Indiana University

Displaying 1-40 of 147 results

  • White Papers // Jun 2014

    SPARQL Query Optimization for Structural Indexed RDF Data

    Resource description framework, RDF, is a standard language model for representing semantic data. As the concept of semantic Web becomes more viable, the ability to retrieve and exchange semantic data will become increasingly more important. Efficient management of RDF data is one of the key research issues in semantic Web;...

    Provided By Indiana University

  • White Papers // Jun 2014

    The FutureGrid Testbed for Big Data

    In this paper the authors will be introducing FutureGrid, which provides a testbed to conduct research for cloud, grid, and high performance computing. Although FutureGrid has only a modest number of compute cores (about 4500 regular cores and 14000 GPU cores) it provides an ideal playground to test out various...

    Provided By Indiana University

  • White Papers // Mar 2014

    Towards Understanding Cloud Usage through Resource Allocation Analysis on XSEDE

    In shared resource environments, usage data is necessary to identify utilization of the infrastructure by users. Many cloud platforms recently started to collect measurements for use of resources that can be applied to billing and monitoring. Understanding utilization and performance through these measurements is crucial in the infrastructure in order...

    Provided By Indiana University

  • White Papers // Mar 2014

    Evaluation of Java Message Passing in High Performance Data Analytics

    In the last few years, Java gain popularity in processing \"Big data\" mostly with Apache big data stack - a collection of open source frameworks dealing with abundant data, which includes several popular systems such as Hadoop, Hadoop Distributed File System (HDFS), and spark. Efforts have been made to introduce...

    Provided By Indiana University

  • White Papers // Mar 2014

    Converting Data to Task-Parallelism by Rewrites: Purely Functional Programs Across Multiple GPUs and CPUs

    High-level domain-specific-languages for array processing on the GPU are increasingly common, but to date they run only on a single GPU. The authors argue that languages will need to target multiple devices, even simultaneous combinations of GPU/GPU and CPU/GPU. Increased flexibility may be key to making these languages more easily...

    Provided By Indiana University

  • White Papers // Feb 2014

    Supporting Queries and Analyses of Large-Scale Social Media Data with Customizable and Scalable Indexing Techniques over NoSQL Databases

    Social media data analysis demonstrates two special characteristics in big data processing. First, most analyses focus on data subsets related to specific social events or activities, instead of the whole data set. Second, analysis workflows consist of multiple stages, and algorithms applied in each stage may use different computation and...

    Provided By Indiana University

  • White Papers // Feb 2014

    Advanced Virtualization Techniques for High Performance Cloud Cyberinfrastructure

    With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for data-intensive applications. However,...

    Provided By Indiana University

  • White Papers // Jan 2014

    Towards a Collective Layer in the Big Data Stack

    During the last decade three largely industry-driven disruptive trends have altered the landscape of scalable parallel computing, which has long been dominated by the HPC applications. These disruptions are the emergence of data intensive computing (aka big data), the new emergence of commodity cluster-based execution & storage frameworks such as...

    Provided By Indiana University

  • White Papers // Oct 2013

    Parallel Deterministic Annealing Clustering and its Application to LC-MS Data Analysis

    The authors present a scalable parallel deterministic annealing formalism for clustering with cutoffs and position dependent variances. They apply it to the \"Peak matching\" problem of the precise identification of the common LC-MS peaks across a cohort of multiple biological samples in proteomic biomarker discovery. They find reliably and automatically...

    Provided By Indiana University

  • White Papers // Sep 2013

    Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

    The authors present a study of three important kernels that occur frequently in iterative statistical applications: k-means, Multi-Dimensional Scaling (MDS), and PageRank. They implemented each kernel using OpenCL and evaluated their performance on an NVIDIA Tesla GPGPU card. By examining the underlying algorithms and empirically measuring the performance of various...

    Provided By Indiana University

  • White Papers // Jul 2013

    An Overview of Present NoSQL Solutions and Features

    NoSQL database is an emerging research topic as the amount of stored digital information is dramatically growing each minute. In the authors' current era of extreme data scales, NoSQL meets the requirements of the large-scale distributed computing environment, which provides scalability, high availability, high performance and reliability. NoSQL solutions share...

    Provided By Indiana University

  • White Papers // Jun 2013

    Bootstrapping Trust in Online Dating: Social Verification of Online Dating Profiles

    Online dating is an increasingly thriving business which boasts billion dollar revenues and attracts users in the tens of millions. Notwithstanding its popularity, online dating is not impervious to worrisome trust and privacy concerns raised by the disclosure of potentially sensitive data as well as the exposure to self-reported (and...

    Provided By Indiana University

  • White Papers // May 2013

    A Robust and Scalable Solution for Interpolative Multidimensional Scaling With Weighting

    Advances in modern bio-sequencing techniques have led to a proliferation of raw genomic data that enables an unprecedented opportunity for data mining. To analyze such large volume and high-dimensional scientific data, many high performance dimension reduction and clustering algorithms have been developed. Among the known algorithms, the authors use Multi-Dimensional...

    Provided By Indiana University

  • White Papers // Apr 2013

    Mammoth Data in the Cloud: Clustering Social Images

    Social image datasets have grown to dramatic size with images classified in vector spaces with high dimension (512-2048) and with potentially billions of images and corresponding classification vectors. The authors study the challenging problem of clustering such sets into millions of clusters using iterative MapReduce. They introduce a new K-means...

    Provided By Indiana University

  • White Papers // Apr 2013

    Co-processing SPMD Computation on GPUs and CPUs on Shared Memory System

    Heterogeneous parallel system with multi processors and accelerators are becoming ubiquitous due to better cost-performance and energy-efficiency. These heterogeneous processor architectures have different instruction sets and are optimized for either task-latency or throughput purposes. Challenges occur in regard to programmability and performance when executing SPMD computations on heterogeneous architectures simultaneously....

    Provided By Indiana University

  • White Papers // Mar 2013

    Android Provenance: Diagnosing Device Disorders

    Mobile devices are a ubiquitous part of the people daily lives. Smartphones are being used in many areas where data privacy and integrity are a concern. One threat to integrity and privacy is the existence of bugs in operating system code. Little has been done to provide tools for system-wide...

    Provided By Indiana University

  • White Papers // Nov 2012

    Survey on High Productivity Computing Systems (HPCS) Languages

    Parallel languages have been focused towards performance, but it alone is not be sufficient to overcome the barrier of developing software that exploits the power of evolving architectures. DARPA initiated High Productivity Computing Systems (HPCS) languages project as a solution which addresses software productivity goals through language design. The resultant...

    Provided By Indiana University

  • White Papers // Nov 2012

    FRIEDA: Flexible Robust Intelligent Elastic Data Management in Cloud Environments

    Scientific applications are increasingly using cloud resources for their data analysis workflows. However, managing data effectively and efficiently over these cloud resources is challenging due to the myriad storage choices with different performance, cost trade-offs, complex application choices and complexity associated with elasticity, failure rates in these environments. The explosion...

    Provided By Indiana University

  • White Papers // Sep 2012

    PlaceRaider: Virtual Theft in Physical Spaces with Smartphones

    As Smartphone become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of Smartphone features increasingly powerful onboard sensor suites. A new strain of 'Sensor malware' has been developing that leverages these sensors to steal information from the physical environment - e.g., researchers have...

    Provided By Indiana University

  • White Papers // Aug 2012

    The Design and Implementation of a Multi-Level Content-Addressable Checkpoint File System

    Long-running HPC applications guard against node failures by writing checkpoints to parallel file systems. Writing these checkpoints with petascale class machines has proven difficult and the increased concurrency demands of exascale computing will exacerbate this problem. To meet check-pointing demands and sustain application-perceived throughput at exascale, multi-tiered hierarchical storage architectures...

    Provided By Indiana University

  • White Papers // Aug 2012

    Performance Model for Parallel Matrix Multiplication with Dryad: Dataflow Graph Runtime

    In order to meet the big data challenge of today's society, several parallel execution models on distributed memory architectures have been proposed: MapReduce, Iterative MapReduce, graph processing, and dataflow graph processing. Dryad is a distributed data-parallel execution engine that model program as dataflow graphs. In this paper, the authors evaluated...

    Provided By Indiana University

  • White Papers // Jul 2012

    Bridging the Gap Between HPC and IaaS

    With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for data-intensive applications. However,...

    Provided By Indiana University

  • White Papers // Jul 2012

    Design of a Dynamic Provisioning System for a Federated Cloud and Bare-Metal Environment

    The authors present the design of a dynamic provisioning system that is able to manage the resources of a federated cloud environment by focusing on their utilization. With their framework, it is not only possible to allocate resources at a particular time to a specific Infrastructure as a service framework,...

    Provided By Indiana University

  • White Papers // Jun 2012

    My Privacy Policy: Exploring End-User Specification of Free-Form Location Access Rules

    The increasing inclusion of location and other contextual information in social media applications requires users to be more aware of what their location disclosures reveal. As such, it is important to consider whether existing access-control mechanisms for managing location sharing meet the needs of today's users. The authors report on...

    Provided By Indiana University

  • White Papers // Jun 2012

    Scalable Parallel Computing on Clouds Using Twister4Azure Iterative MapReduce

    Recent advances in data intensive computing for science discovery are fueling a dramatic growth in the use of data-intensive iterative computations. The utility computing model introduced by cloud computing, combined with the rich set of cloud infrastructure and storage services, offers a very attractive environment in which scientists can perform...

    Provided By Indiana University

  • White Papers // Jun 2012

    Large Scale Classification Based on Combination of Parallel SVM and Interpolative MDS

    With the development of information technology, the scale of electronic data becomes larger and larger. Data deluge occurs in many kinds of application fields. How to explore the useful information from the large scale dataset is a very important issue. Data mining is just to take on the task. Support...

    Provided By Indiana University

  • White Papers // Jun 2012

    A Parallel Clustering Method Study Based on MapReduce

    Clustering is considered as the most important task in data mining. The goal of clustering is to determine the intrinsic grouping in a set of unlabeled data. Many practical application problems should be solved with clustering method. It has been widely applied into all kinds of areas, such marketing, biology,...

    Provided By Indiana University

  • White Papers // Jun 2012

    Study on Parallel SVM Based on MapReduce

    Support Vector Machines (SVM) is powerful classification and regression tools. They have been widely studied by many scholars and applied in many kinds of practical fields. But their compute and storage requirements increase rapidly with the number of training vectors, putting many problems of practical interest out of their reach....

    Provided By Indiana University

  • White Papers // May 2012

    Improving Resource Utilization in MapReduce

    MapReduce has been adopted widely in both academia and industry to run large-scale data parallel applications. In MapReduce, each slave node hosts a number of task slots to which tasks can be assigned. So they limit the maximum number of tasks that can execute concurrently on each node. When all...

    Provided By Indiana University

  • White Papers // May 2012

    Hiding in Plain Sight: Exploiting Broadcast for Practical Host Anonymity

    Users are being tracked on the Internet more than ever before as Web sites and search engines gather pieces of information sufficient to identify and study their behavior. While many existing schemes provide strong anonymity, they are inappropriate when high bandwidth and low latency are required. In this paper, the...

    Provided By Indiana University

  • White Papers // May 2012

    Sensitive Data Requests: Do Sites Ask Correctly?

    The Web offers unprecedented opportunities for ecommerce. The security of such transactions is commonly provided through the use of the Transport Layer Security (TLS) protocol, the standards track successor of the Secure Sockets Layer (SSL) protocol. TLS allows clients to verify the authenticity of the servers they access and ensures...

    Provided By Indiana University

  • White Papers // May 2012

    Exploitable Redirects on the Web: Identification, Prevalence, and Defense

    Web sites on the Internet often use redirection. Unfortunately, without additional security, many of the redirection links can be manipulated and abused to mask phishing attacks. In this paper, the authors prescribe a set of heuristics to identify redirects that can be exploited. Using these heuristics, they examine the prevalence...

    Provided By Indiana University

  • White Papers // May 2012

    Trust Management Framework for Social Networks

    Inspired by the similarities between human trust and physical measurements, the authors propose a new system of trust metrics, composed by impression and confidence, which captures both human trust level and its uncertainty, while being intuitive and user friendly. Furthermore, based on measurement error propagation theory, they propose an evaluation...

    Provided By Indiana University

  • White Papers // May 2012

    Abstract Image Management and Universal Image Registration for Cloud and HPC Infrastructures

    Cloud computing has become an important driver for delivering Infrastructure as a Service (IaaS) to users with on-demand requests for customized environments and sophisticated software stacks. Within the FutureGrid (FG) project, the authors offer different IaaS frameworks as well as high performance computing infrastructures by allowing users to explore them...

    Provided By Indiana University

  • White Papers // May 2012

    Comparison of Multiple Cloud Frameworks

    Today, many cloud Infrastructure as a Service (IaaS) frameworks exist. Users, developers, and administrators have to make a decision about which environment is best suited for them. Unfortunately, the comparison of such frameworks is difficult because either users do not have access to all of them or they are comparing...

    Provided By Indiana University

  • White Papers // May 2012

    Accelerating Data Transfers In Iterative MapReduce Framework

    MapReduce has become popular in recent years due to its attractive programming interface with scalability and reliability in processing big data problems. Recently several iterative MapReduce frameworks including their Twister system have emerged to improve the performance on many important data mining applications. Utilizing local memory on each compute node...

    Provided By Indiana University

  • White Papers // Mar 2012

    Seed and Grow: An Attack Against Anonymized Social Networks

    Digital traces left by a user of an online social networking service can be abused by a malicious party to compromise the person's privacy. This is exacerbated by the increasing overlap in user-bases among various services. In this paper, the authors propose an algorithm, Seed and Grow, to identify users...

    Provided By Indiana University

  • White Papers // Mar 2012

    Qualitative Comparison of Multiple Cloud Frameworks

    Many cloud infrastructure as a service frameworks exist and users, developers and administrators have to make a decision, which environment is best suited for them. Unfortunately, the comparison of such frameworks is difficult as users may not have access to all of them, or are comparing the performance of such...

    Provided By Indiana University

  • White Papers // Mar 2012

    Towards Cloud Deployments Using FutureGrid

    In this paper, the authors briefly outline some differences between IaaS frameworks Eucalyptus, OpenNebula, OpenStack and Nimbus. They provide also an overview how platforms such as Amazon, Azure, and Google provide additional services to provide more convenient platforms for its users. They then present an overview of what FutureGrid currently...

    Provided By Indiana University

  • White Papers // Mar 2012

    Synchronization Level Specification and Matching of Software Components

    Generating distributed systems from independently developed and deployed components is a promising alternative for today's dynamic and interconnected world. If such components have to collaborate with each other effectively, they must indicate their contracts explicitly. Traditionally, only the syntactical interfaces are depicted for such components. Recent attempts have argued for...

    Provided By Indiana University

  • White Papers // Oct 2010

    Building a Distributed Block Storage System for Cloud Infrastructure

    The development of cloud infrastructures has stimulated interest in virtualized block storage systems, exemplified by Amazon Elastic Block Store (EBS), Eucalyptus' EBS implementation, and the Virtual Block Store (VBS) system. Compared with other solutions, VBS is designed for flexibility, and can be extended to support various Virtual Machine Managers and...

    Provided By Indiana University

  • White Papers // Sep 2010

    Map-Reduce Expansion of the ISGA Genomic Analysis Web Server

    Biological sequence data can be subjected to a variety of analysis workflows to glean pertinent scientific insight. Recent advances in sequencing techniques have led to a deluge of biosequence data, which necessitates the use of high-performance computing resources in order to carry out analysis in a reasonable period of time....

    Provided By Indiana University

  • White Papers // Oct 2010

    Hybrid Cloud and Cluster Computing Paradigms for Life Science Applications

    Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that...

    Provided By Indiana University

  • White Papers // Aug 2010

    Building Services and Web Portal for GPS Time Series Data Analysis

    In recent years, there has been an increasing demand for methods of analyzing geodetic time series data, informed in part by the observation of unusual aseismic deformation events in GPS data collected from Cascadia, Japan, Peru, and Mexico. The QuakeSim project aims to address this demand by developing a set...

    Provided By Indiana University

  • White Papers // Jul 2010

    Efficient Resource Management for Cloud Computing Environments

    The notion of Cloud computing has not only reshaped the field of distributed systems but also fundamentally changed how businesses utilize computing today. While Cloud computing provides many advanced features, it still has some shortcomings such as the relatively high operating cost for both public and private Clouds. The area...

    Provided By Indiana University

  • White Papers // Oct 2009

    GreenIT Service Level Agreements

    In this paper the authors are introducing a framework towards the inclusion of Green IT metrics as part of service level agreements for future Grids and Clouds. As part of this effort the authors need to revisit Green IT metrics and proxies that the authors consider optimizing against in order...

    Provided By Indiana University

  • White Papers // Feb 2010

    Parallel Data Mining From Multicore to Cloudy Grids

    This paper describe a suite of data mining tools that cover clustering, information retrieval and the mapping of high dimensional data to low dimensions for visualization. Preliminary applications are given to particle physics, bioinformatics and medical informatics. The data vary in dimension from low (2-20), high (Thousands) to undefined (Sequences...

    Provided By Indiana University

  • White Papers // Apr 2010

    Measuring Overhead for Distributed Web Service Handler

    Service Oriented Architecture perfectly manifests itself in Web services, which create seamless and loosely-coupled interactions. Web service utilizes supportive functionalities such as security, reliability and so on. These functionalities are called as handlers, which incrementally add new capabilities. However, adding new handlers into the execution path may cause performance and...

    Provided By Indiana University

  • White Papers // Apr 2010

    Clouds and MapReduce for Scientific Applications

    Cloud computing is at the peak of the Gartner technology hype curve but there are good reasons to believe that as it matures that it will not disappear into their trough of disillusionment but rather move into the plateau of productivity as have for example service oriented architectures. Clouds are...

    Provided By Indiana University

  • White Papers // Jan 2010

    Schedule Distributed Virtual Machines in a Service Oriented Environment

    Virtual machines offer unique advantages to the scientific computing community, such as Quality of Service (QoS) guarantee, performance isolation, easy resource management, and the on-demand deployment of computing environments. Using virtual machines as a computing resource within a distributed environment, such as Service Oriented Architecture (SOA), creates a variety of...

    Provided By Indiana University

  • White Papers // Mar 2010

    Secure Cloud Computing With Brokered Trusted Sensor Networks

    This paper proposes a model for large-scale smartphone based sensor networks, with sensor information processed by clouds and grids, with a mediation layer for processing, filtering and other mashups done via a brokering network. Final aggregate results are assumed to be sent to users through traditional cloud interfaces such as...

    Provided By Indiana University

  • White Papers // Oct 2010

    MapReduce in the Clouds for Science

    The utility computing model introduced by cloud computing combined with the rich set of cloud infrastructure services offers a very viable alternative to traditional servers and computing clusters. MapReduce distributed data processing architecture has become the weapon of choice for data-intensive analyses in the clouds and in commodity clusters due...

    Provided By Indiana University

  • White Papers // Feb 2010

    Cloud Computing for Geosciences

    Cyberinfrastructure has closely tracked commercial best practices for over a decade, but the authors believe there is still much to learn about correct strategies for building distributed systems for collaborating scientists and related communities. This position paper discusses the opportunities to the geo-sciences if Cloud Computing strategies currently used by...

    Provided By Indiana University

  • White Papers // Sep 2009

    High Performance Parallel Computing With Cloud and Cloud Technologies

    This paper presents the experiences in applying, developing, and evaluating cloud and cloud technologies. First, this paper presents the experience in applying Hadoop and DryadLINQ to a series of data/compute intensive applications and then compares them with a novel MapReduce runtime developed by them, named CGL-MapReduce, and MPI. Preliminary applications...

    Provided By Indiana University

  • White Papers // Sep 2010

    Parallel Applications and Tools for Cloud Computing Environments

    The main research focus of SALSA project is two-fold. First, the authors investigate new programming models of parallel multicore computing and Cloud/Grid computing. It aimed at developing and applying parallel and distributed Cyber infrastructure to support large scale data analysis. Second, the authors develop user-friendly and integrated Cloud computing environments...

    Provided By Indiana University

  • White Papers // Nov 2010

    Performance Analysis of HPC Virtualization Technologies Within FutureGrid

    As Cloud computing emerges as the dominant paradigm in distributed systems, it's important to fully understand the underlying technologies that make clouds possible. One technology, and perhaps the most important, is virtualization. Recently virtualization through the use of hypervisors has become widespread and well understood by many. However, there are...

    Provided By Indiana University

  • White Papers // Aug 2010

    Survey on Cloud Computing Security

    Cloud computing may be defined as management and provision of resources, software, applications and information as services over the cloud (internet) on demand. Cloud computing is a model for enabling convenient, on demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released...

    Provided By Indiana University

  • White Papers // Dec 2008

    Comparative Analysis Of ERP Vendors: SAP, Oracle, And Microsoft

    This paper gives the comparative analysis on the Enterprise Resource Planning (ERP) vendors, SAP, Oracle, and Microsoft. The authors research on functionalities, cost, features, and target market for each vendor. ERP system is an integrated information system to support the business within different organizational parts of an enterprise. The leading...

    Provided By Indiana University

  • White Papers // Sep 2009

    Project Bloom: Empowering the Security Research Community Through Data Products and Computing

    Cybercrime is a thriving multi-billion dollar underground economy. Web sites connected to phishing, malware, and scam spring up by the millions every day, and users are lured to them through creative spam, social engineering, and search-engine manipulation. Botnets, or armies of compromised user machines, are a major enabler in much...

    Provided By Indiana University

  • White Papers // Jan 2011

    Programming the Grid: Distributed Software Components, P2P and Grid Web Services for Scientific Applications

    Computational Grids [Grid, Grid1] have become an important asset in large-scale scientific and engineering research. By providing a set of services that allow a widely distributed collection of resources to be tied together into a relatively seamless computing framework, teams of researchers can collaborate to solve problems that they could...

    Provided By Indiana University

  • White Papers // Nov 2010

    Backtesting Portfolio Value-at-Risk With Estimated Portfolio Weights

    This paper theoretically and empirically analyzes backtesting portfolio VaR with estimation risk in an intrinsically multivariate framework. For the first time in the literature, it takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating...

    Provided By Indiana University

  • White Papers // Apr 2010

    Backtesting Value-at-Risk Models: A Multivariate Approach

    The purpose of this paper is to develop a new and simple backtesting procedure that extends the previous work into the multivariate framework. The authors propose to use the multivariate Portmanteau statistic of Ljung-Box type to jointly test for the absence of autocorrelations and cross-correlations in the vector of hits...

    Provided By Indiana University

  • White Papers // Feb 2010

    The Integrated Instrumental Variables Estimator: Exploiting Nonlinearities For Identification Of Linear Models

    A new estimator for linear models with endogenous regressors and strictly exogenous instruments is proposed. The new estimator, called the Integrated Instrumental Variables (IIV) estimator, only requires minimal assumptions to identify the true parameters, thereby providing a potential robust alternative to classical Instrumental Variables (IV) methods when instruments and endogenous...

    Provided By Indiana University

  • White Papers // Nov 2009

    Cross Market Effects Of Stocks Short-Selling Restrictions: Evidence From The September 2008 Natural Experiment

    Using intraday data, this paper investigates empirically the joint stock and corporate bond markets responses to the September 2008 stocks short sell ban. This paper intends to exploit the natural experiment in order to asses the impact of the stock market short sale restrictions (stock market liquidity shock) on corporate...

    Provided By Indiana University

  • White Papers // Nov 2009

    Anchors Away: How Fiscal Policy Can Undermine "Good" Monetary Policy

    Slow moving demographics are aging populations around the world and pushing many countries into an extended period of heightened fiscal stress. In some countries, taxes alone cannot or likely will not fully fund projected pension and health care expenditures. If economic agents place sufficient probability on the economy hitting its...

    Provided By Indiana University

  • White Papers // Oct 2009

    Quasi-Fiscal Policies Of Independent Central Banks And Inflation

    Recently, central banks expanded their balance sheets by unconventional actions, including credit easing operations. Although such quasi-fiscal operations are significant in size and assumed to be crucial for the economy's recovery, little theory is available to explain the possible macroeconomic consequences of these operations. The main contribution of this paper...

    Provided By Indiana University

  • White Papers // Jun 2010

    Modelling Overnight And Daytime Returns Using A Multivariate GARCH-Copula Model

    The authors introduce a multivariate GARCH-Copula model to describe joint dynamics of overnight and daytime returns for multiple assets. The conditional mean and variance of individual overnight and daytime returns depend on their previous realizations through a variant of GARCH specification, and two Student's t copulas describe joint distributions of...

    Provided By Indiana University

  • White Papers // Sep 2010

    What Has Financed Government Debt?

    Equilibrium models imply that the real value of debt in the hands of the public must equal the expected present-value of surpluses. Empirical models of fiscal policy typically do not impose this condition and often do not even include debt. Absence of debt from empirical models can produce non-invertible representations,...

    Provided By Indiana University

  • White Papers // May 2010

    When Does Government Debt Crowd Out Investment?

    The authors examine when government debt crowds out investment for the U.S. economy using an estimated New Keynesian model with a detailed fiscal specification. The estimation accounts for the interaction between monetary and fiscal policies. Whether private investment is crowded in or out in the short term depends on the...

    Provided By Indiana University

  • White Papers // Sep 2009

    The Natural Resource Curse And Economic Transition

    Using cross-country regressions, the authors examine the relationship between "Point-source" resource abundance and economic growth, quality of institutions, investment in human and physical capital, and social welfare (life expectancy and infant mortality). Contrary to most literature, they find little evidence of natural resource curse outside of the economies in transition....

    Provided By Indiana University

  • White Papers // Aug 2009

    Anchoring Fiscal Expectations

    In this paper, the author argues that there are remarkable parallels between how monetary and fiscal policies operate on the macro economy and that these parallels are sufficient to lead one to think about transforming fiscal policy and fiscal institutions as many countries have transformed monetary policy and monetary institutions....

    Provided By Indiana University

  • White Papers // Sep 2009

    Rescuing Banks From The Effects Of The Financial Crisis

    This paper examines government policies aimed at rescuing banks from the effects of the great financial crisis of 2007-2009. To delimit the scope of the analysis, the authors concentrate on the fiscal side of interventions and ignore, by design, the monetary policy reaction to the crisis. The policy response to...

    Provided By Indiana University

  • White Papers // Sep 2009

    Green IT - Key Contributor to Campus Sustainability

    Although college and university campuses are increasingly focusing on sustainability efforts, the direct impact of IT on institutional carbon levels and the potential for new technologies to reduce inefficiencies is not always considered in the overall effort. The Presidents Climate Commitment, for example, makes no mention of server consolidation or...

    Provided By Indiana University

  • White Papers // Oct 2009

    A Federated Approach to Information Management in Grids

    This paper proposes a novel approach to managing information in grids. The proposed approach is an add-on information system that provides unification and federation of grid information services. The system interacts with local information services and assembles their metadata instances under one hybrid architecture to provide a common query/publish interface...

    Provided By Indiana University

  • White Papers // Nov 2010

    Do Male And Female Loan Officers Differ In Small Business Lending? A Review Of The Literature

    It may be surprising to professional bankers, but it has only been recently recognized within the economic literature that loan origination and bank relationships with small enterprises are strongly influenced by the personality, disposition and behavior of loan officers. Information on new loan applicants and client small firms, it is...

    Provided By Indiana University

  • White Papers // Jul 2010

    Horizontal Mergers Of Online Firms: Structural Estimation And Competitive Effects

    This paper presents a general model of online price competition, shows how to structurally estimate the underlying parameters of the model when the number of competing firms is unknown or in dispute, estimates these parameters based on UK data for personal digital assistants, and uses these estimates to simulate the...

    Provided By Indiana University

  • White Papers // Jan 2010

    Querying XML Data: Does One Query Language Fit All?

    This paper describes the characteristics of two different query languages designed to query XML data: DSQL, a declarative SQL like language and XQuery, a procedural language that is fast becoming the defacto language for XML querying. This paper then describes the design of an experiment aimed at comparing the accuracy...

    Provided By Indiana University

  • White Papers // Sep 2009

    A Unified Approach to Intra-Domain Security

    While a variety of mechanisms have been developed for securing individual intra-domain protocols, none address the issue in a holistic manner. The authors develop a unified framework to secure prominent networking protocols within a single domain. They begin with a secure version of the DHCP protocol, which has the additional...

    Provided By Indiana University

  • White Papers // Jan 2011

    Malicious Hubs: Detecting Abnormally Malicious Autonomous Systems

    While many attacks are distributed across botnets, investigators and network operators have recently targeted malicious networks through high profile Autonomous System (AS) de-peerings and network shut-downs. In this paper, the authors explore whether some ASes indeed are safe havens for malicious activity. They look for ISPs and ASes that exhibit...

    Provided By Indiana University

  • White Papers // Aug 2010

    An Internet Without the Internet Protocol

    The growth of the Internet has brought about many challenges for its critical infrastructure. The DNS infrastructure, which translates mnemonic host names into IP addresses understood by the routers, is frequently the target of cache poisoning attacks. Internet routers are also experiencing alarming growth in their routing table sizes, which...

    Provided By Indiana University