Puredata Systems for Analytics: Concurrency and Workload Management

PureDataTM System for Analytics also called as Netezza is a data warehouse server handling analytic operations capable of providing throughput 1000 times greater and faster than traditional database servers. Impressively, it requires minimal system tuning thereby providing high-end performance as well as requiring a low total cost of ownership (TCO). Database performance is directly linked to the allocation of system resources on a database management system. The heart of the Netezza appliance, Field-Programmable Gate Array (FPGA) plays a key role in boosting the overall performance of a server. I/O operations are always a bottleneck in any database server and it is the FPGA that eradicates the I/O problem in Netezza by filtering the data across each snippet processing unit (SPU), processing and running the queries faster thereby pumping server’s performance greatly. This paper describes the current problems the companies face in a “big data” environment which includes concurrency handling and query performance. There are various factors which affect a query\u27s performance, which includes bad data distribution, stale statistics, server load and uneven system resources. Since this paper is restricted to only the system resources, an in-depth analysis of system resources and its components will be analyzed in this research. A database server’s performance is directly related to its underlying allocation of system resources. Work Load Management (WLM) and each of its features are described in this paper which gives the reader a clear notion of how a query\u27s performance is altered using various mechanisms. The paper describes the current performance problems that exist on the traditional database servers and how the Work Load Management components can be tweaked along with the predefined system configurations to process a query to run faster on a Netezza machine

The Cowl - v.79 - n.1 - Sep 4, 2014

The Cowl - student newspaper of Providence College. Vol 79 - No. 1 - September 4, 2014. 24 pages

Database Security: An Inventory of Threats, Vulnerabilities, and Security Solutions

x, 59 p. This paper was completed as part of the final research component in the University of Oregon Applied Information Management Master's Degree Program [see htpp://aim.uoregon.edu].Databases are being compromised today at an alarming rate (Britt 2007). This content analysis study provides database administrators and security managers with an inventory of five common threats to and six common vulnerabilities of databases of large corporations when more than 1000 devices require security management (Whitman and Mattord 2004), aligning these threats with potential security solutions. As noted by Vizard (2007), while companies are becoming adept at fighting data breaches, attacks are gaining in sophistication

September 14, 1989

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia

A cloud-agnostic queuing system to support the implementation of deadline-based application execution policies

There are many scientific and commercial applications that require the execution of a large number of independent jobs resulting in significant overall execution time. Therefore, such applications typically require distributed computing infrastructures and science gateways to run efficiently and to be easily accessible for end-users. Optimising the execution of such applications in a cloud computing environment by keeping resource utilisation at minimum but still completing the experiment by a set deadline has paramount importance. As container-based technologies are becoming more widespread, support for job-queuing and auto-scaling in such environments is becoming important. Current container management technologies, such as Docker Swarm or Kubernetes, while provide auto-scaling based on resource consumption, do not support job queuing and deadline-based execution policies directly. This paper presents JQueuer, a cloud-agnostic queuing system that supports the scheduling of a large number of jobs in containerised cloud environments. The paper also demonstrates how JQueuer, when integrated with a cloud application-level orchestrator and auto-scaling framework, called MiCADO, can be used to implement deadline-based execution policies. This novel technical solution provides an important step towards the cost-optimisation of batch processing and job submission applications. In order to test and prove the effectiveness of the solution, the paper presents experimental results when executing an agent-based simulation application using the open source REPAST simulation framework

The Montclarion, September 22, 2011

Student Newspaper of Montclair State Universityhttps://digitalcommons.montclair.edu/montclarion/1936/thumbnail.jp

Blockchain Software Verification and Optimization

In the last decade, blockchain technology has undergone a strong evolution. The maturity reached and the consolidation obtained have aroused the interest of companies and businesses, transforming it into a possible response to various industrial needs. However, the lack of standards and tools for the development and maintenance of blockchain software leaves open challenges and various possibilities for improvements. The goal of this thesis is to tackle some of the challenges proposed by blockchain technology, to design and implement analysis, processes, and architectures that may be applied in the real world. In particular, two topics are addressed: the verification of the blockchain software and the code optimization of smart contracts. As regards the verification, the thesis focuses on the original developments of tools and analyses able to detect statically, i.e. without code execution, issues related to non-determinism, untrusted cross-contracts invocation, and numerical overflow/underflow. Moreover, an approach based on on-chain verification is investigated, to proactively involve the blockchain in verifying the code before and after its deployment. For the optimization side, the thesis describes an optimization process for the code translation from Solidity language to Takamaka, also proposing an efficient algorithm to compute snapshots for fungible and non-fungible tokens. The results of this thesis are an important first step towards improving blockchain software development, empirically demonstrating the applicability of the proposed approaches and their involvement also in the industrial field

Transforming Leadership Pathways for Humanities Professionals in Higher Education

Transforming Leadership Pathways for Humanities Professionals in Higher Education includes thirteen essays from a variety of contributors investigating how humanities professionals grapple with the opportunities and challenges of leadership positions. Written by insiders sharing their lived experience, this collection provides an authentic look at the multiple roles humanities specialists play, as well as offers strategies for professional growth, sustenance, and satisfaction. The collection also considers the relationship between disciplinary areas of study, academic training, and the valuable skill sets and habits of mind that serve higher education leaders. While Transforming Leadership Pathways emphasizes that a leadership route in higher education can be a welcome and positive professional move for many humanities scholars, the volume also acknowledges the issues that arise when faculty take on administrative positions while otherwise marginalized on campus because of faculty status, rank, or personal identity. This collection demystifies the path into higher education administration and argues that humanities scholars are uniquely qualified for such roles. Empathetic, deeply analytical, attuned to historical context, and trained in communication, teachers and scholars who hail from humanities disciplines often find themselves well-suited to the demands of complex academic leadership in today’s colleges and universities.https://docs.lib.purdue.edu/navigatingcareershighered/1001/thumbnail.jp