Thesis (M.B.A.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf [84-85]).

The thesis is divided into two parts. The first theoretical part defines the basic concepts related to combined transport and its current trends and supporting projects. It is focused on the structure of the European transport networks, with emphasis on road and rail transport. The practical part was developed in collaboration with the company PELMI, Ltd. and is focused on the analysis of the current situation of combined transport and price comparison of straight road and combined transport of containers. There is evaluation and definition of the conditions in which is advantageous / disadvantageous to move the containers road carriage to continental combined transport involving rail in conclusion.

Internet application servers are currently designed to maximize resource efficiency by servicing many thousands of users that may fall within disparate privilege classes. Pooling users into a shared execution context in this way enables adversaries not only to laterally propagate attacks against other clients, but also to use the application server as a "confused deputy" to gain escalated privileges against sensitive backend data. In this work, we present the Single-use Server (SuS) model, which detects and defeats these attacks by separating users into isolated, containerized application servers with tailored backend permissions. In this model, exploited servers no longer have unfettered access to the backend data or other users. We create a prototype implementation of the SuS model for the WordPress content management system and demonstrate our model's ability to neutralize real-world exploits against vulnerable WordPress versions. We find that the SuS model achieves a high level of security while minimizing the amount of code modification required for porting an application server. In our performance evaluation, we find that the CPU and latency overheads of the SuS model are very low, and memory consumption scales linearly. We generalize the SuS model to be applicable to a wide range of application server and backend resource pairs. With our modularized codebase, we port IMAP, a widely-used mail retrieval protocol, to the SuS model and find that doing so requires minimal effort.

This master’s thesis is focused on detailed analysis of possibilities of implementing a private cloud and secure data archiving for a long period of time using open-source tools. It describes the individual standards and processes of data preparation, as well as the OAIS reference model for long-term preservation. From the analyzed information, a complete design of the final solution is created, with a description of the functionality and the method of deployment in the environment of Docker containers. The design implementation and the main functionality of individual systems such as Archivematica or Nextcloud are thoroughly described and also the hardware requirements and cryptographic security were evaluated.

Containerization and virtualization are two of the keystones of cloud computing. Neither technologies are a new invention but did not become widely used until it regained popularity through new implementations. Virtualization regained popularity with the founding of VMWare, and containerization has become vastly popular in the last decade with Docker. When using a service from a Cloud Service Provider today, that service will more than likely be utilizing one of these technologies. This study aims to compare the performance of these two technologies when being used to host an API and how they utilize their provided hardware resources to handle HTTP requests.A series of load tests were conducted on an API developed and hosted on the two technologies to measure the hardware performance, response time and throughput of each technology.Hyper-V was used for virtualization, and Docker was used for containerization. Data was collected on resource utilization, response time, and throughput. The data was also compared to related research to validate it.The results of the experiment showed that, in our implementation, virtualization was superior to containerization in every measured aspect.We conclude that containerization has a bottleneck in the implementation we chose that impedes the container's network performance, which results in the container not being able to process as many HTTP requests as the virtualized environment.The number of processed HTTP requests for the container in relation to CPU usage is superior to that of the virtualized environment, which leads us to believe that it could be possible that the container would be superior if not for the network performance.

Docker is a popular tool for virtualization that allows for fast and easy deployment of applications and has been growing increasingly popular among companies. Docker also include a large library of images from the repository Docker Hub which mainly is user created and uncontrolled. This leads to low frequency of updates which results in vulnerabilities in the images. In this thesis we are developing a tool for determining what vulnerabilities that exists inside Docker images with a Linux distribution. This is done by using our own tool for downloading and retrieving the necessary data from the images and then utilizing Outpost24's scanner for finding vulnerabilities in Linux packages. With the help of this tool we also publish statistics of vulnerabilities from the top downloaded images of Docker Hub. The result is a tool that can successfully scan a Docker image for vulnerabilities in certain Linux distributions. From a survey over the top 1000 Docker images it has also been shown that the amount of vulnerabilities have increased in comparison to earlier surveys of Docker images.

Kubernetes is a software for managing clusters of containerized applications and has recently risen in popularity in the tech industry. However, this popularity seems to not have spread to the game development industry, prompting the author to investigate if the reason is a technical limitation. The investigation is done by creating a proof-of-concept of a simple system setup for running a game server in Kubernetes, consisting of the Kubernetes-cluster itself, the game server to be run in the cluster, and a matchmaker server for managing client requests and creation of game server instances. Thanks to the successful proof-of-concept, a conclusion can be made that there is no inherent technical limitation causing its infrequent use in game development, but most likely habitual reasons in combination with how new Kubernetes is.

Software containers are changing the way distributed applications are executedand managed on cloud computing resources. Autoscaling allows containerizedapplications and services to run resiliently with high availability without the demandof user intervention. However, specifying an auto­scaling policy that can guaranteethat no performance violations will take place is an extremely hard task, and doomedto fail unless considerable care is taken. Existing autoscaling solutions try to solvethis problem but fail to consider application specific parameters when doing so, thuscausing poor resource utilization and/or unsatisfactory quality of service in certaindynamic workload scenarios.This thesis proposes an autoscaling solution that enables cloud native application toautoscale based on application specific parameters. The proposed solution consistsof a profiling strategy that detects key parameters that affect the performance ofautoscaling, and an autoscaling algorithm that automatically enforces autoscalingdecisions based on derived parameters from the profiling strategy.The proposed solution is compared and evaluated against the default auto­scalingfeature in Kubernetes during different realistic user scenarios. Results from thetesting scenarios indicate that the proposed solution, which uses application specificparameters, outperforms the default autoscaling feature of Kubernetes in resourceutilization while keeping SLO violations at a minimum

Modern technology is rapidly and efficiently expanding, and by looking at the largest companies by market cap, one will find enterprises like Apple, Microsoft, Alphabet, and Meta. Given the complexity of modern software architecture, there arises a necessity for a software architecture that is both scalable and adaptable. This demand has given rise to the adoption of microservices as a preferred approach for building complex and distributed applications. However, managing microservices effectively is a difficult task. Therefore, Google created an orchestration tool called Kubernetes (K8). The primary purpose of this thesis is to extend the information about the characteristics of a K8 cluster by monitoring its performance in various scenarios. There is substantial documentation about how K8 works and why it is used. However, insufficient information exists regarding the performance of K8 in different scenarios.  Extensive testing has transpired to extend the information about the characteristics of K8. Parameters such as the number of Pods, containers, mounts, and CPU cores have been thoroughly tested. Additionally, parameters such as container load, CPU limitation, container distribution, and memory allocation have been examined. The core result will include startup time and CPU utilization. The startup time is essential in a K8 cluster because of its ephemeral characteristics, meaning each Pod is short-lived and will restart frequently. CPU utilization testing is essential to analyze how K8 allocate resources and perform with different amounts of resources.  The results show that the most significant parameters regarding startup time are, as one might expect, the number of containers, CPUs, Pods, and the load in each Pod. However, the complexity of the Pod, for instance, the number of mount points, has significantly less effect on the cluster than expected. Regarding CPU utilization, the results show that K8 does lower CPU usage if possible, resulting in equal CPU usage even with different numbers of CPUs. The most significant CPU usage parameter is the load of the application. Finally, this thesis work has filled some gaps in how a K8 cluster behaves during various circumstances, for instance, varying numbers of Pods, containers, or CPUs. One must consider several aspects while designing a K8 cluster. However, all aspects have not been considered, and the usage of K8 increases daily. Therefore, this thesis will hopefully be one of many reports investigating how a K8 cluster behaves and what to consider when building a cluster.

Intermodal traffic has been steadily increasing on the nation's railroads since the mid 1950's. Intermodal flatcar activity is now second only to coal in terms of total car loadings throughout the industry. The intermodal segment of the nation's transportation system is expected to play an ever increasing role in the future. Intermodal managers faced with increasing demands on their systems, have expressed a need for methods to aid in the development of new management techniques, economic costing models, and management information systems. The computer simulation intermodal model that is presented in this paper is designed to aid managers with the analysis of their current terminal systems and to plan for future growth in intermodal activity. The intermodal terminal model employs discrete, next event, simulation techniques. The Q-GERT simulation language, developed by A. Allen B. Pritsker, provides the vehicle necessary to approximate the required activities and associated flow of transactions through the terminal system. Three specific types of containers and flatcars are provided for, in addition to provisions for over-the-road container pick up and delivery. Thus, the model is adaptable to complex terminal systems, including sea ports where highly specialized containers are commonly encountered with rail, truck and ship interfaces. It is possible to simulate terminal activities for any period of time required for a specific analysis. The model's simulation output can also be modified, with little difficulty, to provide estimates of specific variables of interest for a particular terminal. Provisions for the operating environment of a terminal are also included in the model. These include week-end work rules, switching rules, container consignee notification rules, types of handling equipment employed and the standard working hours for a terminal. The primary applications of the model are viewed to be in the areas of planning and analysis for intermodal terminal current operations and future design concepts. The graphical network orientation of the model, however, could provide managers with a communications tool to apprise upper level decision makers of new concepts. Current problems, with recommended solutions, could also be visually illustrated. / Ph. D.