levels were significantly lower in patients with HT than in controls (144.98±75.98 versus 176.67±48.12 pg/mL, p=0.011). PSP levels were positively correlated with hsCRP among both the patient and the control groups (p=0.015 and p=0.009, resp.). However, PSP levels were not correlated with WBC among both groups (p=0.09 and p=0.67, resp.). Conclusions. PSP levels are not elevated in patients with well-controlled HT compared to controls. This result may be associated with anti-inflammatory effects of antihypertensive medicines