Computer Engineering Commons^™

Open Scholarly Publishing Plugin, Barry Bailey

Sabbatical Projects

Presentation reflecting author's sabbatical project, which reviewed the need for and developed a plugin to allow institutions to convert WordPress into an institutional repository.

Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu

Research Collection School Of Computing and Information Systems

Proper feature selection for unsupervised outlier detection can improve detection performance but is very challenging due to complex feature interactions, the mixture of relevant features with noisy/redundant features in imbalanced data, and the unavailability of class labels. Little work has been done on this challenge. This paper proposes a novel Coupled Unsupervised Feature Selection framework (CUFS for short) to filter out noisy or redundant features for subsequent outlier detection in categorical data. CUFS quantifies the outlierness (or relevance) of features by learning and integrating both the feature value couplings and feature couplings. Such value-to-feature couplings capture intrinsic data characteristics and …

Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie

Research Collection School Of Computing and Information Systems

In large-scale distributed file systems, efficient metadata operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the lookup service could be a performance bottleneck due to its significant CPU overhead. Our investigations showed that the lookup service could reduce system throughput by up to 70%, and increase system latency by a factor of up to 8 compared to ideal scenarios. In this paper, we present MetaFlow, a scalable metadata lookup service utilizing software-defined networking (SDN) techniques to distribute lookup workload over network components. MetaFlow tackles …

Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu

Research Collection School Of Computing and Information Systems

Indoor localization is of great importance to a wide range ofapplications in shopping malls, office buildings and publicplaces. The maturity of computer vision (CV) techniques andthe ubiquity of smartphone cameras hold promise for offering sub-meter accuracy localization services. However, pureCV-based solutions usually involve hundreds of photos andpre-calibration to construct image database, a labor-intensiveoverhead for practical deployment. We present ClickLoc, anaccurate, easy-to-deploy, sensor-enriched, image-based indoor localization system. With core techniques rooted insemantic information extraction and optimization-based sensor data fusion, ClickLoc is able to bootstrap with few images. Leveraging sensor-enriched photos, ClickLoc also enables user localization with a single photo of the …

Enthalpy-Based System-Model For Pumped Two-Phase Cooling Systems, Leitao Chen, Fanghao Yang, Pritish R. Parida, Mark Schultz, Timothy Chainer

Publications

The development of embedded chip cooling for 2D and 3D integrated circuits using pumped dielectric refrigerant has gained recent attention due to the ability to manage high heat densities and compatibility with electronics. Recent studies have focused on in-situ thermal and hydrodynamic phenomena (e.g. boiling and bubble dynamics) of two-phase flow boiling at micro-scales. In this paper we focus on the two-phase cooling system design including the cooling capability, size and coefficient of performance (COP). In implementing a two-phase cooling, a system-level computational model for two-phase cooling systems becomes necessary. Therefore, a computationally manageable and accurate one dimensional (1D) system …

Linear Encryption With Keyword Search, Shiwei Zhang, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

Nowadays an increasing amount of data stored in the public cloud need to be searched remotely for fast accessing. For the sake of privacy, the remote files are usually encrypted, which makes them difficult to be searched by remote servers. It is also harder to efficiently share encrypted data in the cloud than those in plaintext. In this paper, we develop a searchable encryption framework called Linear Encryption with Keyword Search (LEKS) that can semi-generically convert some existing encryption schemes meeting our Linear Encryption Template (LET) to be searchable without re-encrypting all the data. For allowing easy data sharing, we …

On Optimizations Of Virtual Machine Live Storage Migration For The Cloud, Yaodong Yang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Virtual Machine (VM) live storage migration is widely performed in the data cen- ters of the Cloud, for the purposes of load balance, reliability, availability, hardware maintenance and system upgrade. It entails moving all the state information of the VM being migrated, including memory state, network state and storage state, from one physical server to another within the same data center or across different data centers. To minimize its performance impact, this migration process is required to be transparent to applications running within the migrating VM, meaning that ap- plications will keep running inside the VM as if there were …

Outlier Detection In Complex Categorical Data By Modeling The Feature Value Couplings, Guansong Pang, Longbing Cao, Ling Chen

Research Collection School Of Computing and Information Systems

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified frequency distributions and many noisy features. Existing pattern-based outlier detection methods are ineffective in handling such complex scenarios, as they misfit such data. CBRW estimates outlier scores of feature values by modelling feature value level couplings, which carry intrinsic data characteristics, via biased random walks to handle this complex data. The outlier scores of feature values can either measure the outlierness of an object or facilitate the existing methods as a feature weighting and selection indicator. Substantial …

Optimizing Main Memory Usage In Modern Computing Systems To Improve Overall System Performance, Daniel Jose Campello

FIU Electronic Theses and Dissertations

Operating Systems use fast, CPU-addressable main memory to maintain an application’s temporary data as anonymous data and to cache copies of persistent data stored in slower block-based storage devices. However, the use of this faster memory comes at a high cost. Therefore, several techniques have been implemented to use main memory more efficiently in the literature. In this dissertation we introduce three distinct approaches to improve overall system performance by optimizing main memory usage.

First, DRAM and host-side caching of file system data are used for speeding up virtual machine performance in today’s virtualized data centers. The clustering of VM …

Sustainable Resource Management For Cloud Data Centers, A. S. M. Hasan Mahmud

FIU Electronic Theses and Dissertations

In recent years, the demand for data center computing has increased significantly due to the growing popularity of cloud applications and Internet-based services. Today's large data centers host hundreds of thousands of servers and the peak power rating of a single data center may even exceed 100MW. The combined electricity consumption of global data centers accounts for about 3% of worldwide production, raising serious concerns about their carbon footprint. The utility providers and governments are consistently pressuring data center operators to reduce their carbon footprint and energy consumption. While these operators (e.g., Apple, Facebook, and Google) have taken steps to …

Eliminating Data Redundancy: Our Solution For Database Discovery Using Alma/Primo, Jacob Kindle, Travis Clamon

ETSU Faculty Works

East Tennessee State University recently adopted Alma & Primo and was suprised by the lack of an A-Z database discovery module. Frustrated by having to maintain electronic resources separately on our library website and in Alma, we embarked on a goal to eliminate redundancy and use Alma/Primo exclusively. This presentation will cover our entire workflow in both Alma & Primo and the issues we encountered along the way. I'll first go over our process in Alma including MARC record creation, electronic collection setup, and the top level collection module. Next, I'll cover our workflow in Primo including normalization rules, scoping, …

Efspredictor: Predicting Configuration Bugs With Ensemble Feature Selection, Bowen Xu, David Lo, Xin Xia, Ashish Sureka, Shanping Li

Research Collection School Of Computing and Information Systems

The configuration of a system determines the system behavior and wrong configuration settings can adversely impact system's availability, performance, and correctness. We refer to these wrong configuration settings as configuration bugs. The importance of configuration bugs has prompted many researchers to study it, and past studies can be grouped into three categories: detection, localization, and fixing of configuration bugs. In the work, we focus on the detection of configuration bugs, in particular, we follow the line-of-work that tries to predict if a bug report is caused by a wrong configuration setting. Automatically prediction of whether a bug is a configuration …

An Integrated Framework For Patent Analysis And Mining, Longhui Zhang

FIU Electronic Theses and Dissertations

Patent documents are important intellectual resources of protecting interests of individuals, organizations and companies. These patent documents have great research values, beneficial to the industry, business, law, and policy-making communities. Patent mining aims at assisting patent analysts in investigating, processing, and analyzing patent documents, which has attracted increasing interest in academia and industry. However, despite recent advances in patent mining, several critical issues in current patent mining systems have not been well explored in previous studies.

These issues include: 1) the query retrieval problem that assists patent analysts finding all relevant patent documents for a given patent application; 2) the …

Dual-Server Public-Key Encryption With Keyword Search For Secure Cloud Storage, Rongmao Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xiaofen Wang

Research Collection School Of Computing and Information Systems

Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, we define a new variant of the smooth projective …

“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams

Senior Honors Theses

Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …

Storage Management Of Data-Intensive Computing Systems, Yiqi Xu

FIU Electronic Theses and Dissertations

Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and storage management is critical to application performance in such data-intensive computing systems. However, existing resource management frameworks in these systems lack the support for storage management, which causes unpredictable performance degradations when applications are under I/O contention. Storage management of data-intensive systems is a challenging problem because I/O resources cannot be easily partitioned and distributed storage systems require scalable management. This dissertation presents the solutions to address these challenges for typical data-intensive systems including high-performance computing (HPC) systems and big-data …

Flash Caching For Cloud Computing Systems, Dulcardo Ariel Arteaga Clavijo

FIU Electronic Theses and Dissertations

As the size of cloud systems and the number of hosted virtual machines (VMs) rapidly grow, the scalability of shared VM storage systems becomes a serious issue. Client-side flash-based caching has the potential to improve the performance of cloud VM storage by employing flash storage available on the VM hosts to exploit the locality inherent in VM IOs. However, there are several challenges to the effective use of flash caching in cloud systems. First, cache configurations such as size, write policy, metadata persistency and RAID level have significant impacts on flash caching. Second, the typical capacity of flash devices is …

In-Field Fuel Use And Load States Of Agricultural Field Machinery, Santosh Pitla, Joe D. Luck, Jared Werner, Nannan Lin, Scott A. Shearer

Department of Biological Systems Engineering: Papers and Publications

The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors …

Defining A Smart Nation: The Case Of Singapore, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Purpose - The purpose of this paper is to identify the key characteristics and propose a working definition of a smart nation.Design/methodology/approach - A case study of Singapore through an analysis of the key speeches made by senior Singapore leaders, publicly available government documents and news reports since the launch of the smart nation initiative in December 2014 was carried out.Findings - Just like smart cities, the idea of a smart nation is an evolving concept. However, there are some emerging characteristics that define a smart nation.Research limitations/implications - The paper provides an initial understanding of the key characteristics and …