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BIT-RATE AWARE RECONFIGURABLE ARCHITECTURE FOR H.264/AVC DEBLOCKING FILTER
Title
BIT-RATE AWARE RECONFIGURABLE ARCHITECTURE FOR H.264/AVC DEBLOCKING FILTER.
Creator
Khraisha, Rakan, Lee, Jooheung, University of Central Florida
Abstract / Description
In H.264/AVC, DeBlocking Filter (DBF) achieves bit rate savings and it is used to improve visual quality by reducing the presence of blocking artifacts. However, these advantages come at the expense of increasing computational complexity of the DBF due to highly adaptive mode decision and small 4x4 block size. The DBF easily accounts for one third of the computational complexity of the decoder. The computational complexity required for various target applications from mobile to high...
Show moreIn H.264/AVC, DeBlocking Filter (DBF) achieves bit rate savings and it is used to improve visual quality by reducing the presence of blocking artifacts. However, these advantages come at the expense of increasing computational complexity of the DBF due to highly adaptive mode decision and small 4x4 block size. The DBF easily accounts for one third of the computational complexity of the decoder. The computational complexity required for various target applications from mobile to high definition video applications varies significantly. Therefore, it becomes apparent to design efficient architecture to adapt to different requirements. In this work, we exploit the scalability on both the hardware level and the algorithmic level to synergize the performance and to reduce computational complexity. First, we propose a modular DBF architecture which can be scaled to adapt to the required computing capability for various bit-rates, resolutions, and frame rates of video sequences. The scalable architecture is based on FPGA using dynamic partial reconfiguration. This desirable feature of FPGAs makes it possible for different hardware configurations to be implemented during run-time. The proposed design can be scaled to filter up to four different edges simultaneously, resulting in significant reduction of total processing time. Secondly, our experiments show by lowering the bit rate of video sequences, significant reduction in computational complexity can be achieved by the increased presence of skipped macroblocks, thus, avoiding redundant filtering operations. The implemented architecture has been evaluated using Xilinx Virtex-4 ML410 FPGA board. The design can operate at a maximum frequency of 103 MHz. The reconfiguration is done through Internal Configuration Access Port (ICAP) to achieve maximum performance needed by real time applications.
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Date Issued
2010
Identifier
CFE0003247, ucf:48542
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0003247
Research on Improving Reliability, Energy Efficiency and Scalability in Distributed and Parallel File Systems
Title
Research on Improving Reliability, Energy Efficiency and Scalability in Distributed and Parallel File Systems.
Creator
Zhang, Junyao, Wang, Jun, Zhang, Shaojie, Lee, Jooheung, University of Central Florida
Abstract / Description
With the increasing popularity of cloud computing and "Big data" applications, current data centers are often required to manage petabytes or exabytes of data. To store this huge amount of data, thousands or tens of thousands storage nodes are required at a single site. This imposes three major challenges for storage system designers: (1) Reliability---node failure in these datacenters is a normal occurrence rather than a rare situation. This makes data reliability a great concern. (2) Energy...
Show moreWith the increasing popularity of cloud computing and "Big data" applications, current data centers are often required to manage petabytes or exabytes of data. To store this huge amount of data, thousands or tens of thousands storage nodes are required at a single site. This imposes three major challenges for storage system designers: (1) Reliability---node failure in these datacenters is a normal occurrence rather than a rare situation. This makes data reliability a great concern. (2) Energy efficiency---a data center can consume up to 100 times more energy than a standard office building. More than 10% of this energy consumption can be attributed to storage systems. Thus, reducing the energy consumption of the storage system is key to reducing the overall consumption of the data center.(3) Scalability---with the continuously increasing size of data, maintaining the scalability of the storage systems is essential. That is, the expansion of the storage system should be completed efficiently and without limitations on the total number of storage nodes or performance.This thesis proposes three ways to improve the above three key features for current large-scale storage systems. Firstly, we define the problem of "reverse lookup", namely finding the list of objects (blocks) for a failed node. As the first step of failure recovery, this process is directly related to the recovery/reconstruction time. While existing solutions use metadata traversal or data distribution reversing methods for reverse lookup, which are either time consuming or expensive, a deterministic block placement can achieve fast and efficient reverse lookup.However, the deterministic placement solutions are designed for centralized, small-scale storage architectures such as RAID etc.. Due to their lacking of scalability, they cannot be directly applied in large-scale storage systems. In this paper, we propose Group-Shifted Declustering (G-SD), a deterministic data layout for multi-way replication. G-SD addresses the scalability issue of our previous Shifted Declustering layout and supports fast and efficient reverse lookup.Secondly, we define a problem: "how to balance the performance, energy, and recovery in degradation mode for an energy efficient storage system?". While extensive researches have been proposed to tradeoff performance for energy efficiency under normal mode, the system enters degradation mode when node failure occurs, in which node reconstruction is initiated. This very process requires a number of disks to be spun up and requires a substantial amount of I/O bandwidth, which will not only compromise energy efficiency but also performance. Without considering the I/O bandwidth contention between recovery and performance, we find that the current energy proportional solutions cannot answer this question accurately. This thesis present PERP, a mathematical model to minimize the energy consumption for a storage systems with respect to performance and recovery. PERP answers this problem by providing the accurate number of nodes and the assigned recovery bandwidth at each time frame.Thirdly, current distributed file systems such as Google File System(GFS) and Hadoop Distributed File System (HDFS), employ a pseudo-random method for replica distribution and a centralized lookup table (block map) to record all replica locations. This lookup table requires a large amount of memory and consumes a considerable amount of CPU/network resources on the metadata server. With the booming size of "Big Data", the metadata server becomes a scalability and performance bottleneck. While current approaches such as HDFS Federation attempt to "horizontally" extend scalability by allowing multiple metadata servers, we believe a more promising optimization option is to "vertically" scale up each metadata server. We propose Deister, a novel block management scheme that builds on top of a deterministic declustering distribution method Intersected Shifted Declustering (ISD). Thus both replica distribution and location lookup can be achieved without a centralized lookup table.
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Date Issued
2015
Identifier
CFE0006238, ucf:51082
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006238
SCALABLE VOLUMETRIC THREE-DIMENSIONAL UP-CONVERSION DISPLAY MEDIUM
Title
SCALABLE VOLUMETRIC THREE-DIMENSIONAL UP-CONVERSION DISPLAY MEDIUM.
Creator
Cho, Jung-Hyun, Bass, Michael, University of Central Florida
Abstract / Description
There are many different techniques to display 3D information. However, not many of them are able to provide sufficient depth cues to the observers to sense or feel the images as real three-dimensional objects. Volumetric three-dimensional displays generate images within a real 3D space, so they provide most of the depth cues automatically. This thesis discusses the basic notions required to understand three-dimensional displays. Also discussed are different techniques used to display 3D...
Show moreThere are many different techniques to display 3D information. However, not many of them are able to provide sufficient depth cues to the observers to sense or feel the images as real three-dimensional objects. Volumetric three-dimensional displays generate images within a real 3D space, so they provide most of the depth cues automatically. This thesis discusses the basic notions required to understand three-dimensional displays. Also discussed are different techniques used to display 3D information and their advantages and disadvantages as well as their current limitations. Several rare-earth doped fluoride crystals that are excited to emit visible light by sequential two photon absorption have been investigated as display medium candidates for static volumetric three dimensional displays. A scalable display medium is suggested to enable large 3D displays. This medium is a dispersion of particles of the rare earth doped fluoride crystals in a refractive index-matched polymer matrix. Detailed experiments are described to prepare such a scalable display medium using a wide variety of polymers. The scattering problem in such a medium was greatly reduced by index-matching the polymer to the crystalline particles. An index-matching condition that optimizes the performance was identified and demonstrated. A potential near-future solution is demonstrated and improvements are suggested.
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Date Issued
2007
Identifier
CFE0001899, ucf:47405
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001899
Scalable Network Design and Management with Decentralized Software-defined Networking
Title
Scalable Network Design and Management with Decentralized Software-defined Networking.
Creator
Atwal, Kuldip Singh, Bassiouni, Mostafa, Fu, Xinwen, Zou, Changchun, Deo, Narsingh, University of Central Florida
Abstract / Description
Network softwarization is among the most significant innovations of computer networks in the last few decades. The lack of uniform and programmable interfaces for network management led to the design of OpenFlow protocol for the university campuses and enterprise networks. This breakthrough coupled with other similar efforts led to an emergence of two complementary but independent paradigms called software-defined networking (SDN) and network function virtualization (NFV). As of this writing,...
Show moreNetwork softwarization is among the most significant innovations of computer networks in the last few decades. The lack of uniform and programmable interfaces for network management led to the design of OpenFlow protocol for the university campuses and enterprise networks. This breakthrough coupled with other similar efforts led to an emergence of two complementary but independent paradigms called software-defined networking (SDN) and network function virtualization (NFV). As of this writing, these paradigms are becoming the de-facto norms of wired and wireless networks alike. This dissertation mainly addresses the scalability aspect of SDN for multiple network types. Although centralized control and separation of control and data planes play a pivotal role for ease of network management, these concepts bring in many challenges as well. Scalability is among the most crucial challenges due to the unprecedented growth of computer networks in the past few years. Therefore, we strive to grapple with this problem in diverse networking scenarios and propose novel solutions by harnessing capabilities provided by SDN and other related technologies. Specifically, we present the techniques to deploy SDN at the Internet scale and to extend the concepts of softwarization for mobile access networks and vehicular networks. Multiple optimizations are employed to mitigate latency and other overheads that contribute to achieve performance gains. Additionally, by taking care of sparse connectivity and high mobility, the intrinsic constraints of centralization for wireless ad-hoc networks are addressed in a systematic manner. The state-of-the-art virtualization techniques are coupled with cloud computing methods to exploit the potential of softwarization in general and SDN in particular. Finally, by tapping into the capabilities of machine learning techniques, an SDN-based solution is proposed that inches closer towards the longstanding goal of self-driving networks. Extensive experiments performed on a large-scale testbed corroborates effectiveness of our approaches.
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Date Issued
2019
Identifier
CFE0007600, ucf:52543
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007600
Coordinated Optimal Power Planning of Wind Turbines in an Offshore Wind Farm
Title
Coordinated Optimal Power Planning of Wind Turbines in an Offshore Wind Farm.
Creator
Vishwakarma, Puneet, Xu, Yunjun, Kapat, Jayanta, Kauffman, Jeffrey, Behal, Aman, University of Central Florida
Abstract / Description
Wind energy is on an upswing due to climate concerns and increasing energy demands on conventional sources. Wind energy is attractive and has the potential to dramatically reduce the dependency on non-renewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. Wake interferences among wind turbines can lower the overall efficiency considerably, while offshore conditions pose increased...
Show moreWind energy is on an upswing due to climate concerns and increasing energy demands on conventional sources. Wind energy is attractive and has the potential to dramatically reduce the dependency on non-renewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. Wake interferences among wind turbines can lower the overall efficiency considerably, while offshore conditions pose increased loading on wind turbines. In wind farms, wind turbines' wake affects each other depending on their positions and operation modes. Therefore it becomes essential to optimize the wind farm power production as a whole than to just focus on individual wind turbines. The work presented here develops a hierarchical power optimization algorithm for wind farms. The algorithm includes a cooperative level (or higher level) and an individual level (or lower level) for power coordination and planning in a wind farm. The higher level scheme formulates and solves a quadratic constrained programming problem to allocate power to wind turbines in the farm while considering the aerodynamic effect of the wake interaction among the turbines and the power generation capabilities of the wind turbines. In the lower level, optimization algorithm is based on a leader-follower structure driven by the local pursuit strategy. The local pursuit strategy connects the cooperative level power allocation and the individual level power generation in a leader-follower arrangement. The leader, could be a virtual entity and dictates the overall objective, while the followers are real wind turbines considering realistic constraints, such as tower deflection limits. A nonlinear wind turbine dynamics model is adopted for the low level study with loading and other constraints considered in the optimization. The stability of the algorithm in the low level is analyzed for the wind turbine angular velocity. Simulations are used to show the advantages of the method such as the ability to handle non-square input matrix, non-homogenous dynamics, and scalability in computational cost with rise in the number of wind turbines in the wind farm.
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Date Issued
2015
Identifier
CFE0005899, ucf:50896
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005899
Efficient and Scalable Evaluation of Continuous, Spatio-temporal Queries in Mobile Computing Environments
Title
Efficient and Scalable Evaluation of Continuous, Spatio-temporal Queries in Mobile Computing Environments.
Creator
Cazalas, Jonathan, Guha, Ratan, Bassiouni, Mostafa, Orooji, Ali, Al-Deek, Haitham, University of Central Florida
Abstract / Description
A variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. For this research, we present a two-pronged approach at addressing this problem. Firstly, we introduce an efficient and scalable system for monitoring traditional, continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a...
Show moreA variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. For this research, we present a two-pronged approach at addressing this problem. Firstly, we introduce an efficient and scalable system for monitoring traditional, continuous queries by leveraging the parallel processing capability of the Graphics Processing Unit. We examine a naive CPU-based solution for continuous range-monitoring queries, and we then extend this system using the GPU. Additionally, with mobile communication devices becoming commodity, location-based services will become ubiquitous. To cope with the very high intensity of location-based queries, we propose a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view. Our studies show that by exploiting the parallel processing power of the GPU, we are able to significantly scale the number of mobile objects, while maintaining an acceptable level of performance.Our second approach was to view this research problem as one belonging to the domain of data streams. Several works have convincingly argued that the two research fields of spatio-temporal data streams and the management of moving objects can naturally come together. [IlMI10, ChFr03, MoXA04] For example, the output of a GPS receiver, monitoring the position of a mobile object, is viewed as a data stream of location updates. This data stream of location updates, along with those from the plausibly many other mobile objects, is received at a centralized server, which processes the streams upon arrival, effectively updating the answers to the currently active queries in real time.For this second approach, we present GEDS, a scalable, Graphics Processing Unit (GPU)-based framework for the evaluation of continuous spatio-temporal queries over spatio-temporal data streams. Specifically, GEDS employs the computation sharing and parallel processing paradigms to deliver scalability in the evaluation of continuous, spatio-temporal range queries and continuous, spatio-temporal kNN queries. The GEDS framework utilizes the parallel processing capability of the GPU, a stream processor by trade, to handle the computation required in this application. Experimental evaluation shows promising performance and shows the scalability and efficacy of GEDS in spatio-temporal data streaming environments. Additional performance studies demonstrate that, even in light of the costs associated with memory transfers, the parallel processing power provided by GEDS clearly counters and outweighs any associated costs.Finally, in an effort to move beyond the analysis of specific algorithms over the GEDS framework, we take a broader approach in our analysis of GPU computing. What algorithms are appropriate for the GPU? What types of applications can benefit from the parallel and stream processing power of the GPU? And can we identify a class of algorithms that are best suited for GPU computing? To answer these questions, we develop an abstract performance model, detailing the relationship between the CPU and the GPU. From this model, we are able to extrapolate a list of attributes common to successful GPU-based applications, thereby providing insight into which algorithms and applications are best suited for the GPU and also providing an estimated theoretical speedup for said GPU-based applications.
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Date Issued
2012
Identifier
CFE0004222, ucf:49012
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004222