Markov reward models are commonly used in the analysis of systems by integrating a reward rate to each system state. Typically, rewards are defined based on system states and reflect the system’s perspective. From a user’s point of view, it is important to consider the changing system conditions and dynamics while the user consumes a service. The key contributions of this paper are proper definitions for (i) system-centric reward and (ii) user-centric reward of the Erlang loss model M/M/n-0 and M/M(x)/n with state-dependent service rates, as well as (iii) the analysis of the relationships between those metrics. Our key result allows a simple computation of the user-centric rewards. The differences between the system-centric and the user-centric rewards are demonstrated for a real-world cloud gaming use case. To the best of our knowledge, this is the first analysis showing the relationship between user-centric rewards and system-centric rewards. This work gives relevant and important insights in how to integrate the user’s perspective in the analysis of Markov reward models and is a blueprint for the analysis of other services beyond cloud gaming while also considering user engagement.

The recent trend to deploy programmable packet processors in cloud environaxsxsments enhances the packet processing capability without losing the flexibility to adapt the functions at runtime. In particular, distributed edge clouds can have a heterogeneous programmable processing substrate made up of different classes of devices: CPUs, NPUs, FPGAs, etc. However, managing the allocation of workloads in such a heterogeneous programmable processing substrate, in particular deciding where to instantiate a certain function, is a non-trivial task with many decisive functional and QoS-related factors. In this paper, we propose a mathematical model for optimizing the embedding of Service Function Chains implemented in P4, while considering the functional and QoS requirements associated with embedding requests, and the various types of processing devices that have different properties in terms of processing delay and supported features. To satisfy delay requirements, the problem formulation utilizes performance models to predict the forwarding latency associated with different candidate embedding options. Furthermore, a greedy solution is proposed to solve the problem in an efficient manner. Finally, a detailed numerical evaluation is conducted to evaluate the formulated model when different workload and infrastructure characteristics are varied and to evaluate the effectiveness of the proposed greedy solution.

The increasing popularity of cloud-native approaches has led to their wide adoption in the telecommunications industry. 5G Core Networks (5GCN) are developed to take advantage of cloud-native design principles, with a high degree of functional decomposition and distributed deployment. This results in implications in inter-Network Function (NF) dependencies that need to be studied. This work focuses on investigating the effect that these dependencies have in how the resources are utilized from the 5GCN NFs. We consider a private cloud environment where a reference 5G Core implementation, namely Free5GC, is deployed and orchestrated with Kubernetes. In addition, a gNB & UE Emulator is developed to allow for the execution of different control plane procedures. Our evaluations highlight the importance of catering for the inter-NF dependencies in achieving efficient resource utilization as well as avoiding deployments where a single NF can bottleneck the entire 5GCN.

Networking devices with programmable data planes, such as P4 programmable devices, are gaining more popularity because of the flexibility they provide in describing the packet processing behavior. Despite this attained flexibility, the performance of these devices can be the Achilles' heel in case the desired performance level is not met. To this end, we evaluate the performance of three state-of-the-art P4 devices focusing on the following properties: (i) the device's processing latency as a function of a scaled number of flows; (ii) the device's response time in reaction to control plane commands. The scalability analysis shows that different devices have different limits on the maximum number of flows they can support. On the other hand, the device's response time to control plane commands is found to be in milliseconds, which is three orders of magnitude larger when compared to the measured data plane's packet processing latency.

Data plane programmability brings network flexibility to a new level. However, it introduces the complexity of the data path's program as a new factor that influences packet forwarding latency and thus devices' performance. Accurate identification of the relation between data path complexity and packet forwarding latency enables the design and management of networks with predictable performance. In this article, we leverage the characteristics of P4 programming language to provide a method for estimating the packet forwarding latency as a function of the data path program. We analyze the impact of different P4 constructs on packet processing latency for three state-of-the-art P4 devices: Netronome SmartNIC, NetFPGA-SUME, and T4P4S DPDK-based software switch. Besides comparing the performance of these three targets, we use the derived results to propose a method for estimating the average packet latency, at compilation time, of arbitrary P4-based network functions implemented using the surveyed P4 constructs. The proposed method is finally validated using a set of realistic network functions, which shows that our method estimates the average packet latency with sub-microsecond precision.

The advent of programmable network switch ASICs and recent developments on other programmable data planes (NPUs, FPGAs) drive the renewed interest in network data plane programmability. The P4 language has emerged as a strong candidate to describe a protocol independent datapath pipeline. With its supported architectures, the P4 language provides an excellent way to define the packet processing and forwarding behavior, while leaving other networking components such as the traffic management engine, to non-programmable fixed function elements, based on the capabilities of most programmable devices. However, network flexibility is essential to meet the Quality of Service (QoS) requirements of traffic flows. Thus, enabling programmable control for fixed-function elements like traffic management is crucial. Towards that end we propose the use of virtual queues in the P4 pipeline, investigate the application of virtual queue-based traffic management, and portability of the approach using different P4 programmable targets. Specifically, we focus on virtual queue based Active Queue Management (AQM) for congestion policing and meeting the latency targets of distinct network slices. The solution is compared to P4 built-in functionality for bandwidth management using meters, proving also that the additional dimensions of control are achieved without compromising the processing complexity of the solution.

Software Defined Networking aims to separate network control and data plane by moving the control logic from network elements into a logically-centralized controller. Using a well-defined, unified control-channel protocol, such as OpenFlow, the controller is able to configure the forwarding behavior of data plane devices. Here, the OpenFlow protocol is translated to vendor- and device-specific instructions that, for instance, manipulate the flow table entries of a switch. In practice, SDN-enabled switches often feature different hardware capabilities and configurations with respect to the number of flow tables, their implementation, and which kind of data plane features they support. This leads to device heterogeneity within the SDN landscape, thereby obstructing the increased scalability and flexibility promised by the SDN paradigm. To overcome this challenge we propose TableVisor, a transparent proxy-layer for the SDN control channel that enables the flexible abstraction of heterogeneous data plane devices into a single emulated data plane switch. In this paper, we extend our previous work by introducing features to integrate modern P4 devices into an existing SDN environment and perform a detailed performance evaluation to quantify the overhead induced by our approach.

P4 programmable data planes are becoming more popular due to the flexibility they provide in describing the packet processing pipeline. P4 successfully abstracts the processing pipeline of data planes using a limited set of constructs. The performance variation as a function of the configured P4 pipeline is an important aspect that should be studied. Analyzing the impact of different P4 constructs on packet latency helps in understanding the overall performance of P4 programmable devices. In this paper, we analyze the impact of a basic set of P4 constructs on packet processing latency to derive the influential parameters. We use the derived results to propose a method for estimating the packet latency of P4-based network functions implemented using the surveyed P4 constructs. Finally, we validate the accuracy of the proposed method by applying it to realistic network functions.

The ongoing network softwarization trend holds the promise to revolutionize network infrastructures by making them more flexible, reconfigurable, portable, and more adaptive than ever. Still, the migration from hard-coded/hard-wired network functions toward their software-programmable counterparts comes along with the need for tailored optimizations and acceleration techniques so as to avoid or at least mitigate the throughput/latency performance degradation with respect to fixed function network elements. The contribution of this paper is twofold. First, we provide a comprehensive overview of the host-based network function virtualization (NFV) ecosystem, covering a broad range of techniques, from low-level hardware acceleration and bump-in-the-wire offloading approaches to high-level software acceleration solutions, including the virtualization technique itself. Second, we derive guidelines regarding the design, development, and operation of NFV-based deployments that meet the flexibility and scalability requirements of modern communication networks.

Network virtualization enables increasingly diverse network services to cohabit and share a given physical infrastructure and its resources, with the possibility to rely on different network architectures and protocols optimized towards specific requirements. In order to ensure a predictable performance despite shared resources, network virtualization requires a strict performance isolation and hence, resource reservations. Moreover, the creation of virtual networks should be fast and efficient. The underlying NP-hard algorithmic problem is known as the Virtual Network Embedding (VNE) problem and has been studied intensively over the last years. This paper presents NeuroViNE, a novel approach to speed up and improve a wide range of existing VNE algorithms: NeuroViNE is based on a search space reduction mechanism and preprocesses a problem instance by extracting relevant subgraphs, i.e., good combinations of substrate nodes and links. These subgraphs can then be fed to an existing algorithm for faster and more resource-efficient embeddings. NeuroViNE relies on a Hopfield network, and its performance benefits are investigated in simulations for random networks, real substrate networks, and data center networks.

Modern Software Defined Networking (SDN) applications rely on sophisticated packet processing. However, there is a mismatch between control plane requirements and data plane capabilities caused by increasing hardware heterogeneity. To overcome this challenge, we propose TableVisor, a proxy-layer for the OpenFlow control channel that enables the flexible and scalable abstraction of multiple physical devices into one emulated data plane switch that meets the requirements of the control plane application. TableVisor registers with the SDN controller as a single switch with use-case specific capabilities. It translates the instructions and rules from the control application towards the appropriate physical device where they are executed. In this paper, we present the updated architecture and functionality of TableVisor as well as first evaluation results based on testbed experiments.

Network Functions Virtualization (NFV) is a concept that aims at providing network operators with benefits in terms of cost, flexibility, and vendor independence by utilizing virtualization techniques to run network functions as software on commercial off-the-shelf (COTS) hardware. In contrast, prior solutions rely on specialized hardware for each function. Performance evaluation of such systems usually requires a dedicated testbed for each individual component. Rather than analyzing these proprietary black-box components, Virtualized Network Functions (VNFs) are pieces of software that run on COTS hardware and whose properties can be investigated in a generic testbed. However, depending on the underlying hardware, operating system, and implementation, VNFs might behave differently. Therefore, mechanisms for the performance evaluation of VNFs should be similar to benchmarking of software, where different implementations are compared by applying them to predefined test cases and scenarios. This work presents a first step towards a benchmarking framework for VNFs. Given two different implementations of a VNF that acts as LTE Serving Gateway (SGW), influence factors and key performance indicators are identified and a comparison between the two mechanisms is drawn.

Software Defined Networking (SDN) introduces the concept of logically-centralized controllers in charge of managing the forwarding behavior of network elements. The new possibilities enabled through the centralization of control logic come with a certain risk: The controller might become a performance bottleneck. Therefore, ensuring sufficient controller performance is one of the crucial tasks prior to a successful SDN deployment. Furthermore, fine-grained traffic engineering, e.g., to achieve higher link utilization, results in a higher frequency of requests that are sent to the controller, which leads to an increased controller load. It is therefore important to analyze the capabilities of SDN controllers prior to deployment. This paper investigates two software implementations, the OpenDaylight and Ryu controllers. The control message throughput of different controllers has been studied several times already; however, it is not yet known what influence the number and topology of connected switches have. This paper investigates this influence in detail for a fat-tree data center topology and a WAN topology as well as 261 topologies with varying characteristics from the Internet Topology Zoo.

Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

Today's Internet does not provide an exchange of information between applications and networks, which may result in poor application performance. Concepts such as application-aware networking or network-aware application programming try to overcome these limitations. The introduction of Software-Defined Networking (SDN) opens a path towards the realization of an enhanced interaction between networks and applications. Hence, a more dynamic and demand-based allocation of network resources to heterogeneous applications can be realized. The implementation of the resource management action, however, may have an impact on the data transport and application quality. This paper summarizes resource management mechanisms provided by current SDN approaches based on OpenFlow and exemplary evaluates implementation prospects and challenges.

No abstract available.

Since its introduction OpenFlow has been used as an enabler for network experiments in a variety of fields. Although OpenFlow was initially only used in the research domain, the concept is now finding its way into data centers due to the relatively cheap hardware and high flexibility. In this paper, we take a look at the scalability and usability of OpenFlow in data centers. Based on data center traffic models and OpenFlow measurements, we evaluate whether OpenFlow is able to cope with the short flow inter-arrival times of the traffic models by means of simulation.

No abstract available.