abstract: Researchers and practitioners have widely studied road network traffic data in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate the impact of road network changes. Unfortunately, collecting large-scale high-quality urban traffic data requires tremendous efforts because participating vehicles must install Global Positioning System(GPS) receivers and administrators must continuously monitor these devices. There have been some urban traffic simulators trying to generate such data with different features. However, they suffer from two critical issues (1) Scalability: most of them only offer single-machine solution which is not adequate to produce large-scale data. Some simulators can generate traffic in parallel but do not well balance the load among machines in a cluster. (2) Granularity: many simulators do not consider microscopic traffic situations including traffic lights, lane changing, car following. This paper proposed GeoSparkSim, a scalable traffic simulator which extends Apache Spark to generate large-scale road network traffic datasets with microscopic traffic simulation. The proposed system seamlessly integrates with a Spark-based spatial data management system, GeoSpark, to deliver a holistic approach that allows data scientists to simulate, analyze and visualize large-scale urban traffic data. To implement microscopic traffic models, GeoSparkSim employs a simulation-aware vehicle partitioning method to partition vehicles among different machines such that each machine has a balanced workload. The experimental analysis shows that GeoSparkSim can simulate the movements of 200 thousand cars over an extensive road network (250 thousand road junctions and 300 thousand road segments). / Dissertation/Thesis / Masters Thesis Computer Engineering 2019

This work develops and examines design strategies for reducing the stiffness of 3D-printed compliant mechanisms. The three aspects of a flexure that determine its stiffness are well known: material, boundary conditions, and geometry. In a highly constrained design space however, flexure stiffness may remain unacceptably high even while arriving at the limits of design constraints. In this work, changes to geometry and boundary conditions are examined that lead to drastically reduced stiffness behavior without changing flexure thickness, width, or length. Changes to geometry can result in very complex mechanisms. However, 3D printing enables almost arbitrarily complex geometries. This dissertation presents three design strategies for stiffness reduction: static balancing, lattice flexures, and compound joints. Static balancing refers to changes in the boundary conditions that result in a near-zero net change in potential energy storage over the useful deflection of a flexure. In this work, I present a method for static balancing that utilizes non-dimensional parameters to quickly synthesize a joint design with stiffness reduced by nearly 90%. This method is not only simple and straightforward, it is applicable to a wide range of flexure topologies. The only requirements on the joint to be balanced are that it must be approximated as a pin joint and torsion spring, and it must have a well-understood stiffness when subjected to a compressive load. Lattice flexures result from modifications to geometry that reduce cross-sectional area without changing width or thickness. However, the reduction in stiffness is greater than the reduction in cross sectional area. This can occur because the bending load is now carried by beams partially in torsion. Two lattice geometries are proposed and analyzed in detail using analytic and numeric techniques. It is shown that the off-axis stiffness behavior of lattice flexures can be better than that of conventional blade flexures while bending stiffness is reduced >60%. Compound joints are those that consist of arrays of flexures arranged co-axially. This arrangement provides increased range of motion, generally decreased stiffness, and improved stability. Additionally, a method is herein presented to reduce the parasitic center shift of a compound joint to nearly zero at a specified deflection. The penultimate chapter demonstrates how all three strategies can be used together, and includes new results to facilitate their combination.

The potential value of the chitin biomass (e.g. food waste) is recently considered being ignored by landfill. Chitin can be a potential cheap carbon source for converting into value-added chemicals by microorganisms. Serratia marcescens is a chitinolytic bacterium that harbors endogenous chitinase systems. With goals of characterzing S. marcescens chitinolytic capabilities and applying S. marcescens to chemical production from chitin, my dissertation main content includes five chapters: 1) Chapter 1 highlights background information of chitin source, S. marcescens and potential metabolic engineering targets using chitin as a substrate; 2) Chapter 2 demonstrates that ChiR is a key regulator in regulating 9 chitinase-related genes in S. marcescens Db11 and manipulation of chiR can be a useful and efficient genetic target to enhance chitin utilization; 3) Chapter 3 reports the production of N-acetylneuraminic acid (Neu5Ac) from chitin by a bottom-up approach of engineering the nonconventional chitinolytic bacterium, Serratia marcescens, including native constitutive promoter characterization and transcriptional and translational pathway balancing; 4) Chapter 4 describes improvement of S. marcescens chitinolytic capability by an adaptive evolution approach; 5) Chapter 5 elucidates S. marcescens intracellular metabolite profile using a constraint-based genome-scale metabolic model (iSR929) based on genomic annotation of S. marcescens Db11. Overall, the dissertation work is the first report of demonstrating the concept of chitin-based CBP using S. marcescens and the computational model and genetic molecular tools developed in this dissertation are valuable but not limited to design-build-test of S. marcescens for contributing to the field of biological science and metabolic engineering applications.

As wireless communications is becoming an increasingly important part of ourevery day lives, the amount of transmitted data is constantly growing, creating ademand for ever-increasing data rates. One of the technologies used for boostingdata rates is carrier aggregation, which allows for wireless units to combine multipleconnections to the cellular network. However, there is a limited number ofpossible combinations defined, meaning that there is a need to search for the bestcombination in any given setup. This thesis introduces software capable of organizingthe defined combinations into tree structures, simplifying the search foroptimal combinations as well as allowing for visualizations of the connectionspossible. In the thesis, a proposed method of creating these trees is presented,together with suggestions on how to visualize important combination characteristics.Studies has also been made on different tree traversal algorithms, showingthat there is little need for searching through all possible combinations, but thata greedy approach has a high performance while substantially limiting the searchcomplexity. / I samband med att trådlösa kommunikationssystem blir en allt större del av våraliv och mängden data som skickas fortsätter att stiga, skapas en efterfrågan förökade datatakter. En av teknologierna som används för att skapa högre datatakterär bäraraggregering (carrier aggregation), som möjliggör för trådlösa enheteratt kombinera flertalet uppkopplingar mot det mobila nätverket. Det finns dockbara ett begränsat antal kombinationer definierade, vilket skapar ett behov av attsöka upp den bästa kombinationen i varje givet tillfälle. Detta arbete introducerarmjukvara som organiserar dessa kombinationer i trädstrukturer, vilket förenklarsökning efter optimala kombinationer tillsammans med möjligheten att visualiserade potentiella uppkopplingarna. I arbetet presenteras en föreslagen metodför att skapa dessa träd, tillsammans med uppslag på hur viktiga egenskaperhos kombinationerna kan visualiseras. Olika trädsökningsalgoritmer har ocksåundersökts, och det visas att det inte är nödvändigt att söka igenom hela träd.Istället visar sig giriga algoritmer ha hög prestanda, samtidigt som sökstorlekenkan hållas kraftigt begränsad.

Power-performance efficiency has become a central focus that is challenging in heterogeneous processing platforms as the power constraints have to be established without hindering the high performance. In this dissertation, a framework for optimizing the power and performance of GPUs in the context of general-purpose computing in GPUs (GPGPU) is proposed. To optimize the leakage power of caches in GPUs, we dynamically switch the L1 and L2 caches into low power modes during periods of inactivity to reduce leakage power. The L1 cache can be put into a low-leakage (sleep) state when a processing unit is stalled due to no ready threads to be scheduled and the L2 can be put into sleep state during its idle period when there is no memory request. The sleep mode is state-retentive, which obviates the necessity to flush the caches after they are woken up, thereby, avoiding any performance degradation. Experimental results indicate that this technique can reduce the leakage power by 52% on average. Further, to improve performance, we redistribute the GPGPU workload across the computing units of the GPU during application execution. The fundamental idea is to monitor the workload on each multi-processing unit and redistribute it by having a portion of its unfinished threads executed in a neighboring multi-processing unit. Experimental results show this technique improves the performance of the GPGPU workload by 15.7%. Finally, to improve both performance and dynamic power of GPUs, we propose two dynamic frequency scaling (DFS) techniques implemented on CPU host threads, one of which is motivated by the significance of the pipeline stalls during GPGPU execution. It applies a feedback controlling algorithm, Proportional-Integral-Derivative (PID), to regulate the frequency of parallel processors and memory channels based on the occupancy of the memory buffering queues. The other technique targets on maximizing the average throughput of all parallel processors under the dynamic power constraints. We formalize this target as a linear programming problem and solve it on the runtime. According to the simulation results, the first technique achieves more than 22% power savings with a 4% improvement in performance and the second technique saves 11% power consumption with 9% performance improvement. The contributions of this dissertation represent a significant advancement in the quest for improving performance and reducing energy consumption of GPGPU.

This thesis explores the functions of laughter in Japanese communication. In orientation it contrasts markedly with previous studies and is the first study to have been based on such a large volume of data. In this paper I have focused on laughter as it serves to maintain a co-operative relationship between the participants in a conversation. I find that in the process of communication, people necessarily have to lay themselves open to others, and in doing so they become conscious of the barrier surrounding and protecting their field, i.e. their �inner world�. I hypothesise that in Japanese at least it is consciousness of this barrier that causes the occurrence of laughter in discourse. In other words, people laugh as part of the process of opening up to others, and also to show their intention to be co-operative. By laughing, people are either confirming that they belong to the same in-group, or they are pretending to belong to the same in-group in order to show co-operation. In my model, laughter is classified: A: Joyful laughter for identifying with the in-group B: Balancing laughter for easing tension C: Laughter as a cover-up. A is also divided into 3 subcategories, B into 3, and C into 2 according to the subject of the utterance and the direction of movement into the protective barrier. Two types of statistical analysis were applied to the data in order to the test the validity of the classification. Keywords: interpersonal communication; laughter; field; barrier; co-operation; joy; balancing; cover-up gender

Heavy-tailed workload distributions are commonly experienced in many areas of distributed computing. Such workloads are highly variable, where a small number of very large tasks make up a large proportion of the workload, making the load very hard to distribute effectively. Traditional task assignment policies are ineffective under these conditions as they were formulated based on the assumption of an exponentially distributed workload. Size-based task assignment policies have been proposed to handle heavy-tailed workloads, but their applications are limited by their static nature and assumption of prior knowledge of a task's service requirement. This thesis analyses existing approaches to load distribution under heavy-tailed workloads, and presents a new generalised task assignment policy that significantly improves performance for many distributed applications, by intelligently addressing the negative effects on performance that highly variable workloads cause. Many problems associated with the modelling and optimisations of systems under highly variable workloads were then addressed by a novel technique that approximated these workloads with simpler mathematical representations, without losing any of their pertinent original properties. Finally, we obtain advance queuing metrics (such as the variance of key measurements like waiting time and slowdown that are difficult to obtain analytically) through rigorous simulation.

Recent advances in Micro-Electro-Mechanical Systems (MEMS) and low-power short-range radios have enabled rapid development of wireless sensor networks. Future sensor networks are anticipated to include hundreds or thousands of these devices in many applications, such as capturing multimedia content for surveillance, structural health monitoring, tracking of accidental chemical leaks, machine failures, earthquakes and intrusion detection. With the increase of sensor applications, a number of challenging problems related to the network protocol design has emerged - the most important ones relating to energy efficiency and lifetime maximisation. Techniques devised for sensor networks should deal with a large number of sensors distributed in the field. Wireless sensor nodes are deployed with limited energy reserves, so the networks should operate with minimum energy overhead. In fact, the network should take into account not only individual node's energy efficiency but also consider the global picture, because surviving nodes' energy reserves in a failed network are wasted energy. This thesis examines a node organisation technique to deal with the above challenges. The focus is on improving network lifetime via organising the nodes in a distributed and energy efficient manner. The main goal is lowering wasted energy via energy balancing and exploiting node redundancy in case of node failure. In particular, this thesis proposes Energy Balanced Clustering (EBC) method for node self-organisation where network tasks (such as data aggregation and data forwarding) are shifted to high-energy neighbours to reduce the energy consumption of low energy nodes. After showing how to extend network lifetime by energy balanced node organisation, the effect of redundant node deployments on network lifetime is addressed. Redundant nodes consume energy by performing unnecessary tasks so a method called Self-Calculated Redundancy Check (SCRC) is proposed to deactivate redundant nodes. A deactivated redundant node can be used as a replacement for a failed node. The Asynchronous Failed Sensor node Detection (AFSD) proposed in this thesis uses the data packets exchanged between neighbours to identify failed neighbours. To restore coverage for network holes caused by failed nodes, policies are given for re-activating redundant nodes. Detailed analytical analysis and simulation of the proposed methods demonstrate that by taking into account energy balancing, eliminating redundant tasks and replacing failed nodes sensor network lifetime can significantly be improved.

<p>In today's world, more and more phone calls are made over IP. This results in an increasing demand for scalable IP telephony equipment.</p><p>Ingate Systems AB produces firewalls specialized in handling IP telephony. They have an inherent limit in the number of concurrent phone calls that they can handle. This can be a bottleneck at high loads. There is a load balancing solution available in the platform, but it has a number of drawbacks, such as media latency and client capability requirements, limiting its usage.</p><p>Many companies provide load balancing solutions for SIP. However, it appears few handle all the problematic scenarios that the Ingate firewall does. This master's thesis aims to add load balancing functionality to the Ingate firewall, so that it can handle all types of clients.</p><p>By splitting the firewall into two completely separate layers - a SIP layer and a firewall layer - the concept of a virtual machine emerges. A machine is no longer restricted to its physical SIP and firewall layers. Instead, virtual machines are used to process calls. They still have SIP and firewall layers, but the layers can reside on different physical machines.</p><p>This thesis demonstrates the operation of an innovative load balancing implementation. The implementation was evaluated, and using four machines the test setup performed 50% better than the original Ingate platform, while still retaining all functionality -- something that was not possible with the original platform. This surpassed both the company's and my own expectations.</p>

<p>Combustion supervision by evaluating flywheel speed variations is a common approach in the automotive industry. This often involves preliminary measurements. An adequate model for simulating flywheel speed can assist to avoid some of these preliminary measurements. </p><p>A physical nonlinear model for simulating flywheel speed based on cylinder pressure information is investigated in this work. Measurements were conducted at Scania in a test bed and on a chassis dynamometer. The model was implemented in MATLAB/Simulink and simulations are compared to measured data. The first model can not explain all dynamics for the measurements in the test bed so extended models are examined. A model using a dynamically equivalent model of the crank-slider mechanism shows no difference from the simple model, whereas a model including a driveline can explain more from the test-bed measurements. When simulating the setups used at the chassis dynamometer, the simplest model works best. Yet, it is not very accurate and it is proposed that optimization of parameter values might improve the model further. A sensitivity analysis shows that the model is fairly robust to parameter changes.</p><p>A continuation of this work might include optimization to estimate parameter values in the model. Investigating methods for combustion supervision may also be a future issue.</p>