We develop an extension to the tactical planning model (TPM) for a job shop by the third author. The TPM is a discrete-time model in which all transitions occur at the start of each time period. The time period must be defined appropriately in order for the model to be meaningful. Each period must be short enough so that a job is unlikely to travel through more than one station in one period. At the same time, the time period needs to be long enough to justify the assumptions of continuous workflow and Markovian job movements. We build an extension to the TPM that overcomes this restriction of period sizing by permitting production control over shorter time intervals. We achieve this by deriving a continuous-time linear control rule for a single station. We then determine the first two moments of the production level and queue length for the workstation. / Singapore-MIT Alliance (SMA)

Idrottsparken roundabout in Norrkoping is located in the more dense part of the city.Congestion occurs in peak hours causing queue and extended travel time. This thesis aims to provide alternative model to reduce queue and travel time. Types ofobservation data are flow, length of queue, and travel time that are observed during peakhours in the morning and afternoon. Calibration process is done by minimising root meansquare error of queue, travel time, and combination both of them between observation andcalibrated model. SUMO version 0.14.0 is used to perform the microsimulation. There are two proposed alternatives, namely Scenario 1: the additional lane for right turnfrom East leg to North and from North leg to West and Scenario 2: restriction of heavy goodsvehicles passing Kungsgatan which is located in Northern leg of Idrottsparken roundaboutduring peak hours. For Scenario 1, the results from SUMO will be compared with AIMSUNin terms of queue and travel time. The result of microsimulation shows that parameters that have big influence in the calibrationprocess for SUMO are driver imperfection and driver’s reaction time, while for AIMSUN isdriver’s reaction time and maximum acceleration. From analysis found that the model of thecurrent situation at Idrottsparken can be represented by model simulation which usingcombination between root mean square error of queue and travel time in calibration andvalidation process. Moreover, scenario 2 is the best alternative for SUMO because itproduces the decrease of queue and travel time almost in all legs at morning and afternoonpeak hour without accompanied by increase significant value of them in the other legs. Thecomparison between SUMO and AIMSUN shows that, in general, the AIMSUN has higherchanges value in terms of queue and travel time due to the limited precision in SUMO forroundabout modelling.

Cette thèse présente de nouveaux modèles et de nouveaux résultats en théorie de la ruine, lorsque les distributions des montants de sinistres sont à queue épaisse. Les hypothèses classiques d'indépendance et de stationnarité, ainsi que l'analyse univariée sont parfois jugées trop restrictives pour décrire l'évolution complexe des réserves d'une compagnie d'assurance. Dans un contexte de dépendance entre les montants de sinistres, des équivalents de la probabilité deruine univariée en temps fini sont obtenus. Cette dépendance, ainsi que les autres paramètres du modèle sont modulés par un processus Markovien d'environnement pour prendre en compte des possibles crises de corrélation. Nous introduisons ensuite des modèles de dépendance entre les montants de sinistres et les temps inter-sinistres pour des risques de type tremblements de terre et inondations. Dans un cadre multivarié, nous présentons divers critères de risques tels que la probabilité de ruine multivariée ou l'espérance de l'intégrale temporelle de la partie négative du processus de risque. Nous résolvons des problèmes d'allocation optimale pour ces différentes mesures de risque. Nous étudions alors l'impact de la dangerosité des risques et de la dépendance entre les branches sur cette allocation optimale

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In the past 10 years, the bandwidths and processing capabilities of the networks have increased dramatically. The number of real-time applications using these networks has also increased. The large number of real-time packets might, in a switched multi-hop network, lead to unpredictable traffic patterns. This is not a problem when the traffic intensity is low, but if the same network is used by a large number of users simultaneously, the overall performance of the network degrades. In fact, unpredictable delays in the delivery of the message can adversely affect the execution of the tasks dependent on these messages, even if we take into account the soft real-time performance. In this paper, we investigate the effect of traffic shapers on soft real-time performance. We will consider a switched multi-hop network with FCFS queues. We will implement two versions of the network simulator. One version will be without traffic shaper and the other version will use a traffic shaper. By comparing the results (for average delay, deadline miss ratio etc.) from both the versions, we will try to conclude if it is really beneficial to use traffic shapers for soft real-time performance. Leaky bucket and token bucket algorithms are the most popular ones for traffic shaper implementation. We will consider leaky bucket algorithm for our analysis. We analyse different versions of the leaky bucket and present the trade-off’s involved.

Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, due to financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP prior to implementation in order to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated using microscopic simulation models. However, the application of these models is resource intensive and requires specialized expertise that is often not available in-house to transit agencies. In this thesis, an analytical model was proposed for estimating the delay impacts of green extension and early green (red truncation) TSP strategies. The proposed model is validated with analytical model reported in the literature and microscopic simulation model. This is followed by model sensitivity analysis. A software module is developed using the proposed model. The usefulness of the model is illustrated through its application to estimate the TSP performance. Finally, a prioritization is conducted on sixteen intersections with different geometric and operational traffic strategies. The overall results indicate that the proposed model is suitable for both estimating the pre-deployment and post-deployment TSP performance. The proposed model is suitable for implementation within a spreadsheet and requires considerably less effort, and less technical expertise, to apply than a typical micro-simulation model and therefore is a more suitable tool for transit agencies to use for prioritising TSP deployment.

The seminal paper by Gerber and Shiu (1998) gave a huge boost to the study of risk theory by not only unifying but also generalizing the treatment and the analysis of various risk-related quantities in one single mathematical function - the Gerber-Shiu expected discounted penalty function, or Gerber-Shiu function in short. The Gerber-Shiu function is known to possess many nice properties, at least in the case of the classical compound Poisson risk model. For example, upon the introduction of a dividend barrier strategy, it was shown by Lin et al. (2003) and Gerber et al. (2006) that the Gerber-Shiu function with a barrier can be expressed in terms of the Gerber-Shiu function without a barrier and the expected value of discounted dividend payments. This result is the so-called dividends-penalty identity, and it holds true when the surplus process belongs to a class of Markov processes which are skip-free upwards. However, one stringent assumption of the model considered by the above authors is that all the interclaim times and the claim sizes are independent, which is in general not true in reality. In this thesis, we propose to analyze the Gerber-Shiu functions under various dependent structures. The main focus of the thesis is the risk model where claims follow a Markovian arrival process (MAP) (see, e.g., Latouche and Ramaswami (1999) and Neuts (1979, 1989)) in which the interclaim times and the claim sizes form a chain of dependent variables. The first part of the thesis puts emphasis on certain dividend strategies. In Chapter 2, it is shown that a matrix form of the dividends-penalty identity holds true in a MAP risk model perturbed by diffusion with the use of integro-differential equations and their solutions. Chapter 3 considers the dual MAP risk model which is a reflection of the ordinary MAP model. A threshold dividend strategy is applied to the model and various risk-related quantities are studied. Our methodology is based on an existing connection between the MAP risk model and a fluid queue (see, e.g., Asmussen et al. (2002), Badescu et al. (2005), Ramaswami (2006) and references therein). The use of fluid flow techniques to analyze risk processes opens the door for further research as to what types of risk model with dependency structure can be studied via probabilistic arguments. In Chapter 4, we propose to analyze the Gerber-Shiu function and some discounted joint densities in a risk model where each pair of the interclaim time and the resulting claim size is assumed to follow a bivariate phase-type distribution, with the pairs assumed to be independent and identically distributed (i.i.d.). To this end, a novel fluid flow process is constructed to ease the analysis. In the classical Gerber-Shiu function introduced by Gerber and Shiu (1998), the random variables incorporated into the analysis include the time of ruin, the surplus prior to ruin and the deficit at ruin. The later part of this thesis focuses on generalizing the classical Gerber-Shiu function by incorporating more random variables into the so-called penalty function. These include the surplus level immediately after the second last claim before ruin, the minimum surplus level before ruin and the maximum surplus level before ruin. In Chapter 5, the focus will be on the study of the generalized Gerber-Shiu function involving the first two new random variables in the context of a semi-Markovian risk model (see, e.g., Albrecher and Boxma (2005) and Janssen and Reinhard (1985)). It is shown that the generalized Gerber-Shiu function satisfies a matrix defective renewal equation, and some discounted joint densities involving the new variables are derived. Chapter 6 revisits the MAP risk model in which the generalized Gerber-Shiu function involving the maximum surplus before ruin is examined. In this case, the Gerber-Shiu function no longer satisfies a defective renewal equation. Instead, the generalized Gerber-Shiu function can be expressed in terms of the classical Gerber-Shiu function and the Laplace transform of a first passage time that are both readily obtainable. In a MAP risk model, the interclaim time distribution must be phase-type distributed. This leads us to propose a generalization of the MAP risk model by allowing for the interclaim time to have an arbitrary distribution. This is the subject matter of Chapter 7. Chapter 8 is concerned with the generalized Sparre Andersen risk model with surplus-dependent premium rate, and some ordering properties of certain ruin-related quantities are studied. Chapter 9 ends the thesis by some concluding remarks and directions for future research.

Channel access fairness and efficiency in capacity utilization are the two main objectives for Quality of Service (QoS) specific to Medium Access Control (MAC) protocols in computer networks. For bursty and unpredictable traffic in networks, fairness and efficiency involve a mutual tradeoff with the currently popular QoS mechanisms. We propose a QoS MAC framework for carrier sensing multiple access (CSMA) networks, that achieves fairness with improved efficiency through extensive state-keeping based on the MAC evolution. This CSMA with Implicit Scheduling through State-keeping (CSMA/ISS) framework involves the tracking of traffic arrival at active nodes, the nodes that need channel access frequently. It also involves implicit channel access grants to different active nodes according to their estimated queue backlogs and the fair scheduling requirements. These methods save channel capacity that may otherwise be required for disseminating the access requirements of various nodes, and their access rights according to fairness rules. A static, hierarchical, and weighted fair access scheme is designed in CSMA/ISS by allowing repeated rounds of access that are weighted fairly according to requirements. Weighted fairness across classes is achieved by invoking channel access for each traffic class in a round as many times as its weight. Within each class, all active nodes are allowed equal access through in-order channel access based on a looped list of active nodes. Although CSMA/ISS is proposed as a distributed control framework for efficiency, it may also be employed in central control protocols. It may also be adapted to different types of CSMA networks, both wireless and wired, by an appropriate choice of the underlying classical access mechanism. The CSMA/ISS framework was modeled and simulated as a QoS capable MAC protocol for a wired fully connected local network environment. We present the CSMA/ISS framework, the example implementation, and the results of performance evaluation of the example implementation. Significant performance improvements were observed, and the memory and processing trade-off was found to be low to moderate.

Differentiated-Service networks is designed for solving scalability problems through traffic aggregation. However, it can't guarantee end-to-end QoS of individual flow. In this thesis, we propose a Self-Adaptive Control Scheme for Differentiated-Service networks that can improve the throughput of individual flows dynamically. In this scheme, egress routers monitor the average throughput of individual flow, and send the Self-Adaptive Control Messages to ingress routers if need. The ingress router re-allocate network resources to improve throughput of high-priority flows depending on the Control Messages. We use NS-2 simulator to prove that our scheme that can improve throughput of high-priority flows dynamically, and suggest that a better time interval of Self-Adaptive control can be determined based on the queue sizes, packets arrival rate and departure rate. Finally, we use Random Early Detection (RED) queue instead of Drop-Tail queue to reduce unfairness of individual flows when there are congestion and insufficient network resources.

It is essential for the managers to make investment on hardware based on the utilization information of the equipment. From December 2014, a pool of hardware and a scheduling and resource sharing system is implemented by one of the software testing sections in Ericsson. To monitor the efficiency of these equipment and the workflow, a model of non-homogeneous M/M/c queue is developed that successfully captures the main aspects of the system. The model is decomposed into arrival, service, failure and each part is estimated. Mixture exponential is estimated with EM algorithm and the impact of scheduling change is also examined. Finally a simulation of workflow is done with Python module and the optimized number of hardware is proposed based on this M/M/c queue system.