Scheduling for a Processor Sharing System with Linear Slowdown

We consider the problem of scheduling arrivals to a congestion system with a finite number of users having identical deterministic demand sizes. The congestion is of the processor sharing type in the sense that all users in the system at any given time are served simultaneously. However, in contrast to classical processor sharing congestion models, the processing slowdown is proportional to the number of users in the system at any time. That is, the rate of service experienced by all users is linearly decreasing with the number of users. For each user there is an ideal departure time (due date). A centralized scheduling goal is then to select arrival times so as to minimize the total penalty due to deviations from ideal times weighted with sojourn times. Each deviation is assumed quadratic, or more generally convex. But due to the dynamics of the system, the scheduling objective function is non-convex. Specifically, the system objective function is a non-smooth piecewise convex function. Nevertheless, we are able to leverage the structure of the problem to derive an algorithm that finds the global optimum in a (large but) finite number of steps, each involving the solution of a constrained convex program. Further, we put forward several heuristics. The first is the traversal of neighbouring constrained convex programming problems, that is guaranteed to reach a local minimum of the centralized problem. This is a form of a "local search", where we use the problem structure in a novel manner. The second is a one-coordinate "global search", used in coordinate pivot iteration. We then merge these two heuristics into a unified "local-global" heuristic, and numerically illustrate the effectiveness of this heuristic

Empirical Studies in Hospital Emergency Departments

This dissertation focuses on the operational impacts of crowding in hospital emergency departments. The body of this work is comprised of three essays. In the first essay, Waiting Patiently: An Empirical Study of Queue Abandonment in an Emergency Department, we study queue abandonment, or left without being seen. We show that abandonment is not only influenced by wait time, but also by the queue length and the observable queue flows during the waiting exposure. We show that patients are sensitive to being jumped in the line and that patients respond differently to people more sick and less sick moving through the system. This study shows that managers have an opportunity to impact abandonment behavior by altering what information is available to waiting customers. In the second essay, Doctors Under Load: An Empirical Study of State-Dependent Service Times in Emergency Care, we show that when crowded, multiple mechanisms in the emergency department act to retard patient treatment, but care providers adjust their clinical behavior to accelerate the service. We identify two mechanisms that providers use to accelerate the system: early task initiation and task reduction. In contrast to other recent works, we find the net effect of these countervailing forces to be an increase in service time when the system is crowded. Further, we use simulation to show that ignoring state-dependent service times leads to modeling errors that could cause hospitals to overinvest in human and physical resources. In the final essay, The Financial Consequences of Lost Demand and Reducing Boarding in Hospital Emergency Departments, we use discrete event simulation to estimate the number of patients lost to Left Without Being Seen and ambulance diversion as a result of patients waiting in the emergency department for an inpatient bed (known as boarding). These lost patients represent both a failure of the emergency department to meet the needs of those seeking care and lost revenue for the hospital. We show that dynamic bed management policies that proactively cancel some non-emergency patients when the hospital is near capacity can lead to reduced boarding, increased number of patients served, and increased hospital revenue

Effects of Automation on Aircrew Workload and Situation Awareness in Tactical Airlift Missions

In tactical aviation, decision superiority brought upon by high situation awareness remains the arbiter of combat effectiveness. The advancement of sophisticated avionics and highly automated cockpits has allowed for the reduction of aircrew size, and in certain platforms, removal of the crew from the aircraft entirely. However, these developments have not reduced the complex and dynamic interaction between situation awareness and crew workload. While many predictive and experimental methods of evaluating workload exist, situation awareness can only be measured by conducting trials with human operators in a functional prototype. This thesis proposes an innovative methodology to predicatively determine situation awareness potential with discrete-event simulation software. This methodology measures situation awareness as both a function of task accomplishment and workload experienced. Utilizing two common but complex tactical scenarios, this method and existing workload measurement techniques can derive a direct comparison between a reduced-crew highly automated cockpit and a less automated legacy aircraft. Finally, conclusions regarding the effectiveness of replacing human operators with automation in tactical events can be made and tested in future experiments with actual aircraft and aircrews

Coordinating the Design and Management of Heterogeneous Datacenter Resources

<p>Heterogeneous design presents an opportunity to improve energy efficiency but raises a challenge in management. Whereas prior work separates the two, we coordinate heterogeneous design and management. We present a market-based resource allocation mechanism that navigates the performance and power trade-offs of heterogeneous architectures. Given this management framework, we explore a design space of heterogeneous processors and show a 12x reduction in response time violations when equipping a datacenter with three processor types over a homogeneous system that consumes the same power. To better understand trade-offs in large heterogeneous design spaces, we explore dozens of design strategies and present a risk taxonomy that classifies the reasons why a deployed system may underperform relative to design targets. We propose design strategies that explicitly mitigate risk, such as a strategy that minimizes the coefficient of variation in performance. In our experiments, we find that risk-aware design accounts for more than 70% of the strategies that produce systems with the best service quality. We also present a new datacenter management mechanism that fairly allocates processors to latency-sensitive applications. Tasks express value for performance using sophisticated piecewise-linear utility functions. With fairness in market allocations, we show how datacenters can mitigate envy amongst latency-sensitive users. We quantify the price of fairness and detail efficiency-fairness trade-offs. Finally, we extend the market to fairly allocate heterogeneous processors.</p>Dissertatio

Strategic experimentation in queues

We analyze the social and private learning at the symmetric equilibria of a queueing game with strategic experimentation. An infinite sequence of agents arrive at a server which processes them at an unknown rate. The number of agents served at each date is either: a geometric random variable in the good state, or zero in the bad state. The queue lengthens with each new arrival and shortens if the agents are served or choose to quit the queue. Agents can only observe the evolution of the queue after they arrive; they, therefore, solve a strategic experimentation problem when deciding how long to wait to learn about the probability of service. The agents, in addition, benefit from an informational externality by observing the length of the queue and the actions of other agents. They also incur a negative payoff externality, as those at the front of the queue delay the service of those at the back. We solve for the long-run equilibrium behavior of this queue and show there are typically mass exits from the queue, even if the server is in the good state

Scalable Task Schedulers for Many-Core Architectures

This thesis develops schedulers for many-cores with different optimization objectives. The proposed schedulers are designed to be scale up as the number of cores in many-cores increase while continuing to provide guarantees on the quality of the schedule

Supercomputer and cluster performance modeling and analysis efforts:2004-2006.

This report describes efforts by the Performance Modeling and Analysis Team to investigate performance characteristics of Sandia's engineering and scientific applications on the ASC capability and advanced architecture supercomputers, and Sandia's capacity Linux clusters. Efforts to model various aspects of these computers are also discussed. The goals of these efforts are to quantify and compare Sandia's supercomputer and cluster performance characteristics; to reveal strengths and weaknesses in such systems; and to predict performance characteristics of, and provide guidelines for, future acquisitions and follow-on systems. Described herein are the results obtained from running benchmarks and applications to extract performance characteristics and comparisons, as well as modeling efforts, obtained during the time period 2004-2006. The format of the report, with hypertext links to numerous additional documents, purposefully minimizes the document size needed to disseminate the extensive results from our research

Crisis management for the tourism sector, Malaysia's response to the Asian financial crisis

The purpose of this research was to investigate crisis management in the context of the tourism sector by means of a case study of the Malaysian response to the Asian financial crisis. Not only was the reaction of the Malaysian government to the crisis examined but the possibility of developing a strategy to protect the sector against future crises was also explored. Primary data were collected by means of semi-structured interviews with senior Malaysian public and private sector policy makers. Areas of interest addressed included the crisis management measures employed to assist the recovery of the tourism sector; the lessons learnt from the crisis: the potential for public/private sector cooperation to develop a crisis management plan for the tourism sector; and how such a plan might be implemented. It was generally felt by the participants that the measures employed had been effective in restoring the tourism sector status quo, although there was some concern expressed over how long this had taken. It was agreed that there is a need for a sectoral crisis management plan but no consensus as to who should fund it, which figures could be used as indicators of the approach of a crisis and how they should be collected, and what form any such plan should take. This research indicates that there is a case for the government to work with the private sector to develop some sort of crisis management provision for the tourism sector. However, it is apparent that it may be extremely problematic to formulate an appropriate plan and there may be difficulties as to how it should be funded and who should take responsibility for its implementation. It appears that an approach at state level would have more potential than a federal plan but more research in this area is required.The purpose of this research was to investigate crisis management in the context of the tourism sector by means of a case study of the Malaysian response to the Asian financial crisis. Not only was the reaction of the Malaysian government to the crisis examined but the possibility of developing a strategy to protect the sector against future crises was also explored. Primary data were collected by means of semi-structured interviews with senior Malaysian public and private sector policy makers. Areas of interest addressed included the crisis management measures employed to assist the recovery of the tourism sector; the lessons learnt from the crisis: the potential for public/private sector cooperation to develop a crisis management plan for the tourism sector; and how such a plan might be implemented. It was generally felt by the participants that the measures employed had been effective in restoring the tourism sector status quo, although there was some concern expressed over how long this had taken. It was agreed that there is a need for a sectoral crisis management plan but no consensus as to who should fund it, which figures could be used as indicators of the approach of a crisis and how they should be collected, and what form any such plan should take. This research indicates that there is a case for the government to work with the private sector to develop some sort of crisis management provision for the tourism sector. However, it is apparent that it may be extremely problematic to formulate an appropriate plan and there may be difficulties as to how it should be funded and who should take responsibility for its implementation. It appears that an approach at state level would have more potential than a federal plan but more research in this area is required