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Typescript (photocopy) / xvi 239 leaves : ill., charts ; 31 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Computing Science, 1982

In many branches of the economy, including transportation, lodging, and more recently cloud computing, users can reserve resources in advance. Although advance reservations are gaining popularity, little is known about the strategic behavior of customers facing the decision whether to reserve a resource in advance or not. Making an advance reservation can reduce the waiting time or the probability of not getting service, but it is usually associated with an additional cost. To evaluate this trade-off, we develop a game-theoretic framework, called advance reservation games, that helps in reasoning about the strategic behavior of customers in systems that allow advance reservations. Using this framework, we analyze several advance reservation models, in the context of slotted loss queues and waiting queues. The analysis of the economic equilibria, from the provider perspective, yields several key insights, including: (i) If customers have no a-priori information about the availability of servers, then only customers granted service should be charged a reservation fee; (ii) Informing customers about the exact number of available servers is less profitable than only informing them that servers are available; (iii) In many cases, the reservation fee that leads to the equilibrium with maximum possible profit leads to other equilibria, including one resulting with no profit; (iv) If the game repeats many times and customers update their strategy after observing actions of other customers at previous stage, then the system converges to an equilibrium where no one makes an advance reservation, if such an equilibrium exists. Else, the system cycles and yields positive profit to the provider Finally, we study the impact of information sharing in M/M/1 queues with strategic customers. We analyze the intuitive policy of sharing the queue length with customers when it is small and hiding it when it is large. We prove that, from the provider perspective, such a policy is never optimal. That is, either always sharing the queue length or always hiding it maximizes the average number of customers joining the queue.

Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance.

Databases form the common component of many software systems, including mission critical transaction processing systems and multi-tier Internet applications. There is a large body of research in the performance of database management system components, while studies of overall database system performance have been limited. Moreover, performance models specifically targeted at the database design have not been extensively studied. This thesis attempts to address this concern by proposing a performance evaluation method for database designs based on queueing network models. The method is targeted at designs of large databases in which I/O is the dominant cost factor. The database design queueing network performance model is suitable in providing what if comparisons of database designs before database system implementation. A formal specification that captures the essential database design features while keeping the performance model sufficiently simple is presented. Furthermore, the simplicity of the modelling algorithms permits the direct mapping between database design entities and queueing network models. This affords for a more applicable performance model that provides relevant feedback to database designers and can be straightforwardly integrated into early database design development phases. The accuracy of the modelling technique is validated by modelling an open source implementation of the TPC-C benchmark. The contribution of this thesis is considered to be significant in that the majority of performance evaluation models for database systems target capacity planning or overall system properties, with limited work in detailed database transaction processing and behaviour. In addition, this work is deemed to be an improvement over previous methodologies in that the transaction is modelled at a finer granularity, and that the database design queueing network model provides for the explicit representation of active database rules and referential integrity constraints. / Iqra Foundation

A thesis based around saving response time costs as well as respecting electrical costs of a homogenous multi-server system. / In this thesis we consider the impacts of energy costs as they relate to Size Interval Task Assignment Equally--loaded (SITA-E) systems. We find that given systems which have small and large jobs being processed (high variance systems) we could in some cases find savings in terms of energy costs and in terms of lowering the mean response times of the system. How we achieve this is by first working from SITA-E, wherein servers are always on to Electrically Aware SITA-E (EA-SITA-E) by seeing if it is beneficial to make any of our servers rotate between being on and being off as needed. When most beneficial to do so we will turn off some of the servers in question, after this is completed we reallocate some of the jobs that are on the servers that we decide will be cycling to servers that will remain on indefinitely to better use their idle time. This also lowers the mean response time below what we originally saw with SITA-E, by lowering the variance in the sizes of jobs seen by the servers with the longest jobs. These long--job servers are by far the most impacted by the variance of the sizes of the jobs, so it is very desirable to lower this variance. The algorithm contained here can provide benefits in terms of both energy costs and mean response time under some specific conditions. Later we discuss the effect of errors in our assumed knowledge of task sizes. This research contributes methodology that may be used to expand on EA-SITA-E system design and analysis in the future. / Thesis / Master of Science (MSc) / The intention of this research is to be able to improve on existing size interval task-based assignment policies. We try to improve by turning servers off at key times to save energy costs, while not sacrificing too greatly in terms of mean response time of the servers, and in some cases even improving the mean response time through an intelligent re-balancing of the server loads.

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All physical copies are missing page 3 in this thesis. - McMaster Digitization Center / A computer simulation model was developed to simulate the receiving of raw materials at a dock for an integrated steel plant on the North shore of Lake Erie. The model was formulated to study queue build-up, berth waiting time and the effect of various unloading conditions on dock efficiency. A financial analysis, using present value techniques, was then applied to the model results in order to recommend an optimum berth staging plan under various economic conditions. Historical data on raw material receiving at Hilton Works, Hamilton, were collected and used to develop mathematical functions to describe the random nature of vessel arrivals and berth times. It was determined from this data that vessel arrivals are described by a Poisson distribution and berth times are described by an Erlang distribution. The computer model simulates the dock operation by generating random numbers according to these distributions (Monte Carlo Simulation.) Coal and ore vessel arrivals are merged and respective service times generated. Interferences occur and queues grow and diminish as the facility is simulated through the shipping seasons throughout its expected life. Various unloading rates and vessel tonnages are simulated for a single and double berth operation and the associated waiting times and queue lengths are recorded for each alternative. An economic analysis is performed on the alternatives using present value techniques. The economic analysis indicated that the optimum time to expand the dock to a double berth occurs at a tonnage level of 15 million (coal + ore). To reach this level unloading rates of 10,000 TPH for ore and 8,000 TPH for coal would have to be achieved with an average vessel tonnage of 39,000 metric tonnes. Reducing the unloading rates or average vessel tonnage would move forward the required construction of a double berth and would increase the present value for that alternative. This expansion date will also depend on future economic factors such as cost of capital and escalation rate. The other important conclusion drawn from the economic analysis was that the receiving facility should be expanded in minimum feasible increments because of uncertain economic conditions. This concept dictates that conveyors be installed at minimum capacity, i.e. -belt width and drive size, to handle the first stage tonnage only with provision in the equipment to increase capacity by replacing narrow belts with wider ones and adding additional drive units. The timing for the stages is predicted on several factors, such as: life of the initial belt, tonnage forecast, ship delay costs, and most importantly future economic conditions. For example, it would be advantageous to increase the unloading capacity with a wider belt at the time the initial belt is worn out. Belt and drive staging will take place before the expansion to a second berth in order to defer the capital investment as long as possible. The conveyor system for the second berth can be similarily staged. The study indicated that a good planning strategy would be to initially install a 1.8 m wide belt on 2.0 m wide machinery with 3-1,000 H.P. drives. This system would unload ore at approximately 7,000 t/hr. and coal at approximately 5,000 t/hr. This capability could be increased to 10,000 t/hr. for ore and approximately 8,000 t/hr: for coal by adding a 2.0 m wide belt and 1 -1,000 H.P. drive unit. These rates would be compatible with the expected unloading rates of the future fleet. The decision to increase capacity should be considered when the initial belt is worn out or when delay costs and future economics dictate expansion before that time. The study also indicated that it is poor strategy to design the second berth/conveyor system to be restricted to coal receiving only. The Computer simulation indicated ship delay time for the restricted berth to be approximately three times that for a system with capability to receive ore and coal equally at both berths on either conveyor and either stacker. It indicates that ore receiving is the most important capability and should not be restricted. Even though ore pellets unload more quickly the ore tonnage required is twice that for coal. Therefore, it is recommended to design a completely flexible system . with full provision for expansion to higher unloading rates and larger vessels (850 ft.) and with provision to unload equally from either berth to either conveyor and to have the ability to transfer material between converyors at the head end of the stacker conveyor. / Thesis / Master of Engineering (MEngr)

The optimization of the performance of a constant Work-in-Progress (CONWIP) production system through the sequencing of its backlog list is investigated. The performance measures considered are throughput, optimum WIP level (m*), and flow time. Analysis of the effects of sequence dependent bottlenecks on system performance is provided. A procedure is presented to determine a lower bound for (m*) given the product mix. A method that determines (m*) given the sequence of jobs is provided. A heuristic algorithm is provided for the purpose of determining a sequence to minimize (m*). The algorithm attempts to sequence the jobs to achieve the "best fit" between consecutive jobs so that machine and job idle times are minimized. The algorithm is tested through computer implementation to reveal its proficiency. / Master of Science