This dissertation presents an application of multicriteria decision analysis to understand and support pricing decisions in fields where goods are unique and described by their characteristics. The specific application area of this research is antique silver objects, where a complete iteration of the multicritia decision process is performed. This includes two problem structurings using SODA which provide rich detail into this application area. Multi-attribute additive models are constructed, with attribute partial value functions elicited using different methods: directly (bisection methods), indirectly (MACBETH and linear interpolation) and with discrete choice experiments. The applicability and advantages of each method is discussed. Additionally, an open source R package to implement the design of discrete choice experiments is created. The multi-attribute models provide key insights into decision maker's reasoning for price; and contrasting different decision maker's models explains the market. A risk adverse relationship between multicriteria model score and price is characterised and various inverse utility functions investigated. Two decision support systems are fully developed to address the needs of Cape silver decision makers in South Africa.

This dissertation first presents an uniprocessor real-time scheduling algorithm called the Generic Benefit Scheduling algorithm (or GBS). GBS solves a previously open real-time scheduling problem: scheduling activities subject to arbitrarily shaped, time/utility function (TUF) time constraints and mutual exclusion resource constraints. A TUF specifies the utility of completing an application activity as an application- or situation-specific function of when that activity completes. GBS considers the scheduling objective of maximizing system-wide, total accrued utility, while respecting mutual exclusion constraints. Since this problem is NP-hard, GBS heuristically computes schedules in polynomial-time. The performance of the GBS algorithm is evaluated through simulation and through an implementation on a Portable Operating System Interface (POSIX)-compliant real-time operating system. The simulation studies and implementation measurements reveal that GBS performs close to, if not better than existing algorithms for the cases that they apply. Further, the results verify the effectiveness of GBS for its unique model. We also analytically establish timeliness and non-timeliness properties of GBS including bounds on activity utilities and mutual exclusion. GBS targets real-time systems that are subject to significant non-determinism inherent in their operating environments e.g., completely unknown activity arrivals. When system uncertainties can be stochastically characterized (e.g., stochastic activity arrivals and execution times), it is possible to provide stochastic assurances on timeliness behavior. The dissertation also presents algorithmic solutions to fundamental assurance problems in TUF-driven real-time systems, including stochastically satisfying individual, activity utility lower bounds and system-wide, total utility lower bounds. The algorithmic solutions include algorithms for processor bandwidth allocation and TUF scheduling. While bandwidth allocation algorithms allocate processor bandwidth share to activities to satisfy utility lower bounds, TUF scheduling algorithms schedule activities to maximize accrued utility. The algorithmic solutions and analysis are extended with a class of lock-free and lock-based resource access protocols to satisfy mutual exclusion constraints. We show that satisfying utility lower bounds with lock-based resource access protocols does not imply doing so with the lock-free scheme, and vice versa. Finally, the dissertation presents a rule-based framework for trading off assurance requirements on utility lower bound satisfaction. / Ph. D.

In this dissertation, we consider the problem of scheduling and synchronization of distributable real-time threads --- Real-Time CORBA's first-class abstraction for programming real-time, multi-node sequential behaviors. Distributable real-time threads can be scheduled, broadly, using two paradigms: node independent scheduling, in which nodes independently construct thread schedules, based on node-level decomposition of distributable thread (or DT) scheduling parameters, and collaborative scheduling, in which nodes collaborate to construct system-wide thread schedules, which may or may not involve scheduling parameter decomposition. While significant literature exists on node independent scheduling, little is known about collaborative scheduling and its concomitant tradeoffs. We design three collaborative scheduling algorithms, called ACUA, QBUA, and DQBUA. ACUA uses theory of consensus and QBUA uses theory of quorums for distributable thread schedule construction. DQBUA extends QBUA with lock-based, local and distributed concurrency control. The algorithms consider a model where distributable threads arrive arbitrarily, have time/utility function time constraints, access resources in an arbitrary way (e.g., arbitrary lock acquire/release order, arbitrary nestings), and are subject to arbitrary node crash failures and message losses. We analytically establish several properties of the algorithms including probabilistic end-to-end termination time satisfactions, timeliness optimality during underloads, bounded exception handling time, and correctness of the algorithms in partially synchronous systems. We implement distributable real-time threads in the Linux kernel as a first-class programming and scheduling abstraction. The resulting kernel, called ChronOS, provides application interfaces for creating and manipulating distributable threads, as well as kernel interfaces and mechanisms for scheduling them (using both independent and collaborative approaches). ChronOS also has failure detector mechanisms for detecting and recovering from distributable thread failures. We implement the proposed scheduling algorithms and their competitors in ChronOS and compare their behavior. Our studies reveal that the collaborative scheduling algorithms are superior to independent scheduling algorithms for certain thread sets, in particular, when thread sections have significantly varying execution time. This variability, especially if the variability is not consistent among the threads, may cause each node to make conflicting decisions in the absence of global information. We observe that collaborative schedulers outperform independent schedulers (e.g., EDF augmented with PIP) in terms of accrued utility by as much as 75%. We identify distributed dependencies as one of the major sources of overhead in collaborative scheduling. In particular, the cost of distributed lock-based concurrency control (e.g., lock management, distributed deadlock detection/resolution) can significantly reduce the problem space for which collaborative scheduling is beneficial. To mitigate this, we consider the use of software transactional memory (or STM), an optimistic, non-blocking synchronization alternative to lock-based concurrency control which has been extensively studied in non real-time contexts. We consider distributable real-time threads with STM concurrency control, and develop techniques for analyzing and bounding their end-to-end response times on distributed single-processor and distributed multiprocessor systems. We also develop contention management techniques, a key component of STM, which are driven by threads' real-time scheduling parameters, and establish their tradeoffs against non-real-time contention managers. / Ph. D.

This dissertation presents a class of utility accrual scheduling and synchronization algorithms for dynamic, single and multiprocessor real-time systems. Dynamic real-time systems operate in environments with run-time uncertainties including those on activity execution times and arrival behaviors. We consider the time/utility function (or TUF) timing model for specifying application time constraints, and the utility accrual (or UA) timeliness optimality criteria of satisfying lower bounds on accrued activity utility, and maximizing the total accrued utility. Efficient TUF/UA scheduling algorithms exist for single processors---e.g., the Resource-constrained Utility Accrual scheduling algorithm (RUA), and the Dependent Activity Scheduling Algorithm (DASA). However, they all use lock-based synchronization. To overcome shortcomings of lock-based (e.g., serialized object access, increased run-time overhead, deadlocks), we consider non-blocking synchronization including wait-free and lock-free synchronization. We present a buffer-optimal, scheduler-independent wait-free synchronization protocol (the first such), and develop wait-free versions of RUA and DASA. We also develop their lock-free versions, and upper bound their retries under the unimodal arbitrary arrival model. The tradeoff between wait-free, lock-free, and lock-based is fundamentally about their space and time costs. Wait-free sacrifices space efficiency in return for no additional time cost, as opposed to the blocking time of lock-based and the retry time of lock-free. We show that wait-free RUA/DASA outperform lock-based RUA/DASA when the object access times of both approaches are the same, e.g., when the shared data size is so large that the data copying process dominates the object access time of two approaches. We derive lower bounds on the maximum accrued utility that is possible with wait-free over lock-based. Further, we show that when maximum sojourn times under lock-free RUA/DASA is shorter than under lock-based, it is a necessary condition that the object access time of lock-free is shorter than that of lock-based. We also establish the maximum increase in activity utility that is possible under lock-free and lock-based. Multiprocessor TUF/UA scheduling has not been studied in the past. For step TUFs, periodic arrivals, and under-loads, we first present a non-quantum-based, optimal scheduling algorithm called Largest Local Remaining Execution time-tasks First (or LLREF) that yields the optimum total utility. We then develop another algorithm for non-step TUFs, arbitrary arrivals, and overloads, called the global Multiprocessor Utility Accrual scheduling algorithm (or gMUA). We show that gMUA lower bounds each activity's accrued utility, as well as the system-wide, total accrued utility. We consider lock-based, lock-free, and wait-free synchronization under LLREF and gMUA. We derive LLREF's and gMUA's minimum-required space cost for wait-free synchronization using our space-optimal wait-free algorithm, which also applies for multiprocessors. We also develop lock-free versions of LLREF and gMUA with bounded retries. While the tradeoff between wait-free LLREF/gMUA versus lock-based LLREF/gMUA is similar to that for the single processor case, that between lock-free LLREF/gMUA and lock-based LLREF/gMUA hinges on the cost of the lock-free retry, blocking time under lock-based, and the operating system overhead. / Ph. D.

We consider the problem of scheduling real-time tasks on a multiprocessor system. Our primary focus is scheduling on multiprocessor systems where the total task utilization demand, U, is greater than m, the number of processors on a multiprocessor system---i.e., the total available processing capacity of the system. When U > m, the system is said to be overloaded; otherwise, the system is said to be underloaded. While significant literature exists on multiprocessor real-time scheduling during underloads, little is known about scheduling during overloads, in particular, in the presence of task dependencies---e.g., due to synchronization constraints. We consider real-time tasks that are subject to time/utility function (or TUF) time constraints, which allow task urgency to be expressed independently of task importance---e.g., the most urgent task being the least important. The urgency/importance decoupling allowed by TUFs is especially important during overloads, when not all tasks can be optimally completed. We consider the timeliness optimization objective of maximizing the total accrued utility and the number of deadlines satisfied during overloads, while ensuring task mutual exclusion constraints and freedom from deadlocks. This problem is NP-hard. We develop a class of polynomial-time heuristic algorithms, called the Global Utility Accrual (or GUA) class of algorithms. The algorithms construct a directed acyclic graph representation of the task dependency relationship, and build a global multiprocessor schedule of the zero in-degree tasks to heuristically maximize the total accrued utility and ensure mutual exclusion. Potential deadlocks are detected through a cycle-detection algorithm, and resolved by aborting a task in the deadlock cycle. The GUA class of algorithms include two algorithms, namely, the Non-Greedy Global Utility Accrual (or NG-GUA) and Greedy Global Utility Accrual (or G-GUA) algorithms. NG-GUA and G-GUA differ in the way schedules are constructed towards meeting all task deadlines, when possible to do so. We establish several properties of the algorithms including conditions under which all task deadlines are met, satisfaction of mutual exclusion constraints, and deadlock-freedom. We create a Linux-based real-time kernel called ChronOS for multiprocessors. ChronOS is extended from the PREEMPT_RT real-time Linux patch, which provides optimized interrupt service latencies and real-time locking primitives. ChronOS provides a scheduling framework for the implementation of a broad range of real-time scheduling algorithms, including utility accrual, non-utility accrual, global, and partitioned scheduling algorithms. We implement the GUA class of algorithms and their competitors in ChronOS and conduct experimental studies. The competitors include G-EDF, G-NP-EDF, G-FIFO, gMUA, P-EDF and P-DASA. Our study reveals that the GUA class of algorithms accrue higher utility and satisfy greater number of deadlines than the deadline-based scheduling algorithms by as much as 750% and 600%, respectively. In addition, we observe that G-GUA accrues higher utility than NG-GUA during overloads by as much as 25% while NG-GUA satisfies greater number of deadlines than G-GUA by as much as 5% during underloads. / Master of Science

Yes / With China being the world’s largest emitter of greenhouse gases and its aviation sector burgeoning, the environmental performance of Chinese airlines has global significance. Amidst rising demands for eco-friendly practices from both customers and regulators, the interplay between airport infrastructure and environmental performance becomes pivotal. This research offers an innovative methodology to gauge the environmental performance of Chinese airlines, emphasizing the distance traveled between airports using weighted additive utility functions. Leveraging neural networks, the study investigates the impact of various airport infrastructural characteristics on environmental performance. Noteworthy findings indicate that ground control measures, automatic information services at origin airports, surface concrete on runways at both ends, and a centerline lighting system in destination airports positively influence environmental performance. In contrast, longer and wider runways at origin airports, increased distances to control towers, and asphalt runways at destination airports adversely affect it. These insights not only underscore the importance of strategic infrastructure enhancements for reducing carbon footprints but also hold profound policy implications. As global climate change remains at the forefront, fostering sustainable airport infrastructure in China can significantly contribute to worldwide mitigation efforts. / The full-text of this article will be released for public view at the end of the publisher embargo on 18 Jan 2025.

Nesta tese desenvolvemos modelos de apreçamento de ativos financeiros baseados no conceito de influência social, analisamos também algumas das consequências destes modelos e comparamos com os modelos correspondentes clássicos. Por meio das funções de utilidade generalizadas exponencial e quadrática, deduzimos o CAPM com influência social. Obtivemos que o coeficiente beta da fórmula do CAPM depende de uma aversão ao risco efetiva do mercado que depende da distribuição de riqueza dos agentes do mercado. Supondo que distribuição de riqueza dos agentes do mercado segue uma distribuição de Pareto, fomos capazes de conectar, aversão ao risco média efetiva do mercado, volatilidade e distribuição de riqueza dos agentes, estabelecendo a previsão empírica de que a volatilidade aumenta com a concentração da distribuição de riqueza dos agentes do mercado, a qual foi corroborada por meio de análise estatística. Através da função generalizada tipo potência são feitas algumas considerações sobre alguns \"puzzles\" econômicos bem conhecidos (o \"Equity Premium Puzzle\" e o \"Riskfree Rate Puzzle\") que mostram que a modelagem da influência social pode ter impacto no esclarecimento destes \"puzzles\". / In this thesis we develop pricing models for financial assets based in the concept of social influence, we analyze too some of consequences of this models and we compare with the corresponding classical models. By means of the exponential and quadratic generalized utility functions, we deduce the CAPM with social influence. We obtained that the coefficient beta from the formula of the CAPM depends of a market effective risk aversion that depends of the wealth distribution of the market agents. Supposing that the wealth distribution of the market agents follows a Pareto distribution, we were able to connect, market effective average risk aversion, volatility and wealth distribution of the agents, establishing the empirical forecasting that the volatility grows with the concentration of the wealth distribution of the market agents, which was corroborated by means of statistical analysis. Through the generalized power function are made some considerations about some economic puzzles well-known (the Equity Premium Puzzle and the Riskfree Rate Puzzle) that show us that the modeling of the social influence can to have impact in the clarification these puzzles.

Nesta tese desenvolvemos modelos de apreçamento de ativos financeiros baseados no conceito de influência social, analisamos também algumas das consequências destes modelos e comparamos com os modelos correspondentes clássicos. Por meio das funções de utilidade generalizadas exponencial e quadrática, deduzimos o CAPM com influência social. Obtivemos que o coeficiente beta da fórmula do CAPM depende de uma aversão ao risco efetiva do mercado que depende da distribuição de riqueza dos agentes do mercado. Supondo que distribuição de riqueza dos agentes do mercado segue uma distribuição de Pareto, fomos capazes de conectar, aversão ao risco média efetiva do mercado, volatilidade e distribuição de riqueza dos agentes, estabelecendo a previsão empírica de que a volatilidade aumenta com a concentração da distribuição de riqueza dos agentes do mercado, a qual foi corroborada por meio de análise estatística. Através da função generalizada tipo potência são feitas algumas considerações sobre alguns \"puzzles\" econômicos bem conhecidos (o \"Equity Premium Puzzle\" e o \"Riskfree Rate Puzzle\") que mostram que a modelagem da influência social pode ter impacto no esclarecimento destes \"puzzles\". / In this thesis we develop pricing models for financial assets based in the concept of social influence, we analyze too some of consequences of this models and we compare with the corresponding classical models. By means of the exponential and quadratic generalized utility functions, we deduce the CAPM with social influence. We obtained that the coefficient beta from the formula of the CAPM depends of a market effective risk aversion that depends of the wealth distribution of the market agents. Supposing that the wealth distribution of the market agents follows a Pareto distribution, we were able to connect, market effective average risk aversion, volatility and wealth distribution of the agents, establishing the empirical forecasting that the volatility grows with the concentration of the wealth distribution of the market agents, which was corroborated by means of statistical analysis. Through the generalized power function are made some considerations about some economic puzzles well-known (the Equity Premium Puzzle and the Riskfree Rate Puzzle) that show us that the modeling of the social influence can to have impact in the clarification these puzzles.

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In this dissertation, we consider timeliness and energy optimization in battery-powered, mobile embedded real-time systems. We focus on real-time systems that operate in environments with dynamically uncertain properties, including context-dependent activity execution times and arbitrary activity arrival patterns. We consider an application model where activities are subject to time/utility function (or TUF) time constraints, mutual exclusion constraints on concurrent sharing of non-CPU resources, timeliness requirements including assurances on individual activity timeliness behavior, and system-level energy consumption requirements including a non-exhaustable energy budget. To account for uncertainties in activity properties in dynamic systems, we stochastically describe activity execution demands, and describe activity arrival behaviors using the unimodal arbitrary arrival model, which allows unbounded arrival frequencies. We consider the scheduling optimality criteria of: (1) probabilistically satisfying lower bounds on individual activities' maximal timeliness utilities, and (2) maximizing system-level energy efficiency, while ensuring that the system's energy consumption never exhausts the energy budget and resource mutual exclusion constraints are satisfied. For this multi-criteria scheduling problem, we present a DVS (dynamic voltage scaling)-based, real-time scheduling algorithm called the Energy-Bounded Utility Accrual Algorithm (or EBUA). Since the scheduling problem is NP-hard, EBUA heuristically (and dynamically) allocates CPU cycles to activities, computes activity schedules, and scales CPU voltage and frequency with a polynomial-time cost. If activities' cumulative execution demands exceed the available CPU time or may exhaust the system's energy budget, the algorithm defers and rejects jobs in a controlled fashion, minimizing system-level energy consumption and maximizing total accrued utility. We analytically establish several properties of EBUA. We prove that the algorithm never exhausts the specified energy budget. Further, we establish EBUA's timeliness optimality during under-loads, freedom from deadlocks, and correctness in mutually exclusive resource sharing. In particular, we prove that the algorithm's timeliness behavior subsumes the optimal timeliness behavior of deadline scheduling as a special case, and identify the conditions under which lower bounds on individual activity utilities are satisfied. In addition, we upper bound the time needed for mutually exclusively accessing shared resources under EBUA. We conduct experimental studies by simulating the algorithm on the DVS-enabled AMD k6 processor model, and by implementing it on QNX Neutrino 6.2.1 RTOS. Our experimental results validate our analytical results. Further, they confirm EBUA's superiority over other energy-efficient real-time scheduling algorithms on timeliness and energy consumption behaviors. / Ph. D.