Aktuell beobachten wir eine drastische Vervielfältigung der Dienste und Anwendungen, die das Internet für den Datentransport nutzen. Dabei unterscheiden sich die Anforderungen dieser Dienste an das Netzwerk deutlich. Das Netzwerkmanagement wird durch diese Diversität der nutzenden Dienste aber deutlich erschwert, da es einem Datentransportdienstleister kaum möglich ist, die unterschiedlichen Verbindungen zu unterscheiden, ohne den Inhalt der transportierten Daten zu analysieren. Netzwerkvirtualisierung ist eine vielversprechende Lösung für dieses Problem, da sie es ermöglicht für verschiedene Dienste unterschiedliche virtuelle Netze auf dem gleichen physikalischen Substrat zu betreiben. Diese Diensttrennung ermöglicht es, jedes einzelne Netz anwendungsspezifisch zu steuern. Ziel einer solchen Netzsteuerung ist es, sowohl die vom Nutzer erfahrene Dienstgüte als auch die Kosteneffizienz des Datentransports zu optimieren. Darüber hinaus wird es mit Netzwerkvirtualisierung möglich das physikalische Netz so weit zu abstrahieren, dass die aktuell fest verzahnten Rollen von Netzwerkbesitzer und Netzwerkbetreiber entkoppelt werden können. Darüber hinaus stellt Netzwerkvirtualisierung sicher, dass unterschiedliche Datennetze, die gleichzeitig auf dem gleichen physikalischen Netz betrieben werden, sich gegenseitig weder beeinflussen noch stören können. Diese Arbeit  beschäftigt sich mit ausgewählten Aspekten dieses Themenkomplexes und fokussiert sich darauf, ein virtuelles Netzwerk mit bestmöglicher Dienstqualität für den Nutzer zu betreiben und zu steuern. Dafür wird ein Top-down-Ansatz gewählt, der von den Anwendungsfällen, einer möglichen Netzwerkvirtualisierungs-Architektur und aktuellen Möglichkeiten der Hardwarevirtualisierung ausgeht. Im Weiteren fokussiert sich die Arbeit dann in Richtung Bestimmung und Optimierung der vom Nutzer erfahrenen Dienstqualität (QoE) auf Applikationsschicht und diskutiert Möglichkeiten zur Messung und Überwachung von wesentlichen Netzparametern in virtualisierten Netzen. / Currently, we observe a strong growth of services and applications, which use the Internet for data transport. However, the network requirements of these applications differ significantly. This makes network management difficult, since it complicated to separate network flows into application classes without inspecting application layer data. Network virtualization is a promising solution to this problem. It enables running different virtual network on the same physical substrate. Separating networks based on the service supported within allows controlling each network according to the specific needs of the application. The aim of such a network control is to optimize the user perceived quality as well as the cost efficiency of the data transport. Furthermore, network virtualization abstracts the network functionality from the underlying implementation and facilitates the split of the currently tightly integrated roles of Internet Service Provider and network owner. Additionally, network virtualization guarantees that different virtual networks run on the same physical substrate do not interfere with each other. This thesis discusses different aspects of the network virtualization topic. It is focused on how to manage and control a virtual network to guarantee the best Quality of Experience for the user. Therefore, a top-down approach is chosen. Starting with use cases of virtual networks, a possible architecture is derived and current implementation options based on hardware virtualization are explored. In the following, this thesis focuses on assessing the Quality of Experience perceived by the user and how it can be optimized on application layer. Furthermore, options for measuring and monitoring significant network parameters of virtual networks are considered.

In the past two decades, there has been a trend to move from traditional television to Internet-based video services. With video streaming becoming one of the most popular applications in the Internet and the current state of the art in media consumption, quality expectations of consumers are increasing. Low quality videos are no longer considered acceptable in contrast to some years ago due to the increased sizes and resolution of devices. If the high expectations of the users are not met and a video is delivered in poor quality, they often abandon the service. Therefore, Internet Service Providers (ISPs) and video service providers are facing the challenge of providing seamless multimedia delivery in high quality. Currently, during peak hours, video streaming causes almost 58\% of the downstream traffic on the Internet. With higher mobile bandwidth, mobile video streaming has also become commonplace. According to the 2019 Cisco Visual Networking Index, in 2022 79% of mobile traffic will be video traffic and, according to Ericsson, by 2025 video is forecasted to make up 76% of total Internet traffic. Ericsson further predicts that in 2024 over 1.4 billion devices will be subscribed to 5G, which will offer a downlink data rate of 100 Mbit/s in dense urban environments. One of the most important goals of ISPs and video service providers is for their users to have a high Quality of Experience (QoE). The QoE describes the degree of delight or annoyance a user experiences when using a service or application. In video streaming the QoE depends on how seamless a video is played and whether there are stalling events or quality degradations. These characteristics of a transmitted video are described as the application layer Quality of Service (QoS). In general, the QoS is defined as "the totality of characteristics of a telecommunications service that bear on its ability to satisfy stated and implied needs of the user of the service" by the ITU. The network layer QoS describes the performance of the network and is decisive for the application layer QoS. In Internet video, typically a buffer is used to store downloaded video segments to compensate for network fluctuations. If the buffer runs empty, stalling occurs. If the available bandwidth decreases temporarily, the video can still be played out from the buffer without interruption. There are different policies and parameters that determine how large the buffer is, at what buffer level to start the video, and at what buffer level to resume playout after stalling. These have to be finely tuned to achieve the highest QoE for the user. If the bandwidth decreases for a longer time period, a limited buffer will deplete and stalling can not be avoided. An important research question is how to configure the buffer optimally for different users and situations. In this work, we tackle this question using analytic models and measurement studies. With HTTP Adaptive Streaming (HAS), the video players have the capability to adapt the video bit rate at the client side according to the available network capacity. This way the depletion of the video buffer and thus stalling can be avoided. In HAS, the quality in which the video is played and the number of quality switches also has an impact on the QoE. Thus, an important problem is the adaptation of video streaming so that these parameters are optimized. In a shared WiFi multiple video users share a single bottleneck link and compete for bandwidth. In such a scenario, it is important that resources are allocated to users in a way that all can have a similar QoE. In this work, we therefore investigate the possible fairness gain when moving from network fairness towards application-layer QoS fairness. In mobile scenarios, the energy and data consumption of the user device are limited resources and they must be managed besides the QoE. Therefore, it is also necessary, to investigate solutions, that conserve these resources in mobile devices. But how can resources be conserved without sacrificing application layer QoS? As an example for such a solution, this work presents a new probabilistic adaptation algorithm that uses abandonment statistics for ts decision making, aiming at minimizing the resource consumption while maintaining high QoS. With current protocol developments such as 5G, bandwidths are increasing, latencies are decreasing and networks are becoming more stable, leading to higher QoS. This allows for new real time data intensive applications such as cloud gaming, virtual reality and augmented reality applications to become feasible on mobile devices which pose completely new research questions. The high energy consumption of such applications still remains an issue as the energy capacity of devices is currently not increasing as quickly as the available data rates. In this work we compare the optimal performance of different strategies for adaptive 360-degree video streaming. / In den vergangenen zwei Jahrzehnten gab es einen starken Trend weg vom traditionellen Fernsehen hin zum Videostreaming über das Internet. Dabei macht Videostreaming zurzeit den größten Anteil des gesamten Internetverkehrs aus. Beim Herunterladen eines Internetvideos wird das Video vor dem Ausspielen in einem Puffer beim Client zwischengespeichert, um Netzfluktuationen zu kompensieren. Leert sich der Puffer, so muss das Video stoppen (Stalling), um Daten nachzuladen. Um dies zu verhindern, müssen Pufferstrategien und -Parameter optimal an Nutzerszenarien angepasst sein. Mit diesem Problem beschäftigen wir uns im ersten Kapitel dieser Arbeit unter Anwendung von Wartschlangenmodelle, numerische Simulationen und Messstudien. Zur Bewertung der Güte eines Videostreams nutzen wir ein Modell, das auf subjektiven Studien basiert. Mit HTTP Adaptive Streaming hat der Videoplayer die Fähigkeit, Videosegmente in einer an die Bandbreite angepasster Bitrate und somit auch angepasster Qualität anzufordern. Somit kann die Leerung des Puffers gebremst und Stalling verhindert werden. Allerdings hat neben Stalling auch die Videoqualität und die Anzahl der Qualitätswechsel Auswirkungen auf die Zufriedenheit der Zuschauer. Inwiefern diese Parameter optimiert werden können, untersuchen wir im zweiten Kapitel mit Hilfe von linearen und quadratischen Programmen sowie einem Warteschlangenmodell. Hierbei untersuchen wie auch die Fairness in Netzen mit mehreren Nutzern und 360-Grad Videos. Im dritten Kapitel untersuchen wir Möglichkeiten, Videostreaming ressourcenschonender zu gestalten. Hierzu untersuchen wir in einer Feldstudie die Möglichkeit Caches an WiFi-Hotspots einzusetzen und somit redundanten Verkehr zu reduzieren. Wir untersuchen das Verhalten von mobilen Videonutzern, indem wir eine Nutzerstudie auswerten. Außerdem stellen wir einen neuen Adaptionsalgorithmus vor, der abhängig vom Nutzerverhalten den Datenverbrauch und Stromverbrauch des Videostreams reduziert.

Modern disk-storage systems have to accomplish the requirements of a variety of application classes. Applications that process continuous-media data such as video and audio streams require the storage system to guarantee sustained bandwidths. Interactive applications demand the storage system to ensure bounded response times, posing timing constraints on the execution of individual disk requests. Traditional timesharing applications may require both high throughput or overall short response times. With the described applications being more and more used together in todays computing systems, the disk-storage subsystems have to efficiently combine the different requirements of this application mix. In this thesis, I develop the design of a storage system that comprehensively addresses the various challenges posed by including the support for quality-of-service guarantees in disk-storage systems. The presented storage system provides three main properties. First, the admission control includes the support for statistical guarantees to increase the share of the disk bandwidth that can be utilized by the admission control. Second, the disk-request scheduling clearly separates the enforcement of real-time guarantees from the task to establish the optimal execution order of the requests, and it provides a flexible mechanism to combine the execution of requests with different quality-of-service requirements. Finally, the file system addresses both the needs of the former two elements of the storage system and of the various file types used by the applications by providing a flexible block-allocation policy and customized client interfaces. I show the implementation of the presented designs with the DROPS Disk-Storage System and I provide a detailed evaluation based on this implementation.

Modern disk-storage systems have to accomplish the requirements of a variety of application classes. Applications that process continuous-media data such as video and audio streams require the storage system to guarantee sustained bandwidths. Interactive applications demand the storage system to ensure bounded response times, posing timing constraints on the execution of individual disk requests. Traditional timesharing applications may require both high throughput or overall short response times. With the described applications being more and more used together in todays computing systems, the disk-storage subsystems have to efficiently combine the different requirements of this application mix. In this thesis, I develop the design of a storage system that comprehensively addresses the various challenges posed by including the support for quality-of-service guarantees in disk-storage systems. The presented storage system provides three main properties. First, the admission control includes the support for statistical guarantees to increase the share of the disk bandwidth that can be utilized by the admission control. Second, the disk-request scheduling clearly separates the enforcement of real-time guarantees from the task to establish the optimal execution order of the requests, and it provides a flexible mechanism to combine the execution of requests with different quality-of-service requirements. Finally, the file system addresses both the needs of the former two elements of the storage system and of the various file types used by the applications by providing a flexible block-allocation policy and customized client interfaces. I show the implementation of the presented designs with the DROPS Disk-Storage System and I provide a detailed evaluation based on this implementation.

In future telecommunication systems, we observe an increasing diversity of access networks. The separation of transport services and applications or services leads to multi-network services, i.e., a future service has to work transparently to the underlying network infrastructure. Multi-network services with edge-based intelligence, like P2P file sharing or the Skype VoIP service, impose new traffic control paradigms on the future Internet. Such services adapt the amount of consumed bandwidth to reach different goals. A selfish behavior tries to keep the QoE of a single user above a certain level. Skype, for instance, repeats voice samples depending on the perceived end-to-end loss. From the viewpoint of a single user, the replication of voice data overcomes the degradation caused by packet loss and enables to maintain a certain QoE. The cost for this achievement is a higher amount of consumed bandwidth. However, if the packet loss is caused by congestion in the network, this additionally required bandwidth even worsens the network situation. Altruistic behavior, on the other side, would reduce the bandwidth consumption in such a way that the pressure on the network is released and thus the overall network performance is improved. In this monograph, we analyzed the impact of the overlay, P2P, and QoE paradigms in future Internet applications and the interactions from the observing user behavior. The shift of intelligence toward the edge is accompanied by a change in the emerging user behavior and traffic profile, as well as a change from multi-service networks to multi-networks services. In addition, edge-based intelligence may lead to a higher dynamics in the network topology, since the applications are often controlled by an overlay network, which can rapidly change in size and structure as new nodes can leave or join the overlay network in an entirely distributed manner. As a result, we found that the performance evaluation of such services provides new challenges, since novel key performance factors have to be first identified, like pollution of P2P systems, and appropriate models of the emerging user behavior are required, e.g. taking into account user impatience. As common denominator of the presented studies in this work, we focus on a user-centric view when evaluating the performance of future Internet applications. For a subscriber of a certain application or service, the perceived quality expressed as QoE will be the major criterion of the user's satisfaction with the network and service providers. We selected three different case studies and characterized the application's performance from the end user's point of view. Those are (1) cooperation in mobile P2P file sharing networks, (2) modeling of online TV recording services, and (3) QoE of edge-based VoIP applications. The user-centric approach facilitates the development of new mechanisms to overcome problems arising from the changing user behavior. An example is the proposed CycPriM cooperation strategy, which copes with selfish user behavior in mobile P2P file sharing system. An adequate mechanism has also been shown to be efficient in a heterogeneous B3G network with mobile users conducting vertical handovers between different wireless access technologies. The consideration of the user behavior and the user perceived quality guides to an appropriate modeling of future Internet applications. In the case of the online TV recording service, this enables the comparison between different technical realizations of the system, e.g. using server clusters or P2P technology, to properly dimension the installed network elements and to assess the costs for service providers. Technologies like P2P help to overcome phenomena like flash crowds and improve scalability compared to server clusters, which may get overloaded in such situations. Nevertheless, P2P technology invokes additional challenges and different user behavior to that seen in traditional client/server systems. Beside the willingness to share files and the churn of users, peers may be malicious and offer fake contents to disturb the data dissemination. Finally, the understanding and the quantification of QoE with respect to QoS degradations permits designing sophisticated edge-based applications. To this end, we identified and formulated the IQX hypothesis as an exponential interdependency between QoE and QoS parameters, which we validated for different examples. The appropriate modeling of the emerging user behavior taking into account the user's perceived quality and its interactions with the overlay and P2P paradigm will finally help to design future Internet applications. / Applikationen im heutigen Internet werden immer mehr durch intelligente Endknoten bereitgestellt, deren Kommunikation in logischen, virtuellen Netzwerken, (Overlays) realisiert wird. Die verstärkte Diensterbringung durch solche Overlays, wie zum Beispiel bei Peer-to-Peer Dateitauschbörsen oder Telefonie über das Internet, wird durch einen Paradigmenwechsel von Multi-Service Networks zu Multi-Network Services beschrieben. Während in einem Multi-Service Network verschiedene Dienste innerhalb eines Netzes angeboten werden, beschreibt ein Multi-Network Service die Diensterbringung über verschiedene Netze und Netzzugangstechnologien, wie es im Internet der Fall ist. Dadurch kann die technische Güte des Telekommunikationsdienstes (Quality of Service, QoS) nicht mehr die alleinige Metrik für die Qualität eines Dienstes sein. Stattdessen ist die vom Nutzer erfahrene Dienstgüte (User Perceived Quality of Experience, QoE) zu betrachten. Diese QoE muss entsprechend modelliert werden, um die Performanz von heutigen oder auch zukünftigen Internetapplikationen zu beurteilen. Die Berücksichtigung der QoE beinhaltet unter anderem auch neuartige Verhaltensweisen der Teilnehmer, die ebenfalls modelliert werden müssen. Ein Beispiel ist der Dienstabbruch durch ungeduldige Nutzer beim Herunterladen von Filmen oder bei nicht ausreichender Qualität bei Internet-Telefonie. Durch die Verschiebung der Intelligenz von Applikationen in Richtung Endknoten entstehen neu aufkommende Verhaltensweisen der Teilnehmer und sich ändernde Charakteristika des Netzwerkverkehrs, die sie von klassischen Client-Server-Anwendungen unterscheiden. Beispiele hierfür sind egoistisches oder altruistisches Nutzerverhalten bei der Einbringung von Endnutzer-Ressourcen zur Diensterbringung oder auch bösartiges Nutzerverhalten bei der gezielten Störung eines Dienstes (Pollution). In beiden Fällen sind die zeitdynamischen Verhaltensmuster (Churn, Flash Crowds) zu berücksichtigen. Um die ausgedehnten Overlay. Netze zu planen und zu evaluieren, sind überdies auch neue Leistungsbewertungsmodelle notwendig, damit zum Beispiel die Simulation skaliert oder aber auch zeitdynamische Nutzerverhalten in analytischen Modellen abgebildet wird. Diese Doktorarbeit arbeitet diese Aspekte an drei Anwendungsbeispielen auf: Verteilernetz für Dateiinhalte (Content Distribution Network), Netzwerk-basierte Videorekorder (Online TV Recorder) und Sprachtelefonie über P2P (VoP2P). Die Ergebnisse und Untersuchungen dieser Arbeit gliedern sich entsprechend dieser Anwendungsbeispiele.

Future broadband wireless networks should be able to support not only best effort traffic but also real-time traffic with strict Quality of Service (QoS) constraints. In addition, their available resources are scare and limit the number of users. To facilitate QoS guarantees and increase the maximum number of concurrent users, wireless networks require careful planning and optimization. In this monograph, we studied three aspects of performance optimization in wireless networks: resource optimization in WLAN infrastructure networks, quality of experience control in wireless mesh networks, and planning and optimization of wireless mesh networks. An adaptive resource management system is required to effectively utilize the limited resources on the air interface and to guarantee QoS for real-time applications. Thereby, both WLAN infrastructure and WLAN mesh networks have to be considered. An a-priori setting of the access parameters is not meaningful due to the contention-based medium access and the high dynamics of the system. Thus, a management system is required which dynamically adjusts the channel access parameters based on the network load. While this is sufficient for wireless infrastructure networks, interferences on neighboring paths and self-interferences have to be considered for wireless mesh networks. In addition, a careful channel allocation and route assignment is needed. Due to the large parameter space, standard optimization techniques fail for optimizing large wireless mesh networks. In this monograph, we reveal that biology-inspired optimization techniques, namely genetic algorithms, are well-suitable for the planning and optimization of wireless mesh networks. Although genetic algorithms generally do not always find the optimal solution, we show that with a good parameter set for the genetic algorithm, the overall throughput of the wireless mesh network can be significantly improved while still sharing the resources fairly among the users. / Die Anbindung an das Internet erfolgt zunehmend über drahtlose Netze. Deren Ressourcen sind allerdings limitiert, was die Anzahl der unterstützten Nutzer stark einschränkt. Zudem ist ein Trend dieser Nutzer weg von der Verwendung reiner Datendienste zu Diensten mit Echtzeitanforderungen wie Voice over IP (VoIP) zu erkennen, deren Dienstgüteanforderungen eingehalten werden müssen. Heutige drahtlose Zugangsnetze sind jedoch nur für den herkömmlichen Datenverkehr ausgelegt. Der IEEE 802.11 WLAN Standard unterscheidet zwar zwischen verschiedenen Dienstklassen, gibt aber keine Dienstgütegarantien. Um die Dienstgüte (Quality of Service, QoS), bzw. die vom Nutzer erfahrene Dienstgüte (Quality of Experience, QoE) zu garantieren, müssen die zukünftigen drahtlosen Netze daher sorgfältig geplant und optimiert werden. Um die limitierten Ressourcen auf der Luftschnittstelle effektiv zu nutzen und um Dienstgüteanforderungen für Echtzeitanwendungen einzuhalten, bedarf es eines adaptiven Ressourcenmanagements. Dabei sind sowohl drahtlose Infrastruktur, als auch drahtlose Mesh-Netze zu betrachten. Durch den randomisierten Medienzugriff und die hohe Dynamik im System ist eine a-priori Wahl der Zugangsparameter nicht sinnvoll. Vielmehr wird ein Managementsystem benötigt, das die Zugangsparameter dynamisch in Abhängigkeit der Last in einem Netz wählt. Während dies für drahtlose Infrastrukturnetze ausreicht, müssen in drahtlosen Mesh-Netzen zusätzlich noch Interferenzen von Nachbarpfaden und Eigeninterferenzen berücksichtigt werden. Desweiteren ist eine sorgfältige Planung der Kanalzuweisung und des Routings notwendig, um einerseits den Durchsatz in drahtlosen Mesh-Netzen zu maximieren und andererseits die Ressourcen fair zwischen den Stationen aufzuteilen. Da es dabei eine Vielzahl von Parametern zu berücksichtigen gilt, sind neue Optimierungsmethoden notwendig, die es ermöglichen, auch große Mesh-Netze in annehmbarer Zeit zu planen und zu optimieren. Diese Doktorarbeit arbeitet die folgenden drei Optimierungsmöglichkeiten für drahtlose Zugangsnetze aus: Optimierung der Zugangsparameter in drahtlosen Infrastrukturnetzen, Optimierung von drahtlosen Mesh-Netzen unter Berücksichtigung der QoE und Planung und Optimierung von drahtlosen Mesh-Netzen mit Berücksichtigung einer fairen Ressourcenallokation. Die Ergebnisse und Untersuchungen dieser Arbeit gliedern sich entsprechend dieser Optimierungsmöglichkeiten.

Data stream processing in the industrial as well as in the academic field has gained more and more importance during the last years. Consider the monitoring of industrial processes as an example. There, sensors are mounted to gather lots of data within a short time range. Storing and post-processing these data may occasionally be useless or even impossible. On the one hand, only a small part of the monitored data is relevant. To efficiently use the storage capacity, only a preselection of the data should be considered. On the other hand, it may occur that the volume of incoming data is generally too high to be stored in time or–in other words–the technical efforts for storing the data in time would be out of scale. Processing data streams in the context of this thesis means to apply database operations to the stream in an on-the-fly manner (without explicitly storing the data). The challenges for this task lie in the limited amount of resources while data streams are potentially infinite. Furthermore, data stream processing must be fast and the results have to be disseminated as soon as possible. This thesis focuses on the latter issue. The goal is to provide a so-called Quality-of-Service (QoS) for the data stream processing task. Therefore, adequate QoS metrics like maximum output delay or minimum result data rate are defined. Thereafter, a cost model for obtaining the required processing resources from the specified QoS is presented. On that basis, the stream processing operations are scheduled. Depending on the required QoS and on the available resources, the weight can be shifted among the individual resources and QoS metrics, respectively. Calculating and scheduling resources requires a lot of expert knowledge regarding the characteristics of the stream operations and regarding the incoming data streams. Often, this knowledge is based on experience and thus, a revision of the resource calculation and reservation becomes necessary from time to time. This leads to occasional interruptions of the continuous data stream processing, of the delivery of the result, and thus, of the negotiated Quality-of-Service. The proposed robustness concept supports the user and facilitates a decrease in the number of interruptions by providing more resources.

Das Chemnitzer StudentenNetz (CSN) setzt seit mehreren Jahren ein System zur automatischen Regelung der Bandbreite ("DynShaper") basierend auf den Grundlagen der Diplomarbeit von Jan Horbach "Dynamische Bandbreitenbeschränkung mit QoS" ein. Aufgrund der weiterhin bestehenden Notwendigkeit zum Einsatz dieses Systems, ist es nötig die DynShaper-Software zu überarbeiten, um ihre Implementierung an die Standards des CSN anzupassen und die unvollständige Dokumentation zu ergänzen. Hauptaugenmerk liegt dabei auf der Integration des Systems in die bestehende Softwarearchitektur des CSN und der Schaffung einer modularen Implementierung zur Evaluierung anderer Berechnungsverfahren.

This document specifies a simple signalling mechanism for inter-domain QoS marking using a BGP Extended Community QoS Attribute. Class based packet forwarding for delay and loss critical services is currently performed in an individual AS internal manner. The new QoS marking attribute makes the QoS class setup within the IP prefix advertising AS known to all access and transit ASes. This enables individual (re-)marking and forwarding treatment adaptation to the original QoS class setup of the respective IP prefix. The attribute provides the means to signal QoS markings on different layers, which are linked together in QoS class sets. It provides inter-domain and cross-layer insight into the QoS class mapping of the source AS with minimal signalling traffic.

The increasing number of delay and loss critical services in packet networks require differentiated packet handling in the forwarding plane. Quality of Service (QoS) guarantees can be given for networks using resource reservation and admission control. However, such strategies require complex control plane extensions and might lead to higher operation expenditures. Network operators therefore often use over-provisioning and traffic differentiation to offer cheaper class of service quality in their internet protocol (IP) packet networks. Priority marking and forwarding of packetized data traffic can be realized mainly using different layer two and three mechanisms. The number of differentiated classes and their autonomous system (AS) internal implementation is at the operator’s choice. This paper proposes a concept of cross-domain and cross-layer priority signaling between packet switched networks to be used at the inter-AS peering points. It makes use of the Border Gateway Protocol (BGP) as the predominantly used routing protocol for AS peering communication. A new BGP-4 path attribute is used to convey the structured priority information. The new concept ensures that all receiving AS peers are consistently and comprehensively informed about the QoS handling within the IP prefix originating AS. Based on this information, all ASes can perform close QoS treatment approximation in a cross-domain and cross-layer manner. The approach is now work in progress at the IETF.