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International container shipping is a complex system of interlocked stakeholders. Obtaining reliable data can be difficult and the data for specific routes and container terminals change over time. Intermodal transportation has increased in importance over the years. A relational database model was developed as a tool for stakeholders interested in analyzing specific paths. The database uses data on transportation time, variance of transportation time, transportation cost and green house gas emissions. The user can specify their own set of locations, movements, containers, items and transportation modes. The total logistics cost of a specific importing strategy can be calculated for any path defined by the user. A Floyd-Warshall algorithm was implemented to allow for the shortest path between locations to be determined, based on the preferences of the user for either cost, time or CO2 emissions. In order to illustrate the capabilities of our model and because of our interest in the port of Halifax, we created a dataset from the distances between important locations within the international container shipping system. Using this dataset, some example calculations indicate that the port of Halifax and the port of Montreal could consider cooperating to form a hub-and-spoke relationship for European imports. In another example, the port of Halifax provides the fastest route for imports using the Suez Canal intending to reach Toronto but the cheapest total logistics cost route involves using the port of NY/NJ. By using both the total logistics cost algorithms and the shortest path algorithms, the examples illustrate how stakeholders in the container transportation industry can analyze various routes, terminals and make informed decisions.

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Database Management Systems (DBMSs) are an integral part of many applications. Web-based applications, such as e-commerce sites, are faced with highly variable workloads. The number of customers browsing and purchasing items varies throughout the day and business managers can further complicate the workload by requesting complex reports on sales data. This means the load on a database system can fluctuate dramatically with a sudden influx of requests or a request involving a complex query. If there are too many requests operating in the DBMS concurrently, then resources are strained and performance drops. To keep the DBMS’s performance consistent across varying loads, a load control system can be used. This thesis investigates the concept of a load control system based on regulating individual resource usage in a predictive manner. For the purpose of this proof-of- concept study, we focus on a specific resource; namely, the sort heap. A method of estimating sort heap usage based on the query execution plan is presented and several scheduling methods based on these estimations are proposed. A prototype load control system is used to evaluate and compare the scheduling methods. Experiments show that it is possible to both estimate sort heap requirements and to control sort heap usage using our load control system. / Thesis (Master, Computing) -- Queen's University, 2011-06-09 11:02:31.595

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