Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 7 of 7

Full-Text Articles in Physical Sciences and Mathematics

Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian Dec 2018

Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian

Computer Science and Engineering Theses

Monitoring the health of data center clusters is an integral part of any industrial facility. ATLAS is one of the High Energy Physics experiments at the Large Hadron Collider (LHC) at CERN. ATLAS DDM (Distributed Data Management) is a system that manages data transfer, staging, deletions and experimental data on the LHC grid. Currently, the DDM system relies on Rucio software, with Cloud based object storage and No-SQL solutions. It is a cumbersome process in the current system, to fetch and analyze the transfer, staging and deletion metrics of a specific site for any regional center. In this thesis, a …


Tdma Slot Reservation In Cluster-Based Vanets, Mohammad Salem Almalag Apr 2013

Tdma Slot Reservation In Cluster-Based Vanets, Mohammad Salem Almalag

Computer Science Theses & Dissertations

Vehicular Ad Hoc Networks (VANETs) are a form of Mobile Ad Hoc Networks (MANETs) in which vehicles on the road form the nodes of the network. VANETs provide several services to enhance the safety and comfort of drivers and passengers. These services can be obtained by the wireless exchange of information among the vehicles driving on the road. In particular, the transmission of two different types of messages, safety/update and non-safety messages.

The transmission of safety/update message aims to inform the nearby vehicles about the sender's current status and/or a detected dangerous situation. This type of transmission is designed to …


On The Design Of Advanced Filters For Biological Networks Using Graph Theoretic Properties, Kathryn Dempsey Cooper, Tzu-Yi Chen, Sanjukta Bhowmick, Hesham Ali Jan 2012

On The Design Of Advanced Filters For Biological Networks Using Graph Theoretic Properties, Kathryn Dempsey Cooper, Tzu-Yi Chen, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Network modeling of biological systems is a powerful tool for analysis of high-throughput datasets by computational systems biologists. Integration of networks to form a heterogeneous model requires that each network be as noise-free as possible while still containing relevant biological information. In earlier work, we have shown that the graph theoretic properties of gene correlation networks can be used to highlight and maintain important structures such as high degree nodes, clusters, and critical links between sparse network branches while reducing noise. In this paper, we propose the design of advanced network filters using structurally related graph theoretic properties. While spanning …


Dynamic Load Balancing For I/O-Intensive Applications On Clusters, Xiao Qin, Hong Jiang, Adam Manzanares, Xiaojun Ruan, Shu Yin Nov 2009

Dynamic Load Balancing For I/O-Intensive Applications On Clusters, Xiao Qin, Hong Jiang, Adam Manzanares, Xiaojun Ruan, Shu Yin

School of Computing: Faculty Publications

Load balancing for clusters has been investigated extensively, mainly focusing on the effective usage of global CPU and memory resources. However, previous CPU- or memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workloads due to the imbalance of I/O load. To solve this problem, we propose two simple yet effective I/O-aware load-balancing schemes for two types of clusters: (1) homogeneous clusters where nodes are identical and (2) heterogeneous clusters, which are comprised of a variety of nodes with different performance characteristics in computing power, memory capacity, and disk speed. In addition to assigning I/O-intensive sequential and parallel jobs …


Detecting Clusters And Outliers For Multi-Dimensional Data, Yong Shi Jan 2008

Detecting Clusters And Outliers For Multi-Dimensional Data, Yong Shi

Faculty and Research Publications

Nowadays many data mining algorithms focus on clustering methods. There are also a lot of approaches designed for outlier detection. We observe that, in many situations, clusters and outliers are concepts whose meanings are inseparable to each other, especially for those data sets with noise. Thus, it is necessary to treat clusters and outliers as concepts of the same importance in data analysis. In this paper, we present a cluster-outlieriterative detection algorithm, tending to detect the clusters and outliers in another perspective for noisy data sets. In this algorithm, clusters are detected and adjusted according to the intra-relationship within clusters …


A Statistical Performance Model Of Homogeneous Raidb Clusters, Brandon Lamar Rogers Mar 2005

A Statistical Performance Model Of Homogeneous Raidb Clusters, Brandon Lamar Rogers

Theses and Dissertations

The continual growth of the Internet and e-commerce is driving demand for speed, reliability and processing power. With the rapid development and maturation of e-commerce, the need for a quick access to large amounts of information is steadily rising. Traditionally, database systems have been used for information storage and retrieval. However, with online auctions, rapid Internet searches, and data archival, the need for more powerful database systems is also growing. One type of distributed database is called Redundant Arrays of Inexpensive Databases (RAIDb). RAIDb clusters are middleware-driven to promote interoperability and portability. RAIDb clusters allow for multiple levels of data …


Improving Cluster Utilization Through Set Based Allocation Policies, Quinn O. Snell, Julio C. Facelli, Brian D. Haymore, David B. Jackson Sep 2001

Improving Cluster Utilization Through Set Based Allocation Policies, Quinn O. Snell, Julio C. Facelli, Brian D. Haymore, David B. Jackson

Faculty Publications

While clusters have already proven themselves in the world of high performance computing, some clusters are beginning to exhibit resource inefficiencies due to increasing hardware diversity. Much of the success of clusters lies in the use of commodity components built to meet various hardware standards. These standards have allowed a great level of hardware backwards compatibility that is now resulting in a condition referred to as hardware 'drift' or heterogeneity. The hardware heterogeneity introduces problems when diverse compute nodes are allocated to a parallel job, as most parallel jobs are not self-balancing. This paper presents a new method that allows …