Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 71-72). Also available via the Internet.

Thesis (Ph. D.)--University of North Texas, Dec., 2007. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.) -- California Institute of Technology, 2010. / Title from home page (viewed 06/21/2010). Advisor and committee chair names found in the thesis' metadata record in the digital repository. Includes bibliographical references.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 50-52). Also available in electronic version.

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.

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

No description available.

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.

<p>In this work we examine a state constrained resource allocation model a with finite time horizon. Therefore, we use the necessary conditions of the Pontrjagin's Maximum Principle to find candidates for the solution and verify them later on using the sufficient conditions given by the duality concept of Klötzler. Moreover, we proof that the solution of the corresponding infinite horizon model does not fulfill the overtaking criterion of Weizsäcker.</p>