As cloud-based microservice architectures have become the foundation of contempo- rary enterprise solutions, performance interference, wherein co-located services com- pete for shared resources, remains a significant challenge. This phenomenon, often referred to as the noisy neighbor problem, manifests when one workload unexpect- edly increases the CPU, memory, disk I/O, or network consumption, resulting in latency spikes or throughput degradation for other services. While existing isolation mechanisms (e.g., cgroups and QoS policies) provide some mitigation, they rarely prevent contention entirely, particularly in dynamic, rapidly evolving environments with frequent code deployments. This thesis proposes an AIOps-driven adaptive anomaly detection framework that integrates drift detection and Transfer Learning for real-time monitoring of con- tainerized workloads. By focusing on operational metrics, including CPU, memory, I/O, and network usage, rather than solely application-level features, the system de- tects early performance interference signals. A key innovation is the application of the Kolmogorov-Smirnov (KS) test to identify statistically significant shifts in these resource distributions and automatically differentiate between benign updates and potentially disruptive anomalies. When the drift threshold is exceeded, selective re- training is initiated, ensuring that the models maintain accuracy without incurring the overhead of indiscriminate or excessively frequent retraining. Experimental validation employs Acme Air and the DeathStarBench Social Network, two diverse microservice platforms that exhibit varied resource consumption patterns. By systematically introducing new functionalities and monitoring workload evolution, the framework demonstrates how KS-based drift detection surpasses conventional static-threshold methods in identifying early-stage noisy neighbor scenarios. Transfer Learning preserves prior knowledge while adapting rapidly to novel resource-usage profiles, offering a cost-effective approach for continuous, high-precision anomaly detection. In conclusion, this thesis bridges data drift detection and system-level performance monitoring within an MLOps context. It presents a scalable and proactive strategy for mitigating performance interference in multi-tenant, cloud-native environments, ultimately enhancing reliability and preserving service-level objectives.

Die Sicherheit und Zuverlässigkeit von Anwendungen, welche schutzwürdige Daten verarbeiten, lässt sich durch die geschützte Verlagerung in die Cloud mit einer Kombination aus zielgrößenabhängiger Datenkodierung, kontinuierlicher mehrfacher Dienstauswahl, dienstabhängiger optimierter Datenverteilung und kodierungsabhängiger Algorithmen deutlich erhöhen und anwenderseitig kontrollieren. Die Kombination der Verfahren zu einer anwendungsintegrierten Stealth-Schutzschicht ist eine notwendige Grundlage für die Konstruktion sicherer Anwendungen mit zusicherbaren Sicherheitseigenschaften im Rahmen eines darauf angepassten Softwareentwicklungsprozesses. / The security and reliability of applications processing sensitive data can be significantly increased and controlled by the user by a combination of techniques. These encompass a targeted data coding, continuous multiple service selection, service-specific optimal data distribution and coding-specific algorithms. The combination of the techniques towards an application-integrated stealth protection layer is a necessary precondition for the construction of safe applications with guaranteeable safety properties in the context of a custom software development process.

Les applications reparties dans le nuage sont constituées d'un ensemble de composants logiciels interconnectés et répartis sur plusieurs machines virtuelles. Cet environnement nécessite des protocoles pour configurer dynamiquement ces applications. Nous présentons dans la première partie de cette thèse un nouveau protocole pour résoudre les dépendances dans ces applications. Ce protocole consiste à (dé) connecter et démarrer/arrêter les composants dans un ordre spécifique. Il supporte les pannes des machines virtuelles et les opérations de reconfiguration se terminent toujours avec succès. Ces machines virtuelles interagissent à travers un «publish-subscribe communication media» et se reconfigurent d'une manière décentralisée. La conception de ces protocoles étant une source d'erreurs, nous avons étudié l'utilisation du langage formelle LNT pour spécifier le protocole et les outils disponibles dans la boîte à outils CADP pour le vérifier. D'autre part, la gestion des applications reparties dans le nuage est une tâche complexe car l'administration manuelle n'est plus réaliste pour ces systèmes. Nous avons proposé d'automatiser certaines fonctions d'administration en utilisant des boucles de contrôle appelées gestionnaires autonomes. Plusieurs gestionnaires peuvent être déployés pour la gestion de la même application. Cependant, leur utilisation sans coordination peut conduire à des incohérences et des situations d'erreur. Dans la deuxième partie de cette thèse, nous avons proposé une nouvelle approche pour coordonner plusieurs gestionnaires autonomes. Cette approche repose sur une langue de coordination simple, de nouvelles techniques asynchrone pour la synthèse de contrôleur et la génération de code Java. Nous avons appliqué notre approche pour coordonner les applications de cloud computing dans le monde réel. / Cloud applications are composed of a set of interconnected software components distributed over several virtual machines. There is a need for protocols that can dynamically reconfigure such distributed applications. We present in the first part of this thesis a novel protocol, which can resolve dependencies in these applications, by (dis)connecting and starting/stopping components in a specific order. The protocol also supports virtual machine failures. The virtual machines interact through a publish-subscribe communication media and reconfigure themselves upon demand in a decentralised fashion. Designing such protocols is an error-prone task. Therefore, we investigated the use the LNT value-passing process algebra to specify the protocol and the model checking tools available in the CADP toolbox to verify it.Managing distributed cloud applications is a challenging problem because manual administration is no longer realistic for these complex distributed systems. Thus, autonomic computing is a promising solution for monitoring and updating these applications automatically. This is achieved through the automation of administration functions and the use of control loops called autonomic managers. Multiple autonomic managers can be deployed in the same system and must make consistent decisions. Using them without coordination may lead to inconsistencies and error-prone situations. In the second part of the thesis, we propose our approach for coordinating stateful autonomic managers, which relies on a simple coordination language, new techniques for asynchronous controller synthesis and Java code generation. We used our approach for coordinating real-world cloud applications.

Since the use of social media has evolved, the ability of its users to bully others has increased. One of the prevalent forms of bullying is Cyberbullying, which occurs on the social media sites such as Facebook©, WhatsApp©, and Twitter©. The past decade has witnessed a growth in cyberbullying – is a form of bullying that occurs virtually by the use of electronic devices, such as messaging, e-mail, online gaming, social media, or through images or mails sent to a mobile. This bullying is not only limited to English language and occurs in other languages. Hence, it is of the utmost importance to detect cyberbullying in multiple languages. Since current approaches to identify cyberbullying are mostly focused on English language texts, this thesis proposes a new approach (called Multilingual Cyberbullying Detection System) for the detection of cyberbullying in multiple languages (English, Hindi, and Marathi). It uses two techniques, namely, Machine Learning-based and Lexicon-based, to classify the input data as bullying or non-bullying. The aim of this research is to not only detect cyberbullying but also provide a distributed infrastructure to detect bullying. We have developed multiple prototypes (standalone, collaborative, and cloud-based) and carried out experiments with them to detect cyberbullying on different datasets from multiple languages. The outcomes of our experiments show that the machine-learning model outperforms the lexicon-based model in all the languages. In addition, the results of our experiments show that collaboration techniques can help to improve the accuracy of a poor-performing node in the system. Finally, we show that the cloud-based configurations performed better than the local configurations.

Computação nas nuvens e um novo termo criado para expressar uma tendência tecnológica recente que virtualiza o data center. Esse conceito busca um melhor aproveitamento dos recursos computacionais e dos aplicativos corporativos, virtualizados por meio de programas de virtualização de sistema operacional (SO), plataformas, infraestruturas, softwares, entre outros. Essa virtualização ocorre por intermédio de maquinas virtuais (MV) para executar aplicativos nesse ambiente virtualizado. Contudo, uma MV pode ser configurada de tal forma que seu desempenho poderá ter um atraso no processamento por conta de gargalo(s) em algum hardware alocado. A fim de maximizar a alocação do hardware na criação da MV, foi desenvolvido um método de caracterização de aplicações para a coleta de dados de desempenho e busca da melhor configuração de MV. A partir desse estudo, pode-se identificar pelo workload a classificação do tipo de aplicação e apresentar o ambiente mais adequado, um recomendado e não recomendado. Dessa forma, a tendência de se obter um desempenho satisfatório nos ambientes virtualizados pode ser descoberta pela caracterização dos programas, o que possibilita avaliar o comportamento de cada cenário e identificar situações importantes para seu bom funcionamento. Para provar essa linha de raciocínio, foram executados programas mono e multiprocessador em ambientes de monitores de maquinas virtuais. Os resultados obtidos foram satisfatórios e estão de acordo com cada característica de aplicação conhecida previamente. Porem, podem ocorrer situações de exceção nesse método, principalmente quando o monitor de maquinas virtuais, e submetido a processamentos intensos. Com isso, a aplicação pode ter um atraso no processamento por conta do gargalo de processamento no monitor de maquinas virtuais, o que modifica o ambiente ideal dessa aplicação. Portanto, este estudo apresenta um método para identificar a configuração ideal para a execução de um aplicativo. / Cloud computing represents a new age, raised to express a new technology trending that virtualizes the data center. This concept advanced to make a better use of the computational resources and corporate application, virtualizing through the programs of operating systems virtualization, platform, infrastructure, software, etc. This virtualization occurs through the virtual machine (VM) to execute virtualized applications in this environment. However, a VM may be configured in such a way that the performance delays on processing, due to overhead or other hardware allocation itself. In order to maximize the hardware allocation on MV creation, it was developed a methodology of application characterization to collect performance data and achieve the best VM configuration. After this study, based on workload metric, it is possible to identify the classification of the application type and present the best configuration, the recommended environment and the not recommended. This way, the trend to achieve a satisfactory performance in virtualized environment may be discovered through the program characterization, which possibly evaluate the behavior of each scenario and identify important conditions for its proper operation. In order to prove this argument, mono and multi core applications under monitors of virtual machines were executed. The collected results were satisfactory and are aligned with each previously known application characteristic. However, it may occur exceptions in this method, mainly when the monitor of the virtual machine monitor is submitted with high volume of processing.

Computação nas nuvens e um novo termo criado para expressar uma tendência tecnológica recente que virtualiza o data center. Esse conceito busca um melhor aproveitamento dos recursos computacionais e dos aplicativos corporativos, virtualizados por meio de programas de virtualização de sistema operacional (SO), plataformas, infraestruturas, softwares, entre outros. Essa virtualização ocorre por intermédio de maquinas virtuais (MV) para executar aplicativos nesse ambiente virtualizado. Contudo, uma MV pode ser configurada de tal forma que seu desempenho poderá ter um atraso no processamento por conta de gargalo(s) em algum hardware alocado. A fim de maximizar a alocação do hardware na criação da MV, foi desenvolvido um método de caracterização de aplicações para a coleta de dados de desempenho e busca da melhor configuração de MV. A partir desse estudo, pode-se identificar pelo workload a classificação do tipo de aplicação e apresentar o ambiente mais adequado, um recomendado e não recomendado. Dessa forma, a tendência de se obter um desempenho satisfatório nos ambientes virtualizados pode ser descoberta pela caracterização dos programas, o que possibilita avaliar o comportamento de cada cenário e identificar situações importantes para seu bom funcionamento. Para provar essa linha de raciocínio, foram executados programas mono e multiprocessador em ambientes de monitores de maquinas virtuais. Os resultados obtidos foram satisfatórios e estão de acordo com cada característica de aplicação conhecida previamente. Porem, podem ocorrer situações de exceção nesse método, principalmente quando o monitor de maquinas virtuais, e submetido a processamentos intensos. Com isso, a aplicação pode ter um atraso no processamento por conta do gargalo de processamento no monitor de maquinas virtuais, o que modifica o ambiente ideal dessa aplicação. Portanto, este estudo apresenta um método para identificar a configuração ideal para a execução de um aplicativo. / Cloud computing represents a new age, raised to express a new technology trending that virtualizes the data center. This concept advanced to make a better use of the computational resources and corporate application, virtualizing through the programs of operating systems virtualization, platform, infrastructure, software, etc. This virtualization occurs through the virtual machine (VM) to execute virtualized applications in this environment. However, a VM may be configured in such a way that the performance delays on processing, due to overhead or other hardware allocation itself. In order to maximize the hardware allocation on MV creation, it was developed a methodology of application characterization to collect performance data and achieve the best VM configuration. After this study, based on workload metric, it is possible to identify the classification of the application type and present the best configuration, the recommended environment and the not recommended. This way, the trend to achieve a satisfactory performance in virtualized environment may be discovered through the program characterization, which possibly evaluate the behavior of each scenario and identify important conditions for its proper operation. In order to prove this argument, mono and multi core applications under monitors of virtual machines were executed. The collected results were satisfactory and are aligned with each previously known application characteristic. However, it may occur exceptions in this method, mainly when the monitor of the virtual machine monitor is submitted with high volume of processing.

Die Sicherheit und Zuverlässigkeit von Anwendungen, welche schutzwürdige Daten verarbeiten, lässt sich durch die geschützte Verlagerung in die Cloud mit einer Kombination aus zielgrößenabhängiger Datenkodierung, kontinuierlicher mehrfacher Dienstauswahl, dienstabhängiger optimierter Datenverteilung und kodierungsabhängiger Algorithmen deutlich erhöhen und anwenderseitig kontrollieren. Die Kombination der Verfahren zu einer anwendungsintegrierten Stealth-Schutzschicht ist eine notwendige Grundlage für die Konstruktion sicherer Anwendungen mit zusicherbaren Sicherheitseigenschaften im Rahmen eines darauf angepassten Softwareentwicklungsprozesses.:1 Problemdarstellung 1.1 Einführung 1.2 Grundlegende Betrachtungen 1.3 Problemdefinition 1.4 Einordnung und Abgrenzung 2 Vorgehensweise und Problemlösungsmethodik 2.1 Annahmen und Beiträge 2.2 Wissenschaftliche Methoden 2.3 Struktur der Arbeit 3 Stealth-Kodierung für die abgesicherte Datennutzung 3.1 Datenkodierung 3.2 Datenverteilung 3.3 Semantische Verknüpfung verteilter kodierter Daten 3.4 Verarbeitung verteilter kodierter Daten 3.5 Zusammenfassung der Beiträge 4 Stealth-Konzepte für zuverlässige Dienste und Anwendungen 4.1 Überblick über Plattformkonzepte und -dienste 4.2 Netzwerkmultiplexerschnittstelle 4.3 Dateispeicherschnittstelle 4.4 Datenbankschnittstelle 4.5 Stromspeicherdienstschnittstelle 4.6 Ereignisverarbeitungsschnittstelle 4.7 Dienstintegration 4.8 Entwicklung von Anwendungen 4.9 Plattformäquivalente Cloud-Integration sicherer Dienste und Anwendungen 4.10 Zusammenfassung der Beiträge 5 Szenarien und Anwendungsfelder 5.1 Online-Speicherung von Dateien mit Suchfunktion 5.2 Persönliche Datenanalyse 5.3 Mehrwertdienste für das Internet der Dinge 6 Validierung 6.1 Infrastruktur für Experimente 6.2 Experimentelle Validierung der Datenkodierung 6.3 Experimentelle Validierung der Datenverteilung 6.4 Experimentelle Validierung der Datenverarbeitung 6.5 Funktionstüchtigkeit und Eigenschaften der Speicherdienstanbindung 6.6 Funktionstüchtigkeit und Eigenschaften der Speicherdienstintegration 6.7 Funktionstüchtigkeit und Eigenschaften der Datenverwaltung 6.8 Funktionstüchtigkeit und Eigenschaften der Datenstromverarbeitung 6.9 Integriertes Szenario: Online-Speicherung von Dateien 6.10 Integriertes Szenario: Persönliche Datenanalyse 6.11 Integriertes Szenario: Mobile Anwendungen für das Internet der Dinge 7 Zusammenfassung 7.1 Zusammenfassung der Beiträge 7.2 Kritische Diskussion und Bewertung 7.3 Ausblick Verzeichnisse Tabellenverzeichnis Abbildungsverzeichnis Listings Literaturverzeichnis Symbole und Notationen Software-Beiträge für native Cloud-Anwendungen Repositorien mit Experimentdaten / The security and reliability of applications processing sensitive data can be significantly increased and controlled by the user by a combination of techniques. These encompass a targeted data coding, continuous multiple service selection, service-specific optimal data distribution and coding-specific algorithms. The combination of the techniques towards an application-integrated stealth protection layer is a necessary precondition for the construction of safe applications with guaranteeable safety properties in the context of a custom software development process.:1 Problemdarstellung 1.1 Einführung 1.2 Grundlegende Betrachtungen 1.3 Problemdefinition 1.4 Einordnung und Abgrenzung 2 Vorgehensweise und Problemlösungsmethodik 2.1 Annahmen und Beiträge 2.2 Wissenschaftliche Methoden 2.3 Struktur der Arbeit 3 Stealth-Kodierung für die abgesicherte Datennutzung 3.1 Datenkodierung 3.2 Datenverteilung 3.3 Semantische Verknüpfung verteilter kodierter Daten 3.4 Verarbeitung verteilter kodierter Daten 3.5 Zusammenfassung der Beiträge 4 Stealth-Konzepte für zuverlässige Dienste und Anwendungen 4.1 Überblick über Plattformkonzepte und -dienste 4.2 Netzwerkmultiplexerschnittstelle 4.3 Dateispeicherschnittstelle 4.4 Datenbankschnittstelle 4.5 Stromspeicherdienstschnittstelle 4.6 Ereignisverarbeitungsschnittstelle 4.7 Dienstintegration 4.8 Entwicklung von Anwendungen 4.9 Plattformäquivalente Cloud-Integration sicherer Dienste und Anwendungen 4.10 Zusammenfassung der Beiträge 5 Szenarien und Anwendungsfelder 5.1 Online-Speicherung von Dateien mit Suchfunktion 5.2 Persönliche Datenanalyse 5.3 Mehrwertdienste für das Internet der Dinge 6 Validierung 6.1 Infrastruktur für Experimente 6.2 Experimentelle Validierung der Datenkodierung 6.3 Experimentelle Validierung der Datenverteilung 6.4 Experimentelle Validierung der Datenverarbeitung 6.5 Funktionstüchtigkeit und Eigenschaften der Speicherdienstanbindung 6.6 Funktionstüchtigkeit und Eigenschaften der Speicherdienstintegration 6.7 Funktionstüchtigkeit und Eigenschaften der Datenverwaltung 6.8 Funktionstüchtigkeit und Eigenschaften der Datenstromverarbeitung 6.9 Integriertes Szenario: Online-Speicherung von Dateien 6.10 Integriertes Szenario: Persönliche Datenanalyse 6.11 Integriertes Szenario: Mobile Anwendungen für das Internet der Dinge 7 Zusammenfassung 7.1 Zusammenfassung der Beiträge 7.2 Kritische Diskussion und Bewertung 7.3 Ausblick Verzeichnisse Tabellenverzeichnis Abbildungsverzeichnis Listings Literaturverzeichnis Symbole und Notationen Software-Beiträge für native Cloud-Anwendungen Repositorien mit Experimentdaten

A recent trend in software industry is to provide enterprise applications in the cloud that are accessible everywhere and on any device. As the market is highly competitive, customer orientation plays an important role. Companies therefore start providing applications as a service, which are directly configurable by customers in an online self-service portal. However, customer configurations are usually deployed in separated application instances. Thus, each instance is provisioned manually and must be maintained separately. Due to the induced redundancy in software and hardware components, resources are not optimally utilized. A multi-tenant aware application architecture eliminates redundancy, as a single application instance serves multiple customers renting the application. The combination of a configuration self-service portal with a multi-tenant aware application architecture allows serving customers just-in-time by automating the deployment process. Furthermore, self-service portals improve application scalability in terms of functionality, as customers can adapt application configurations on themselves according to their changing demands. However, the configurability of current multi-tenant aware applications is rather limited. Solutions implementing variability are mainly developed for a single business case and cannot be directly transferred to other application scenarios. The goal of this thesis is to provide a generic framework for handling application variability, automating configuration and reconfiguration processes essential for self-service portals, while exploiting the advantages of multi-tenancy. A promising solution to achieve this goal is the application of software product line methods. In software product line research, feature models are in wide use to express variability of software intense systems on an abstract level, as features are a common notion in software engineering and prominent in matching customer requirements against product functionality. This thesis introduces a framework for feature-based configuration management of reconfigurable cloud applications. The contribution is three-fold. First, a development strategy for flexible multi-tenant aware applications is proposed, capable of integrating customer configurations at application runtime. Second, a generic method for defining concern-specific configuration perspectives is contributed. Perspectives can be tailored for certain application scopes and facilitate the handling of numerous configuration options. Third, a novel method is proposed to model and automate structured configuration processes that adapt to varying stakeholders and reduce configuration redundancies. Therefore, configuration processes are modeled as workflows and adapted by applying rewrite rules triggered by stakeholder events. The applicability of the proposed concepts is evaluated in different case studies in the industrial and academic context. Summarizing, the introduced framework for feature-based configuration management is a foundation for automating configuration and reconfiguration processes of multi-tenant aware cloud applications, while enabling application scalability in terms of functionality.

A recent trend in software industry is to provide enterprise applications in the cloud that are accessible everywhere and on any device. As the market is highly competitive, customer orientation plays an important role. Companies therefore start providing applications as a service, which are directly configurable by customers in an online self-service portal. However, customer configurations are usually deployed in separated application instances. Thus, each instance is provisioned manually and must be maintained separately. Due to the induced redundancy in software and hardware components, resources are not optimally utilized. A multi-tenant aware application architecture eliminates redundancy, as a single application instance serves multiple customers renting the application. The combination of a configuration self-service portal with a multi-tenant aware application architecture allows serving customers just-in-time by automating the deployment process. Furthermore, self-service portals improve application scalability in terms of functionality, as customers can adapt application configurations on themselves according to their changing demands. However, the configurability of current multi-tenant aware applications is rather limited. Solutions implementing variability are mainly developed for a single business case and cannot be directly transferred to other application scenarios. The goal of this thesis is to provide a generic framework for handling application variability, automating configuration and reconfiguration processes essential for self-service portals, while exploiting the advantages of multi-tenancy. A promising solution to achieve this goal is the application of software product line methods. In software product line research, feature models are in wide use to express variability of software intense systems on an abstract level, as features are a common notion in software engineering and prominent in matching customer requirements against product functionality. This thesis introduces a framework for feature-based configuration management of reconfigurable cloud applications. The contribution is three-fold. First, a development strategy for flexible multi-tenant aware applications is proposed, capable of integrating customer configurations at application runtime. Second, a generic method for defining concern-specific configuration perspectives is contributed. Perspectives can be tailored for certain application scopes and facilitate the handling of numerous configuration options. Third, a novel method is proposed to model and automate structured configuration processes that adapt to varying stakeholders and reduce configuration redundancies. Therefore, configuration processes are modeled as workflows and adapted by applying rewrite rules triggered by stakeholder events. The applicability of the proposed concepts is evaluated in different case studies in the industrial and academic context. Summarizing, the introduced framework for feature-based configuration management is a foundation for automating configuration and reconfiguration processes of multi-tenant aware cloud applications, while enabling application scalability in terms of functionality.