Mobile computation offloading (MCO) is a way of improving mobile device (MD) performance by offloading certain task executions to a more resourceful edge server (ES), rather than running them locally on the MD. This thesis first considers the problem of assigning the wireless communication bandwidth and the ES capacity needed for this remote task execution, so that task completion time constraints are satisfied. The objective is to minimize the average power consumption of the MDs, subject to a cost budget constraint on communication and computation resources. The thesis includes contributions for both soft and hard task completion deadline constraints. The soft deadline case aims to create assignments so that the probability of task completion time deadline violation does not exceed a given violation threshold. In the hard deadline case, it creates resource assignments where task completion time deadlines are always satisfied. The problems are first formulated as mixed integer nonlinear programs. Approximate solutions are then obtained by decomposing the problems into a collection of convex subproblems that can be efficiently solved. Results are presented that demonstrate the quality of the proposed solutions, which can achieve near optimum performance over a wide range of system parameters. The thesis then introduces algorithms for static task class partitioning in MCO. The objective is to partition a given set of task classes into two sets that are either executed locally or those classes that are permitted to contend for remote ES execution. The goal is to find the task class partition that gives the minimum mean MD power consumption subject to task completion deadlines. The thesis generates these partitions for both soft and hard task completion deadlines. Two variations of the problem are considered. The first assumes that the wireless and computational capacities are given and the second generates both capacity assignments subject to an additional resource cost budget constraint. Two class ordering methods are introduced, one based on a task latency criterion, and another that first sorts and groups classes based on a mean power consumption criterion and then orders the task classes within each group based on a task completion time criterion. A variety of simulation results are presented that demonstrate the excellent performance of the proposed solutions. The thesis then considers the use of digital twins (DTs) to offload physical system (PS) activity. Each DT periodically communicates with its PS, and uses these updates to implement features that reflect the real behaviour of the device. A given feature can be implemented using different models that create the feature with differing levels of system accuracy. The objective is to maximize the minimum feature accuracy for the requested features by making appropriate model selections subject to wireless channel and ES resource availability. The model selection problem is first formulated as an NP-complete integer program. It is then decomposed into multiple subproblems, each consisting of a modified Knapsack problem. A polynomial-time approximation algorithm is proposed using dynamic programming to solve it efficiently, by violating its constraints by at most a given factor. A generalization of the model selection problem is then given and the thesis proposes an approximation algorithm using dependent rounding to solve it efficiently with guaranteed constraint violations. A variety of simulation results are presented that demonstrate the excellent performance of the proposed solutions. / Thesis / Doctor of Philosophy (PhD) / Mobile devices (MDs) such as smartphones are currently used to run a wide variety of application tasks. An alternative to local task execution is to arrange for some MD tasks to be run on a remote non-mobile edge server (ES). This is referred to as mobile computation offloading (MCO). The work in this thesis studies two important facets of the MCO problem. 1. The first considers the joint effects of communication and computational resource assignment on task completion times. This work optimizes task offloading decisions, subject to task completion time requirements and the cost that one is willing to incur when designing the network. Procedures are proposed whose objective is to minimize average mobile device power consumption, subject to these cost constraints. 2. The second considers the use of digital twins (DTs) as a way of implementing mobile computation offloading. A DT implements features that describe its physical system (PS) using models that are hosted at the ES. A model selection problem is studied, where multiple DTs share the execution services at a common ES. The objective is to optimize the feature accuracy obtained by DTs subject to the communication and computation resource availability. The thesis proposes different approximation and decomposition methods that solve these problems efficiently.

The limited energy and computing power of small smart devices restricts their ability to support a wide range of applications, especially those needing quick responses. Mobile edge computing offers a potential solution by providing computing resources at the network access points that can be shared by the devices. This enables the devices to offload some of their computational tasks to the access points. To make this work well for multiple devices, we need to judiciously allocate the available communication and computing resources among the devices. The main focus of this thesis is on (near) optimal resource allocation in a K-user offloading system that employs the time division multiple access (TDMA) scheme. In this thesis, we develop effective algorithms for the resource allocation problem that aim to minimize the overall (cost of the) energy that the devices consume in completing their computational tasks within the specified deadlines while respecting the devices' constraints. This problem is tackled for tasks that cannot be divided and hence the system must make a binary decision as to whether or not a task should be offloaded. This implies the need to develop an effective decision-making algorithm to identify a suitable group of devices for offloading. This thesis commences by developing efficient communication resource algorithms that incorporate the impact of integer finite block length in low-latency computational offloading systems with reserved computing resources. In particular, it addresses the challenge of minimizing total energy consumption in a binary offloading scenario involving K users. The approach considers different approximations of the fundamental rate limit in the finite block length regime, departing from the conventional asymptotic rate limits developed by Shannon. Two such alternatives, namely the normal approximation and the SNR-gap approximation, are explored. A decomposition approach is employed, dividing the problem into an inner component that seeks an optimal solution for the communication resource allocation within a defined set of offloading devices, and an outer component aimed at identifying a suitable set of offloading devices. Given the finiteness of the block length and its integer nature, various relaxation techniques are employed to determine an appropriate communication resource allocation. These include incremental and independent roundings, alongside an extended search that utilizes randomization-based methods in both rounding schemes. The findings reveal that incremental randomized rounding, when applied to the normal approximation of the rate limits, enhances system performance in terms of reducing the energy consumption of the offloading users. Furthermore, customized pruned greedy search techniques for selecting the offloading devices efficiently generate good decisions. Indeed, the proposed approach outperforms a number of existing approaches. In the second contribution, we develop efficient algorithms that address the challenge of jointly allocating both computation and communication resources in a binary offloading system. We employ a similar decomposition methodology as in the previous work to perform the decision-making, but this is now done along with joint computation and communication resource allocation. For the inner resource allocation problem, we divide the problem into two components: determining the allocation of computation resources and the optimal allocation of communication resources for the given allocation of computation resources. The allocation of the computation resources implicitly determines a suitable order for data transmission, which facilitates the subsequent optimal allocation of the communication resources. In this thesis, we introduce two heuristic approaches for allocating the computation resources. These approaches sequentially maximize the allowable transmission time for the devices in sequence, starting from the largest leading to a reduction in total offloading energy. We demonstrate that the proposed heuristics substantially lower the computational burden associated with solving the joint computation--communication resource allocation problem while maintaining a low total energy. In particular, its use results in substantially lower energy consumption than other simple heuristics. Additionally, the heuristics narrow the energy gap in comparison to a fictitious scenario in which each task has access to the whole computation resource without the need for sharing. / Thesis / Master of Applied Science (MASc)

Det finns kunskapsluckor att fylla när det gäller mikroplaster från vindkraftsblad. Denna studie bidrar med ökad kunskap om mikroplaster från erosionsskador på vindkraftsblad. Metoden som använts består av datainsamling från bladreparationer och manuell granskning av bladskador via plattformen IRIS från Clobotics. Resultatet visar att vindparken Mörtjärnberget (MTB) eroderar i snitt cirka fem gram mikroplaster per turbin per år eller cirka 1,8 kilo för hela parken per år och totalt cirka 14 kilo sedan etableringen. Skadeläget för Mörttjärnberget visar på att det finns erosionsskador på alla turbiner. Kemikalierna som sprids och påverkar miljön finns i coatingen (topplacken) det handlar om methyl 1,2,2,6,6-pentamethyl-4-piperidyl sebacate och bis (1,2,2,6,6-pentamethyl-4-piperidyl) sebacate. Dessa kemikalier är väldigt skadliga för vattenlevande organismer med långvarig effekt. Totalt har parken på MTB släppt ut 4,56 kilogram coating som innehåller de miljöfarliga ämnena. En slutsats från denna rapport är att utsläppen av mikroplaster från Mörtjärnberget i form av erosionsskador är lägre än vad flera tillverkare och vinkraftsägare uppger. En annan slutsats är att om mikroplaster släpps ut vid reparationen av erosionsskador i form av slipdamm så kan dammet spridas i den lokala miljön. Den högsta koncentrationen vid markytan beräknas vara efter 300 meter respektive 500 meter i vindens riktning med en vindhastighet på en meter per sekund beroende på atmosfärisk stabilitet. Mikroplasterna från reparation av erosionsskador kan hamna i avrinningsområden med en ekologisk status som kan försämras av mikroplaster. / There are knowledge gaps to be filled regarding microplastics from windturbine blades, this study contributes with increased knowledge about microplastics from erosion damage. The method used consists of data collection from blade repairs and manual review of blade damage via the IRIS platform from Clobotics. The results show that the Mörtjärnberget wind farm erodes an average of about five grams of microplastics per turbine per year or about 1.8 kilograms for the entire park per year and a total of about 14 kilograms since it was built. The damage situation for Mörttjärnberget shows that erosion damage is present on all turbines and all turbines have at least one more serious erosion damage that reach the layer filler. The chemicals that spread and affect the environment are found in the coating (topcoat), it is about methyl 1,2,2,6,6-pentamethyl-4-piperidyl sebacate and bis (1,2,2,6,6-pentamethyl-4- piperidyl) sebacate. These chemicals are very harmful to aquatic organisms with long-term effects. In total, the park at MTB has released 4.56 kilograms of coating that contains environmentally hazardous substances. One conclusion from this report is that the emissions of microplastics from the Mörtjärnberget in the form of erosion damage are lower than what several manufacturers and what is said in the media. Another conclusion is that if microplastics are released during the repair of erosion damage in the form of grinding dust, the dust can be spread in the local environment. The highest concentration at the ground surface should be after 300 meters and 500 meters respectively in the direction of the wind with a wind speed of one meter per second depending on atmospheric stability. The microplastics from the repair of erosion damage can end up in watersheds with an ecological status that canbe degraded by microplastics. / <p>2023-11-03</p>

The effect of the electrical field enhancement at the junction discontinuities and its impact on the on-state resistance of power semiconductor devices was investigated. A systematic analysis of the mechanisms behind the techniques that can be used for the edge termination in power semiconductor devices was performed. The influence of the passivation layer properties, such as effective interface charge and dielectric permittivity, on the devices with different edge terminations was analyzed using numerical simulation. A compact analytical expression for the optimal JTE dose was proposed for the first time. This expression has been numerically evaluated for different targeted values of the blocking voltage and the maximum electric field, always resulting in the optimal field distribution that does not require further optimization with 2-D device simulator. A compact set of rules for the optimal design of super-junction power devices was developed. Compact analytical expressions for the optimal dopings and dimensions of the devices employed the field compensation technique are derived and validated with the results of numerical simulations on practical device structures. A comparative experimental study of several approaches used for the edge termination in SiC power diodes and transistors was performed. The investigated techniques included the mesa termination, high-k termination, JTE, and the combination of JTE and field plate edge termination. The mesa edge termination was found to be the most promising among the techniques investigated in this work. This stand-along technique satisfied all the imposed requirements for the ?ideal? edge termination: performance, reproducibility (scalability), and cost-efficiency. First of all, it resulted in the maximum one-dimensional electric field (E1DMAX) at the main device junction equal to 2.4 MV/cm or 93% of the theoretical value of critical electric field in 4H-SiC. Secondly, the measured E1DMAX was found to be independent of the voltage blocking layer parameters that demonstrate the scalability of this technique. Lastly, the implementation of this technique does not require expensive fabrication steps, and along with an efficient use of the die area results in the low cost and high yield.

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