Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^

Segmental body composition determination through a bioelectrical very large scale integration (VLSI) system

The purpose of this investigation was to develop new techniques to generate segmental assessments of body composition based on Segmental Bioelectrical Impedance Analysis (SBIA). An equally important consideration was the design, simulation, development, and the software and hardware integration of the SBIA system. This integration was carried out with a Very Large Scale Integration (VLSI) Field Programmable Gate Array (FPGA) microcontroller that analyzed the measurements obtained from segments of the body, and provided full body and segmental Fat Free Mass (FFM) and Fat Mass (FM) percentages. Also, the issues related to the estimate of the body's composition in persons with spinal cord injury (SCI) were addressed and investigated. This investigation demonstrated that the SBIA methodology provided accurate segmental body composition measurements. Disabled individuals are expected to benefit from these SBIA evaluations, as they are non-invasive methods, suitable for paralyzed individuals. The SBIA VLSI system may replace bulky, non flexible electronic modules attached to human bodies. ^

Internet Protocol Television (IPTV) controller realization with Very Large Scale Integration (VLSI) modules

Internet Protocol Television (IPTV) is a system where a digital television service is delivered by using Internet Protocol over a network infrastructure. There is considerable confusion and concern about the IPTV, since two different technologies have to be mended together to provide the end customers with some thing better than the conventional television. In this research, functional architecture of the IPTV system was investigated. Very Large Scale Integration based system for streaming server controller were designed and different ways of hosting a web server which can be used to send the control signals to the streaming server controller were studied. The web server accepts inputs from the keyboard and FPGA board switches and depending on the preset configuration the server will open a selected web page and also sends the control signals to the streaming server controller. It was observed that the applications run faster on PowerPC since it is embedded into the FPGA. Commercial market and Global deployment of IPTV were discussed.

Large scale data processing using MapReduce

As massive data sets become increasingly available, people are facing the problem of how to effectively process and understand these data. Traditional sequential computing models are giving way to parallel and distributed computing models, such as MapReduce, both due to the large size of the data sets and their high dimensionality. This dissertation, as in the same direction of other researches that are based on MapReduce, tries to develop effective techniques and applications using MapReduce that can help people solve large-scale problems. Three different problems are tackled in the dissertation. The first one deals with processing terabytes of raster data in a spatial data management system. Aerial imagery files are broken into tiles to enable data parallel computation. The second and third problems deal with dimension reduction techniques that can be used to handle data sets of high dimensionality. Three variants of the nonnegative matrix factorization technique are scaled up to factorize matrices of dimensions in the order of millions in MapReduce based on different matrix multiplication implementations. Two algorithms, which compute CANDECOMP/PARAFAC and Tucker tensor decompositions respectively, are parallelized in MapReduce based on carefully partitioning the data and arranging the computation to maximize data locality and parallelism.

A conceptual ecological model to facilitate understanding the role of invasive species in large-scale ecosystem restoration

We developed a conceptual ecological model (CEM) for invasive species to help understand the role invasive exotics have in ecosystem ecology and their impacts on restoration activities. Our model, which can be applied to any invasive species, grew from the eco-regional conceptual models developed for Everglades restoration. These models identify ecological drivers, stressors, effects and attributes; we integrated the unique aspects of exotic species invasions and effects into this conceptual hierarchy. We used the model to help identify important aspects of invasion in the development of an invasive exotic plant ecological indicator, which is described a companion paper in this special issue journal. A key aspect of the CEM is that it is a general ecological model that can be tailored to specific cases and species, as the details of any invasion are unique to that invasive species. Our model encompasses the temporal and spatial changes that characterize invasion, identifying the general conditions that allow a species to become invasive in a de novo environment; it then enumerates the possible effects exotic species may have collectively and individually at varying scales and for different ecosystem properties, once a species becomes invasive. The model provides suites of characteristics and processes, as well as hypothesized causal relationships to consider when thinking about the effects or potential effects of an invasive exotic and how restoration efforts will affect these characteristics and processes. In order to illustrate how to use the model as a blueprint for applying a similar approach to other invasive species and ecosystems, we give two examples of using this conceptual model to evaluate the status of two south Florida invasive exotic plant species (melaleuca and Old World climbing fern) and consider potential impacts of these invasive species on restoration.

A large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling

With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

Development of effective approaches to the large-scale aerodynamic testing of low-rise buildings

Low-rise buildings are often subjected to high wind loads during hurricanes that lead to severe damage and cause water intrusion. It is therefore important to estimate accurate wind pressures for design purposes to reduce losses. Wind loads on low-rise buildings can differ significantly depending upon the laboratory in which they were measured. The differences are due in large part to inadequate simulations of the low-frequency content of atmospheric velocity fluctuations in the laboratory and to the small scale of the models used for the measurements. A new partial turbulence simulation methodology was developed for simulating the effect of low-frequency flow fluctuations on low-rise buildings more effectively from the point of view of testing accuracy and repeatability than is currently the case. The methodology was validated by comparing aerodynamic pressure data for building models obtained in the open-jet 12-Fan Wall of Wind (WOW) facility against their counterparts in a boundary-layer wind tunnel. Field measurements of pressures on Texas Tech University building and Silsoe building were also used for validation purposes. The tests in partial simulation are freed of integral length scale constraints, meaning that model length scales in such testing are only limited by blockage considerations. Thus the partial simulation methodology can be used to produce aerodynamic data for low-rise buildings by using large-scale models in wind tunnels and WOW-like facilities. This is a major advantage, because large-scale models allow for accurate modeling of architectural details, testing at higher Reynolds number, using greater spatial resolution of the pressure taps in high pressure zones, and assessing the performance of aerodynamic devices to reduce wind effects. The technique eliminates a major cause of discrepancies among measurements conducted in different laboratories and can help to standardize flow simulations for testing residential homes as well as significantly improving testing accuracy and repeatability. Partial turbulence simulation was used in the WOW to determine the performance of discontinuous perforated parapets in mitigating roof pressures. The comparisons of pressures with and without parapets showed significant reductions in pressure coefficients in the zones with high suctions. This demonstrated the potential of such aerodynamic add-on devices to reduce uplift forces.

Background traffic modeling for large-scale network simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Large-Scale Testing to Study the Effects of Critical Parameters on the Aerodynamic Behavior of Long Span Bridges

Long-span bridges are flexible and therefore are sensitive to wind induced effects. One way to improve the stability of long span bridges against flutter is to use cross-sections that involve twin side-by-side decks. However, this can amplify responses due to vortex induced oscillations. Wind tunnel testing is a well-established practice to evaluate the stability of bridges against wind loads. In order to study the response of the prototype in laboratory, dynamic similarity requirements should be satisfied. One of the parameters that is normally violated in wind tunnel testing is Reynolds number. In this dissertation, the effects of Reynolds number on the aerodynamics of a double deck bridge were evaluated by measuring fluctuating forces on a motionless sectional model of a bridge at different wind speeds representing different Reynolds regimes. Also, the efficacy of vortex mitigation devices was evaluated at different Reynolds number regimes. One other parameter that is frequently ignored in wind tunnel studies is the correct simulation of turbulence characteristics. Due to the difficulties in simulating flow with large turbulence length scale on a sectional model, wind tunnel tests are often performed in smooth flow as a conservative approach. The validity of simplifying assumptions in calculation of buffeting loads, as the direct impact of turbulence, needs to be verified for twin deck bridges. The effects of turbulence characteristics were investigated by testing sectional models of a twin deck bridge under two different turbulent flow conditions. Not only the flow properties play an important role on the aerodynamic response of the bridge, but also the geometry of the cross section shape is expected to have significant effects. In this dissertation, the effects of deck details, such as width of the gap between the twin decks, and traffic barriers on the aerodynamic characteristics of a twin deck bridge were investigated, particularly on the vortex shedding forces with the aim of clarifying how these shape details can alter the wind induced responses. Finally, a summary of the issues that are involved in designing a dynamic test rig for high Reynolds number tests is given, using the studied cross section as an example.

Background Traffic Modeling for Large-Scale Network Simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Experimental and Analytical Methodologies for Predicting Peak Loads on Building Envelopes and Roofing Systems

The performance of building envelopes and roofing systems significantly depends on accurate knowledge of wind loads and the response of envelope components under realistic wind conditions. Wind tunnel testing is a well-established practice to determine wind loads on structures. For small structures much larger model scales are needed than for large structures, to maintain modeling accuracy and minimize Reynolds number effects. In these circumstances the ability to obtain a large enough turbulence integral scale is usually compromised by the limited dimensions of the wind tunnel meaning that it is not possible to simulate the low frequency end of the turbulence spectrum. Such flows are called flows with Partial Turbulence Simulation. In this dissertation, the test procedure and scaling requirements for tests in partial turbulence simulation are discussed. A theoretical method is proposed for including the effects of low-frequency turbulences in the post-test analysis. In this theory the turbulence spectrum is divided into two distinct statistical processes, one at high frequencies which can be simulated in the wind tunnel, and one at low frequencies which can be treated in a quasi-steady manner. The joint probability of load resulting from the two processes is derived from which full-scale equivalent peak pressure coefficients can be obtained. The efficacy of the method is proved by comparing predicted data derived from tests on large-scale models of the Silsoe Cube and Texas-Tech University buildings in Wall of Wind facility at Florida International University with the available full-scale data. For multi-layer building envelopes such as rain-screen walls, roof pavers, and vented energy efficient walls not only peak wind loads but also their spatial gradients are important. Wind permeable roof claddings like roof pavers are not well dealt with in many existing building codes and standards. Large-scale experiments were carried out to investigate the wind loading on concrete pavers including wind blow-off tests and pressure measurements. Simplified guidelines were developed for design of loose-laid roof pavers against wind uplift. The guidelines are formatted so that use can be made of the existing information in codes and standards such as ASCE 7-10 on pressure coefficients on components and cladding.

Experimental and analytical methodologies for predicting peak loads on building envelopes and roofing systems

The performance of building envelopes and roofing systems significantly depends on accurate knowledge of wind loads and the response of envelope components under realistic wind conditions. Wind tunnel testing is a well-established practice to determine wind loads on structures. For small structures much larger model scales are needed than for large structures, to maintain modeling accuracy and minimize Reynolds number effects. In these circumstances the ability to obtain a large enough turbulence integral scale is usually compromised by the limited dimensions of the wind tunnel meaning that it is not possible to simulate the low frequency end of the turbulence spectrum. Such flows are called flows with Partial Turbulence Simulation.^ In this dissertation, the test procedure and scaling requirements for tests in partial turbulence simulation are discussed. A theoretical method is proposed for including the effects of low-frequency turbulences in the post-test analysis. In this theory the turbulence spectrum is divided into two distinct statistical processes, one at high frequencies which can be simulated in the wind tunnel, and one at low frequencies which can be treated in a quasi-steady manner. The joint probability of load resulting from the two processes is derived from which full-scale equivalent peak pressure coefficients can be obtained. The efficacy of the method is proved by comparing predicted data derived from tests on large-scale models of the Silsoe Cube and Texas-Tech University buildings in Wall of Wind facility at Florida International University with the available full-scale data.^ For multi-layer building envelopes such as rain-screen walls, roof pavers, and vented energy efficient walls not only peak wind loads but also their spatial gradients are important. Wind permeable roof claddings like roof pavers are not well dealt with in many existing building codes and standards. Large-scale experiments were carried out to investigate the wind loading on concrete pavers including wind blow-off tests and pressure measurements. Simplified guidelines were developed for design of loose-laid roof pavers against wind uplift. The guidelines are formatted so that use can be made of the existing information in codes and standards such as ASCE 7-10 on pressure coefficients on components and cladding.^

Evaluation of wind-induced internal pressure in low-rise buildings: A multi scale experimental and numerical approach

Hurricane is one of the most destructive and costly natural hazard to the built environment and its impact on low-rise buildings, particularity, is beyond acceptable. The major objective of this research was to perform a parametric evaluation of internal pressure (IP) for wind-resistant design of low-rise buildings and wind-driven natural ventilation applications. For this purpose, a multi-scale experimental, i.e. full-scale at Wall of Wind (WoW) and small-scale at Boundary Layer Wind Tunnel (BLWT), and a Computational Fluid Dynamics (CFD) approach was adopted. This provided new capability to assess wind pressures realistically on internal volumes ranging from small spaces formed between roof tiles and its deck to attic to room partitions. Effects of sudden breaching, existing dominant openings on building envelopes as well as compartmentalization of building interior on the IP were systematically investigated. Results of this research indicated: (i) for sudden breaching of dominant openings, the transient overshooting response was lower than the subsequent steady state peak IP and internal volume correction for low-wind-speed testing facilities was necessary. For example a building without volume correction experienced a response four times faster and exhibited 30–40% lower mean and peak IP; (ii) for existing openings, vent openings uniformly distributed along the roof alleviated, whereas one sided openings aggravated the IP; (iii) larger dominant openings exhibited a higher IP on the building envelope, and an off-center opening on the wall exhibited (30–40%) higher IP than center located openings; (iv) compartmentalization amplified the intensity of IP and; (v) significant underneath pressure was measured for field tiles, warranting its consideration during net pressure evaluations. The study aimed at wind driven natural ventilation indicated: (i) the IP due to cross ventilation was 1.5 to 2.5 times higher for Ainlet/Aoutlet>1 compared to cases where Ainlet/Aoutlet<1, this in effect reduced the mixing of air inside the building and hence the ventilation effectiveness; (ii) the presence of multi-room partitioning increased the pressure differential and consequently the air exchange rate. Overall good agreement was found between the observed large-scale, small-scale and CFD based IP responses. Comparisons with ASCE 7-10 consistently demonstrated that the code underestimated peak positive and suction IP.

Leveraging symbiotic relationships for emulation of computer networks

The lack of analytical models that can accurately describe large-scale networked systems makes empirical experimentation indispensable for understanding complex behaviors. Research on network testbeds for testing network protocols and distributed services, including physical, emulated, and federated testbeds, has made steady progress. Although the success of these testbeds is undeniable, they fail to provide: 1) scalability, for handling large-scale networks with hundreds or thousands of hosts and routers organized in different scenarios, 2) flexibility, for testing new protocols or applications in diverse settings, and 3) inter-operability, for combining simulated and real network entities in experiments. This dissertation tackles these issues in three different dimensions. First, we present SVEET, a system that enables inter-operability between real and simulated hosts. In order to increase the scalability of networks under study, SVEET enables time-dilated synchronization between real hosts and the discrete-event simulator. Realistic TCP congestion control algorithms are implemented in the simulator to allow seamless interactions between real and simulated hosts. SVEET is validated via extensive experiments and its capabilities are assessed through case studies involving real applications. Second, we present PrimoGENI, a system that allows a distributed discrete-event simulator, running in real-time, to interact with real network entities in a federated environment. PrimoGENI greatly enhances the flexibility of network experiments, through which a great variety of network conditions can be reproduced to examine what-if questions. Furthermore, PrimoGENI performs resource management functions, on behalf of the user, for instantiating network experiments on shared infrastructures. Finally, to further increase the scalability of network testbeds to handle large-scale high-capacity networks, we present a novel symbiotic simulation approach. We present SymbioSim, a testbed for large-scale network experimentation where a high-performance simulation system closely cooperates with an emulation system in a mutually beneficial way. On the one hand, the simulation system benefits from incorporating the traffic metadata from real applications in the emulation system to reproduce the realistic traffic conditions. On the other hand, the emulation system benefits from receiving the continuous updates from the simulation system to calibrate the traffic between real applications. Specific techniques that support the symbiotic approach include: 1) a model downscaling scheme that can significantly reduce the complexity of the large-scale simulation model, resulting in an efficient emulation system for modulating the high-capacity network traffic between real applications; 2) a queuing network model for the downscaled emulation system to accurately represent the network effects of the simulated traffic; and 3) techniques for reducing the synchronization overhead between the simulation and emulation systems.

Gesture Recognition Using Neural Networks Based on HW/SW Cosimulation Platform

Hardware/software (HW/SW) cosimulation integrates software simulation and hardware simulation simultaneously. Usually, HW/SW co-simulation platform is used to ease debugging and verification for very large-scale integration (VLSI) design. To accelerate the computation of the gesture recognition technique, an HW/SW implementation using field programmable gate array (FPGA) technology is presented in this paper. The major contributions of this work are: (1) a novel design of memory controller in the Verilog Hardware Description Language (Verilog HDL) to reduce memory consumption and load on the processor. (2) The testing part of the neural network algorithm is being hardwired to improve the speed and performance. The American Sign Language gesture recognition is chosen to verify the performance of the approach. Several experiments were carried out on four databases of the gestures (alphabet signs A to Z). (3) The major benefit of this design is that it takes only few milliseconds to recognize the hand gesture which makes it computationally more efficient.