The Internet is an essential resource to an ever-increasing number of businesses and home users. Internet access is increasing dramatically and hence, the need for efficient and effective Web server systems is on the rise. These systems are information engines that are accessed through the Internet by a rapidly growing client base. These systems are expected to provide good performance and high availability to the end user. They are also resilient to failures at both the hardware and software levels. These characteristics make them suitable for servicing the present and future information demands of the end consumer. In recent years, researchers have concentrated on taxonomies of scalable Web server system architectures, and routing and dispatching algorithms for request distribution. However, they have not focused on the classification of commercial products and prototypes, which would be of use to business professionals and software architects. Such a classification would help in selecting appropriate products from the market, based on product characteristics, and designing new products with different combinations of server architectures and dispatching algorithms. Currently, dispatching algorithms are classified as content-blind, content-aware, and Domain Name Server (DNS) scheduling. These classifications are extended, and organized under one tree structure in this thesis. With the help of this extension, this thesis develops a unified product-based taxonomy that identifies product capabilities by relating them to a classification of scalable Web server systems and to the extended taxonomy of dispatching algorithms. As part of a detailed analysis of Web server systems, generic queuing models, which consist of a dispatcher unit and a Web server unit are built. Some performance metrics, such as throughput, server performance, mean queue size, mean waiting time, mean service time and mean response time of these generic queuing models are measured for evaluation. Finally, the correctness of generic queuing models are evaluated with the help of theoretical and simulation analysis. / May 2005

The Internet is an essential resource to an ever-increasing number of businesses and home users. Internet access is increasing dramatically and hence, the need for efficient and effective Web server systems is on the rise. These systems are information engines that are accessed through the Internet by a rapidly growing client base. These systems are expected to provide good performance and high availability to the end user. They are also resilient to failures at both the hardware and software levels. These characteristics make them suitable for servicing the present and future information demands of the end consumer. In recent years, researchers have concentrated on taxonomies of scalable Web server system architectures, and routing and dispatching algorithms for request distribution. However, they have not focused on the classification of commercial products and prototypes, which would be of use to business professionals and software architects. Such a classification would help in selecting appropriate products from the market, based on product characteristics, and designing new products with different combinations of server architectures and dispatching algorithms. Currently, dispatching algorithms are classified as content-blind, content-aware, and Domain Name Server (DNS) scheduling. These classifications are extended, and organized under one tree structure in this thesis. With the help of this extension, this thesis develops a unified product-based taxonomy that identifies product capabilities by relating them to a classification of scalable Web server systems and to the extended taxonomy of dispatching algorithms. As part of a detailed analysis of Web server systems, generic queuing models, which consist of a dispatcher unit and a Web server unit are built. Some performance metrics, such as throughput, server performance, mean queue size, mean waiting time, mean service time and mean response time of these generic queuing models are measured for evaluation. Finally, the correctness of generic queuing models are evaluated with the help of theoretical and simulation analysis.

The Internet is an essential resource to an ever-increasing number of businesses and home users. Internet access is increasing dramatically and hence, the need for efficient and effective Web server systems is on the rise. These systems are information engines that are accessed through the Internet by a rapidly growing client base. These systems are expected to provide good performance and high availability to the end user. They are also resilient to failures at both the hardware and software levels. These characteristics make them suitable for servicing the present and future information demands of the end consumer. In recent years, researchers have concentrated on taxonomies of scalable Web server system architectures, and routing and dispatching algorithms for request distribution. However, they have not focused on the classification of commercial products and prototypes, which would be of use to business professionals and software architects. Such a classification would help in selecting appropriate products from the market, based on product characteristics, and designing new products with different combinations of server architectures and dispatching algorithms. Currently, dispatching algorithms are classified as content-blind, content-aware, and Domain Name Server (DNS) scheduling. These classifications are extended, and organized under one tree structure in this thesis. With the help of this extension, this thesis develops a unified product-based taxonomy that identifies product capabilities by relating them to a classification of scalable Web server systems and to the extended taxonomy of dispatching algorithms. As part of a detailed analysis of Web server systems, generic queuing models, which consist of a dispatcher unit and a Web server unit are built. Some performance metrics, such as throughput, server performance, mean queue size, mean waiting time, mean service time and mean response time of these generic queuing models are measured for evaluation. Finally, the correctness of generic queuing models are evaluated with the help of theoretical and simulation analysis.

Aim of this thesis is to analyze the current situation, to identify bottlenecks and to propose improvements to the department of acquisitions in the selected financial company, which is an important part of the Czech market and which desire not to be named. In the first part of my thesis is provided to the reader a theoretical basis necessary to understand the following text. Then I create simulation models for individual teams, which take part in the mentioned department. These models are based only on average and total values. That is why in the next section, there is described the work to bring them closer to reality with shifts of administrators and the variable number of entities, which are processed throughout the day. Based on the analysis of calculated values, I propose two methods of redistribution of actions to reduce the number of employees and to increase their efficiency.

Queueing theory is widely used in practical queuing applications. It can be applied for specific models of queuing systems, especially the ones that follow the Markovian property. Its purpose is to predict system behaviour in order to be used for performance optimization. In this case study, it was used to evaluate an extended queuing model with agents serving multiple queues. The purpose was to try to capture more variability and input factors into the theoretical model and test its applicability on more extended models. The main objective was to use relevant queuing theory models to estimate the wait time using real contact center data. Different from the theoretical model, the service rates of the system model depended on how many queues an agent served concurrently, which increased the complexity of the model. The obtained results demonstrated some limitations that made the models too restrictive to be applied to a model with multi-skilled agents that were not equally available. Moreover, it was shown that heuristical approaches might be more suitable for more complex queuing systems that are not covered in queueing theory models. / Köteori används i stor utsträckning i praktiska kö-applikationer. Den kan tillämpas för specifika modeller av kö-system, speciellt de som följer Markovegenskapen. Dess syfte är att förutse systembeteende för att kunna användas för prestandaoptimering. I denna fallstudie användes den för att utvärdera en utökad kömodell med agenter som betjänade flera köer. Syftet var att försöka fånga mer variabilitet och inputfaktorer i den teoretiska modellen och testa dess tillämplighet för mer utökade modeller. Huvudmålet var att använda relevanta kö-teorimodeller för att estimera väntetiden med användning av riktiga contact center data. Till skillnad från den teoretiska modellen, betjäningsintensiteten för systemmodellen berodde på hur många köer en agent betjänade samtidigt, vilket ökade komplexiteten av modellen. De erhållna resultaten visade begränsningar som gjorde modellen för restriktiv för att appliceras på en modell med fler-kvalificerade agenter som inte var lika tillgängliga. Utöver detta så visade det sig att heuristiska metoder kan vara mer lämpliga för mer komplicerade system som inte täcks av kö-teori modeller.