A fair and optimal mechanism is required for allocating bandwidth to virtual machine migration in a WAN environment. In this thesis, we propose a dynamic resource allocation algorithm running in either centralized or distributed environments. The centralized version of our algorithm collects information from individual users and dynamically allocates bandwidth according to their demands. The distributed version of our algorithm is running on the internal nodes (e.g. routers) in the network. In the distributed case, we show that even when the routers and the users do not exchange allocation information, the allocation is still stable and optimal if the users are elastic users. Another interesting problem we solved is emergency handling, which is also critical in virtual machine live migration.

Encouraging positive work team growth depends on, in part, the form and availability of organizational resources and support. Support systems have been found to be important for work team health and survival. However, managers are challenged to make resource decisions while working within company budgetary restraints. Previous research has indicated a positive relationship exists between teams provided with appropriate resources and support, and increased team performance. This study extended previous research by exploring if team performance can predict resources and support. Specifically, the means by which managers allocate resources based on team performance was examined. Archival data included 36 work teams and their managers drawn from four geographically dispersed manufacturing companies. Information gathered from a modified version of an original team support system instrument was used to assess the importance and presence of four resource systems. Additionally, a gap score was calculated from these scores to assess the alignment between resource need and resource existence. Data was used to assess the potential relationships between managers' perceptions of team performance and the manner by which resources are allocated. All hypotheses produced non-significant findings. Results of the hypotheses, data patterns, and limitations of the study are discussed, and opportunities for future research are presented.

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The Generalized Matching Equation (GME) has been utilized by many behavioral researchers as a model of operant choice, especially in elite sports. In this instance, the GME was used to analyze the penalty-kick selections (e.g., shoot right or shoot left) of nine elite international soccer players. The analysis of archival data from in-game decisions demonstrated the presence of matching across participants and within a naturalistic setting. Undermatching consistent with previous laboratory and non-laboratory research on the matching law was also observed. The GME accounted for a majority of variance in penalty-kick selection, with minimal bias in responding. The players’ choices did not demonstrate clear preferences for shooting at either side of the goal, but did expose trends in individual responding worth noting. While the results extend the research literature regarding the applicability of GME to professional sports, future research should investigate matching relationships through analyzing larger sample sizes, team-wide responses, and team outcomes. / Applied Behavioral Analysis

Subcontractors perform the majority of the work on commercial construction projects. However, only limited research has focused on subcontractors’ practical needs. In response, this research discovered and documented subcontractor needs through data collections and extended these findings with development of an information model and tool. This research significantly enlarges detailed understanding of subcontractor management practices, in particular around resource allocation across multiple projects. While existing research has shown the importance of multi-project management, exploration of details of this process has largely been limited to overviews of policies. Rich details that allow for specific critiques of existing methods and tools have been missing. This research provides such details, including specific limitations and recommendations to existing information standards, commercial applications, and assignment algorithms. In particular, contributions of this research focus on support for what-if analysis under extreme frequency of resource reallocation, a limitation of existing tools and methods that make them unsuitable for most subcontractors. / text

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In this dissertation, we discuss throughput-optimal scheduling design in multiuser wireless networks. Throughput-optimal scheduling algorithm design in wireless systems with flow-level dynamics is a challenging open problem, especially considering that the majority of the Internet traffic are short-lived TCP controlled flows. In future wireless networks supporting machine-to-machine and human-to-human applications, both short-lived dynamic flows and long-lived persistent flows coexist. How to design the throughput-optimal scheduling algorithm to support dynamic and persistent flows simultaneously is a difficult and important unsolved problem. Our work starts from how to schedule short-lived dynamic flows in wireless systems to achieve throughput-optimality with queue stability. Classic throughput-optimal scheduling algorithms such as the Queue-length based Maxweight scheduling algorithm (QMW) cannot stabilize systems with dynamic flows in practical communication networks. We propose the Head-of-Line (HOL) access delay based scheduling algorithm (HAD) for flow-level dynamic systems, and show that HAD is able to obtain throughput-optimality which is validated by simulation. As the Transmission Control Protocol (TCP) is the dominant flow and congestion control protocol for the Internet nowadays, we turn our attention to the compatibility between throughput-optimal schedulers and TCP. Most of the existing throughput-optimal scheduling algorithms have encountered unfairness problem in supporting TCP-controlled flows, which leads to undesirable network performance. Motivated by this, we first reveal the reason of the unfairness problem, then study the compatibility between HAD and TCP with different channel assumptions, and finally analyze the mean throughput performance of HAD. The result shows that HAD is compatible with TCP. Since the assumption of an infinite buffer size in the existing theoretical analysis of throughput-optimality is not practical, we analyze the queueing behaviour of the proposed throughput-optimal scheduling algorithm to provide useful guidelines for real system design by using the Markov chain analytic model. We propose the analytic model for the queuing and delay performance for the HAD scheduler, and then further develop an approximation approach to reduce the complexity of the model. Finally, we propose a throughput-optimal scheduling algorithm for hybrid wireless systems with the coexistence of persistent and dynamic flows. Then, to generalize the throughput-optimal scheduling, the control function in the scheduling rule is extended from a specific one to a class of functions, so that the scheduling design can be more flexible to make a tradeoff between delay, fairness, etc. We show that the hybrid wireless networks with coexisting persistent flows and dynamic flows can be stabilized by our proposed scheduling algorithm which can obtain throughput-optimality. In summary, we solve the challenging problem of designing throughput-optimal scheduling algorithm in wireless systems with flow-level dynamics. Then we show that our algorithm can support TCP regulated flows much better than the existing throughput-optimal schedulers. We further analyze the queueing behaviour of the proposed algorithm without the assumption of infinite buffer size that is often used in the throughput-optimality analysis in the literature, and the result provides a guideline for the implementation of our algorithm. At last, we generalize the proposed scheduling algorithm to support different types of flows simultaneously in practical wireless networks. / Graduate / chenyi.nwpu@gmail.com

Dynamic resource allocation problems are everywhere. Airlines reserve flight seats for those who purchase flight tickets. Healthcare facilities reserve appointment slots for patients who request them. Freight carriers such as motor carriers, railroad companies, and shipping companies pack containers with loads from specific origins to destinations. We focus on optimizing such allocation problems where resources need to be assigned to customers in real time. These problems are particularly difficult to solve because they depend on random external information that unfolds gradually over time, and the number of potential solutions is overwhelming to search through by conventional methods. In this dissertation, we propose viable allocation algorithms for industrial use, by fully leveraging data and technology to produce gains in efficiency, productivity, and usability of new systems. The first chapter presents a summary of major methodologies used in modeling and algorithm design, and how the methodologies are driven by the size of accessible data. Chapters 2 to 5 present genuine research results of resource allocation problems that are based on Wang and Truong (2017); Wang et al. (2015); Stein et al. (2017); Wang et al. (2016). The algorithms and models cover problems in multiple industries, from a small clinic that aims to better utilize its expensive medical devices, to a technology giant that needs a cost-effective, distributed resource-allocation algorithm in order to maintain the relevance of its advertisements to hundreds of millions of consumers.

Avec l’émergence rapide des applications Internet, il est prévu que le trafic mobile mondial augmente de huit fois entre fin 2018 et 2022. En même temps, les futurs systèmes de communication se devront aussi d’améliorer l'efficacité spectrale des transmissions, le temps de latence et l’équité entre utilisateurs. À cette fin, une technique d’accès multiple non orthogonal (NOMA) a été récemment proposée comme un candidat prometteur pour les futurs accès radio. La technique NOMA est basée sur un nouveau domaine de multiplexage, le domaine des puissances. Elle permet la cohabitation de deux ou plusieurs utilisateurs par sous-porteuse ou sous-bande de fréquence. Cette thèse aborde plusieurs problèmes liés à l’allocation de ressources basée sur NOMA afin d'améliorer les performances du réseau en termes d'efficacité spectrale, de débit et/ou d’équité entre utilisateurs. Dans ce sens, des solutions théoriques et algorithmiques sont proposées et des résultats numériques sont obtenus afin de valider les solutions et de vérifier la capacité des algorithmes proposés à atteindre des performances optimales ou sous-optimales. Après une étude bibliographique des différentes techniques d’allocation de ressources présentée dans le premier chapitre, on propose dans le deuxième chapitre plusieurs stratégies d’allocation de ressource où une réduction de la bande utilisée par les utilisateurs est ciblée. Les résultats de simulation montrent que les stratégies proposées améliorent à la fois l’efficacité spectrale et le débit total des utilisateurs par rapport aux systèmes basés uniquement sur des techniques d’accès orthogonales. Quant au troisième chapitre, il étudie la performance du Proportional Fairness (PF) Scheduler tout en considérant que la bande passante est disponible en totalité. Dans ce sens, plusieurs améliorations basées sur le PF sont proposées, qui offrent au système NOMA des avantages en termes de débit, d’équité entre utilisateurs et de qualité de service. Dans le quatrième chapitre, nous proposons plusieurs techniques d’allocation de ressources qui donnent aux utilisateurs la possibilité de favoriser le débit par rapport à l’équité entre utilisateurs et vice versa. Dans le dernier chapitre, différentes techniques permettant une transmission hybride broadcast/broadband sur la même bande de fréquence sont proposées et comparées à l’état de l’art. / With the proliferation of Internet applications, between the end of 2016 and 2022, total mobile traffic is expected to increase by 8 times. At the same time, communications networks are required to further enhance system efficiency, latency, and user fairness. To this end, non-orthogonal multiple access (NOMA) has recently emerged as a promising candidate for future radio access. By exploiting an additional multiplexing domain, the power domain, NOMA allows the cohabitation of two or more users per subcarrier, based on the principle of signal superposition. This dissertation addresses several radio resource allocation problems in mobile communication systems, in order to improve network performance in terms of spectral efficiency, through put, or fairness. Theoretical analysis and algorithmic solutions are derived. Numerical results are obtained to validate our theoretical findings and demonstrate the algorithms ability of attaining optimal or sub-optimal solutions. To this direction, the second chapter of this thesis investigates several new strategies for the allocation of radio resources (bandwidth and transmission power) using NOMA principle, where the minimization of the total amount of used bandwidth is targeted. Extensive simulation results show that the proposed strategies for resource allocation can improve both the spectral efficiency and the cell-edge user throughput, especially when compared to schemes employing only orthogonal signaling. A context where the total bandwidth is available has also been studied, in the 3rd chapter where we investigate the performance of the proportional fairness (PF) scheduler, and we propose modifications to it, at the level of user scheduling and power allocation that show to improve the system capacity, user fairness and QoS. In the 4th chapter, we proposed new pairing metrics that allow to favor the fairness at the expense of the throughput and vice versa. The proposed metrics show enhancements at the level of system capacity, user fairness, and computational complexity. Different techniques that allow a hybrid broadcast/multicast transmission on the same frequency platform are proposed in the last chapter and compared to the state of the art.