This paper discusses the scheduling of reefer mechanics at container terminals. Reefer mechanics plug and unplug reefer containers such that due times are met. We outline the resulting scheduling problem and two simple heuristics. Subsequently, we present a simulation model to analyze the scheduling methods and the reefer-related processes in a realistic dynamic framework. Some results from the simulation experiments are also presented. They demonstrate the applicability of the heuristic and the use of the simulation model in practice. The simulation study was carried out for a real container terminal in the port of Hamburg, Germany.

Deutlich ansteigende interkontinentale Handelsbeziehungen bilden die wesentliche Grundlage das Wachstum der Containerschifffahrt. Die Schnittstelle der Containerschifffahrt zu den landgebundenen Verkehrsträgern bilden Containerterminals. Deren Entwicklung muss im Zusammenhang mit der Containerschifffahrt gesehen werden. Die Entwicklung des Containerschifffahrtsmarktes wird sich auch in Zukunft weiter dynamisch fortsetzen. Prognosen zur Umschlagsentwicklung sind für die Containerterminals von besonderem Interesse, da die Containerterminals bestrebt sind, genügend Kapazitäten bereitzustellen. Im Umfeld eines Containerterminals sowie in ihnen selbst können diverse Kapazitätsengpässe entstehen. In vielen Fällen ist dringender Handlungsbedarf hinsichtlich der Beseitigung von potenziellen Engpässen gegeben. Eine Option stellt dabei der Neubau von Containerterminals dar. Der Hafenbau wird in dichtbesiedelten Räumen zunehmend schwieriger und teurer. Die aus heutiger Sicht zur Verfügung stehenden Flächen werden langfristig nicht ausreichen, um das Umschlagsaufkommen der Zukunft zu bewältigen. Deswegen kann die Errichtung von herkömmlichen Containerterminals langfristig nicht als ausschließliche Option zur Beseitigung von Umschlagsengpässen angesehen werden. Das Konzept eines Offshore-Containerterminals (OCT) stellt einen alternativen Ansatz dar, der zukünftige Engpässe vermeidet oder ihre Auswirkungen mindert. Ziel des Konzepts ist die Verlagerung von Transshipments von den herkömmlichen Containerterminals auf einen OCT. Dieses Konzept wird auf seine wirtschaftliche Tragfähigkeit untersucht. Letzlich stellt das Konzept des OCTs als Transshipment-Hub eine Möglichkeit dar, die unter heutigen Verhältnissen zwar unrentabel erscheint, unter zukünftigem Expansionsdruck und Kostensteigerungen bei der Erschließung neuer Terminalflächen jedoch als Konzept ökonomisch konkurrenzfähig sein kann und eventuell ohne Alternative ist.

I detta examensarbete genomförs en omfattande analys om hur prissättningsstrategier tillämpas inom sjöfraktindustrin. Denna bransch har en nyckelfunktion i världens globala försörjningskedjor och spelar en viktig roll i världsekonomin. Trots det präglas industrin av låga vinstmarginaler samt höga kostnader och påtaglig konkurrens. Syftet med studien är således att analysera hur prissättningsstrategier kan hantera kostnadsproblematiken och skapa positiva ekonomiska effekter för aktörer inom industrin. Därefter introduceras en konceptuell strategi som förslag på ytterligare intäktsoptimering relaterat till avbokningsproblematik. Denna strategi bygger på en dynamisk avbokningsavgift som baseras på fraktpris och säsongsindikatorer. Modellen testas och analyseras för att undersöka dess ekonomiska effekter. Studien genomförs med en kvalitativ forskningsmetod där respondenter från två internationella rederier med filialer i Sverige intervjuas; CMA-CGM och Maersk. Detta för att få en inblick över hur kostnadsproblematiken ter sig i verkligheten och hur prissättningsstrategier kan hantera den. Slutsatserna av studien är att de två företag som jämförts använder sig av befintliga strategier för att kunna hantera den kostnadsproblematik som ständigt förekommer inom sjöfrakten. Dessa strategier innefattar områden som; utrymmesutnyttjande, allokering baserat på kundkategorier samt överbokning. För att skapa ekonomiska fördelar utvärderas dessa strategier kontinuerligt för att företagen ska kunna uppnå maximal vinst. Det är även av största vikt att företagen är flexibla i den utsträckning som tillåts då marknaden präglas av kraftig konkurrens. Genom att använda centrala delar av de befintliga strategierna har en konceptuell modell tagits fram som potentiellt sett kan öka företagets intäkter vid avbokningar. / In this bachelor thesis, a comprehensive analysis of how pricing strategies are applied in the sea freight industry is carried out. This industry has a key function in the world's global supply chains and plays an important role in the world economy. Despite this, the industry is characterized by low profit margins as well as high costs and considerable competition. The aim of the study is thus to analyze how pricing strategies can deal with the cost problem and create positive economic effects for actors in the industry. Subsequently, a conceptual strategy is introduced as a proposal for further revenue optimization related to cancellation problems. This strategy is based on a dynamic cancellation fee based on freight prices and seasonal indicators. The model is tested and analyzed to investigate its economic effects. The study is carried out with a qualitative research method in which respondents from two international shipping companies with branches in Sweden are being interviewed; CMA-CGM and Maersk. This is to gain an insight into how the cost problem appears in reality and how pricing strategies can handle it. The conclusions of the study are that the two companies that have been compared are using existing strategies to deal with the cost problems that constantly occur in sea freight. These strategies include areas such as; space utilization, allocation based on customer categories and over booking. In order to generate economic benefits, these strategies are continuously evaluated in order for companies to achieve maximum profit. It is also of the utmost importance that companies are flexible to the extent that is permissible since the market is characterized by strong competition. By using central parts of the existing strategies, a conceptual model has been developed that potentially can increase the company's revenues linked to cancellations.

Service assurance is critical for high-demand services running on telecom clouds. While service performance metrics may not always be available in real time to telecom operators or service providers, service performance prediction becomes an important building block for such a system. However, it is generally hard to achieve.  In this master thesis, we propose a machine-learning based method that enables performance prediction for services running in virtualized environments with Docker containers. This method is service agnostic and the prediction models built by this method use only device statistics collected from the server machine and from the containers hosted on it to predict the values of the service-level metrics experienced on the client side.  The evaluation results from the testbed, which runs a Video-on-Demand service using containerized servers, show that such a method can accurately predict different service-level metrics under various scenarios and, by applying suitable preprocessing techniques, the performance of the prediction models can be further improved.  In this thesis, we also show the design of a proof-of-concept of a Real-Time Analytics Engine that uses online learning methods to predict the service-level metrics in real time in a container-based environment.

När Covid-19 pandemin drabbade samhället skedde det en omställning såväl nationellt som internationellt. Vardagen som alla varit vana vid var inte längre densamma, men, även världshandeln blev påverkad. Oförutsedda händelser som detta sker när man minst anar det och man kan inte förutse vad konsekvenserna av dem kommer bli. Detta märktes tydligt under bland annat Covid-19 pandemin. Något som påverkades mycket under 2020–2022 var transporterna, speciellt för sjöfrakten. Studiens syfte är att undersöka de delar i processen av inleveranser som är mest känsliga för störningar samt hur företag kan bli bättre förberedda i framtiden så att de sparar in på såväl tid som kostnader. För att upprätta rapporten genomfördes en fallstudie med hjälp av kvalitativa intervjuer tillsammans med en anställd på klädföretaget X samt en anställd på tredjepartsföretaget Y under våren 2022. Studien visade på att den rådande containerbristen varit en stor faktor till leveransförseningar. För att kunna vara mer flexibel drogs därför slutsatsen, genom bland annat en riskanalys och ett designtänkande, att användningen av fler leverantörer, hybrid sourcing, och en fördelning av produktionen i olika delar av världen, skulle göra att företag kan hantera oförutsedda händelser bättre. Designtänkandets analys genomfördes med en trestegsprocess för att på så sätt utveckla processen och göra den mindre känslig för störningar. Dessa störningar definierades, utvecklades och till slut transformerades, för att företaget inte ska bli lika sårbara i framtiden. Användandet av hybrid sourcing gör att man utnyttjar de goda egenskaper från single och multiple sourcing, vilket leder till att företaget minimerar antal risker i leveransprocessen. Genom att ha en definition för artikelgrupper kan man därför tillämpa multiple sourcing på den nivån samt att man tillämpar single sourcing på artikelnivåerna. Fokuset på Företag X:s basplagg är även något som anses vara relevant för att minimera störningarna vid oförutsedda händelser, då man köper in dem i större kvantiteter från Asien. Trendplaggen bör istället tillverkas i mindre kvantiteter i Europa. / When the Covid-19 pandemic hit the global community, there was a readjustment both national as well as international. The everyday life that we were all used to was no longer the same, but the global trade market was also affected. Contingencies that happen in situations like this occur when you least expect it, and you cannot anticipate the consequences of them. This was clearly noticed during, among other things, the Covid-19 pandemic. Somethings that were affected a lot in 2020-2022 were the deliveries, especially the sea freight. The purpose of this study is to investigate the activities of the delivery process that are most sensitive to disturbances in a company. And thereby how companies can be more prepared for the impact of contingencies, so it is possible to save in on both time and costs. To establish the report, a case study was made with qualitative interviews with the help of an employee at the clothing company X and with an employee at the third part logistics company Y, during the spring of 2022. The study showed that the container shortages that occurred during the Covid-19 pandemic have been a large factor in the shipment delays. To open for the possibility to be more flexible, though, among other things, through a risk analysis and a design thinking, the conclusions that were made was to use more suppliers, hybrid sourcing, and to divide the production to different parts of the world. This would make the companies better at handling contingencies. The design thinking analysis was made through a three-step process that brings up the disturbance that you later define and develop and, in the end, transform so the company will not be as vulnerable to disturbances in the future. The use of hybrid sourcing makes you exploit the good property of single and multiple sourcing, which makes the company minimize the number of risks in the supply chain. By having a definition for the article group, you can apply multiple sourcing on that level, and you can apply single sourcing on a level per article. The focus on Company X basic garments is also something that is considered relevant to minimize the disturbance of the contingencies. This is because you can buy them in larger quantities from Asia. The trend garments should instead be manufactured in smaller quantities in Europe.

Global flood forecasting can benefit developing countries and ungauged regions that lack observational data, computational infrastructure, and human capacity for streamflow modeling. Many technical challenges exist to provide flood predictions on a global scale. First, existing land surface forecasts use coarse resolution grid cells, which provide limited information when used for flood forecasting at local scales. There is, so far, no modeling system that can provide rapid and accurate global flood predictions with low cost. Second, accurate flood predictions often require integrating interdisciplinary models, data sources, and analysis routines into a workflow. Limited accessibility, reusability, and interoperability of models restrict integrated modeling from producing more reliable results. Web services have been demonstrated as an effective way for data and model sharing because of the capability of enabling communication among heterogeneous applications over the internet. However, publishing models or analysis routines as web services is still challenging and, hence, is not commonly done. To address the above challenges, I present a computational system for global streamflow prediction, using existing, well-established open source software tools, that quickly downscales the runoff generated from such coarse grid-based land surface models (LSMs) onto high-resolution vector-based stream networks then routes the results using a vector-based river routing model. A set of experiments are conducted to demonstrate the feasibility and credibility of this approach. I also present a tool to publish complex environmental models as web services by adopting the OpenGMS Wrapper System (OGMS-WS) and Docker. The streamflow prediction system is deployed as a web service using this tool, and the service is used to analyze the historical streamflow tendency in Bangladesh. Next, I present a ready-to-use tool called Tethys WPS Server, which provides a simplified and formalized way to expose web app functionality as standardized Open Geospatial Consortium (OGC) Web Processing Services (WPS) alongside a web app's graphical user interface. Three Tethys web apps are developed to demonstrate how web app functionality(s) can be exposed as WPS using Tethys WPS Server, and to show how these WPS can be coupled to build a complex modeling web app. In sum, this dissertation explores new computational approaches and software tools to advance global streamflow prediction and integrated environmental modeling.

Context. Cloud computing is growing fast and has established itself as the next generationsoftware infrastructure. A major role in cloud computing is the virtualization of hardware toisolate systems from each other. This virtualization is often done with Virtual Machines thatemulate both hardware and software, which in turn makes the process isolation expensive. Newtechniques, known as Microservices or containers, has been developed to deal with the overhead.The infrastructure is conjoint with storing, processing and serving vast and unstructureddata sets. The overall cloud system needs to have high performance while providing scalabilityand easy deployment. Microservices can be introduced for all kinds of applications in a cloudcomputing network, and be a better fit for certain products.Objectives. In this study we investigate how a small system consisting of a Cassandra clusterperform while encapsulated in LXC and Docker containers, compared to a non virtualizedstructure. A specific loader is built to stress the cluster to find the limits of the containers.Methods. We constructed an experiment on a three node Cassandra cluster. Test data is sentfrom the Cassandra-loader from another server in the network. The Cassandra processes are thendeployed in the different architectures and tested. During these tests the metrics CPU, disk I/O,network I/O are monitored on the four servers. The data from the metrics is used in statisticalanalysis to find significant deviations.Results. Three experiments are being conducted and monitored. The Cluster test pointed outthat isolated Docker container indicate major latency during disk reads. A local stress test furtherconfirmed those results. The step-wise test in turn, implied that disk read latencies happened dueto isolated Docker containers needs to read more data to handle these requests. All Microservicesprovide some overheads, but fall behind the most for read requests.Conclusions. The results in this study show that virtualization of Cassandra nodes in a clusterbring latency in comparison to a non virtualized solution for write operations. However, thoselatencies can be neglected if scalability in a system is the main focus. For read operationsall microservices had reduced performance and isolated Docker containers brought out thehighest overhead. This is due to the file system used in those containers, which makes disk I/Oslower compared to the other structures. If a Cassandra cluster is to be launched in a containerenvironment we recommend a Docker container with mounted disks to bypass Dockers filesystem or a LXC solution.

We live in a world that is constantly evolving where new technologies and innovations are being introduced. This progress partly results in developing new technologies and also in the improvement of the current ones. Docker containers are a virtualization method that is one of these new technologies that has become a hot topic around the world as it is said to be a better alternative to today's current virtual machines. One of the aspects that has contributed to this statement is the difference from virtual machines where containers isolate processes from each other and not the entire operating system. The company Saab AB wants to be at the forefront of today's technology and is interested in investigating the possibilities with container technology. The purpose with this thesis work is partly to investigate whether the container solution is in fact an alternative to traditional VMs and what differences there are between these methods. This will be done with the help of an in-depth literature study of comperative studies between containers and VMs. The results of the comparative studies showed that containers are in fact a better alternative than VMs in certain aspects such as performance and scalability and are worthy for the company. Thus, in the second part of this thesis work, a proof of concept implementation was made, by recreating a part of the company’s subsystem TactiCall into containers, to ensure that this transition is possible for the concrete use-case and that the container solution works as intended. This task has succeeded in highlighting the benefits of containers and showing through a proof of concept that there is an opportunity for the company to transition from VMs into containers.

Container technologies are rapidly changing how distributed applications are executed and managed on cloud computing resources. As containers can be deployed on a large scale, there is a tremendous need for Container Orchestration tools like Kubernetes that are highly automatic in deployment, scaling, and management. In recent times, the adoption of these container technologies like Docker has seen a rise in internal usage, commercial offering, and various application fields ranging from High-Performance Computing to Geo-distributed (Edge or IoT) applications. Big Data analytics is another field where there is a trend to run applications (e.g., Apache Spark) as containers for elastic workloads and multi-tenant service models by leveraging various container orchestration tools like Kubernetes. Despite the abundant research on the performance impact of containerizing big data applications, to the best of our knowledge, the studies that focus on specific aspects like scalability and resource management are largely unexplored, which leaves a research gap to study upon. This research studies the performance impact of autoscaling a big data analytics application on Kubernetes based on autoscaling mechanisms like Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA). These state-of-art autoscaling mechanisms available for scaling containerized applications on Kubernetes and the available big data benchmarking tools for generating workload on frameworks like Spark are identified through a literature review. Apache Spark is selected as a representative big data application due to its ecosystem and industry-wide adoption by enterprises. In particular, a series of experiments are conducted by adjusting resource parameters (such as CPU requests and limits) and autoscaling mechanisms to measure run-time metrics like execution time and CPU utilization. Our experiment results show that while Spark performs better execution time when configured to scale with VPA, it also exhibits overhead in CPU utilization. In contrast, the impact of autoscaling big data applications using HPA adds overhead in terms of both execution time and CPU utilization. The research from this thesis can be used by researchers and other cloud practitioners, using big data applications to evaluate autoscaling mechanisms and derive better performance and resource utilization.

Single-board computers as hardware for container orchestration have been a growing subject. Previous studies have investigated their potential of running production-grade technologies in various environments where low-resource, cheap, and flexible clusters may be of use. This report investigates the appliance of methods and processes prevalent in cluster, container orchestration, and cloud-native environments. The motivation being that if single-board computers are able to run clusters to a satisfactory degree, they should also be able to fulfill the methods and processes which permeate the same cloud-native technologies. Investigation of the subject will be conducted through the creation of different criteria for each method and process. They will then act as an evaluation basis for an experiment in which a single-board computer cluster will be built, provisioned, configured, and monitored. As a summary, the investigation has been successful, instilling more confidence in single-board computer clusters and their ability to implement cluster related methodologies and processes.