Applications on mobile devices face varying network conditions in cellular networks. The connected radio cell is often changing, especially with moving devices. Different access technologies, varying signal strengths, or distance to the connected radio tower influence the Quality of Service (QoS) of mobile applications. Existing technologies like buffering or adaptive video streaming work reactive, i.e., they react to a decreasing download bitrate. In contrast, these technologies and mobile applications in general could benefit from early knowledge of the expected connection quality.This work investigates the predictability of QoS metrics in cellular networks based on the experience of previous measurements. For this, we developed an Android app to measure download bitrates with minimal data consumption. We performed over 90 000 measurements using a single network operator and analyzed how precise QoS indicators like packet round trip times and download bitrates can be predicted. We developed a methodology to predict the expected download bitrate along a route and present our approach of aggregating measurements into hexagons of dynamic size. The core contributions of this work are (i) a methodology and implementation of systematic measurement data collection, (ii) an open data publication of our measurement data set, and (iii) an approach for predicting QoS metrics in cellular networks based on aggregated measurements. Our results show, that our approach is able to predict the downlink bitrate, the packet round trip time (ping), or DNS query duration along a given route.

The critical component in any IoT application is the communication between devices. This must not only function smoothly, but also be secured. An important step in securing IoT communication is its encryption. However, in order for IoT devices to encrypt their communication with each other, they must first agree on appropriate cryptographic keys. In practice, the generation and distribution of such keys is usually managed by a central authority. However, this centralized approach has the disadvantages that (i) a central authority must be trusted, (ii) the central authority represents a single point of failure, and (iii) the central authority may be far away and thus communication with it takes a long time. To overcome these drawbacks, distributed group key agreement approaches have also been proposed. Since these distributed approaches were not originally developed for IoT devices, their performance on such devices is unknown. Therefore, in this work, we investigate the performance of a distributed group encryption scheme on IoT devices. To this end, we have built a measurement environment for distributed group encryption schemes and compare centralized and distributed group encryption schemes for IoT. Our measurements show that under perfect network conditions, the distributed approach performs worse than the centralized approaches in terms of time and memory requirements. However, our measurements also show that the distributed approach allows a group of 5 members to agree on a key in less than a minute. Thus, the distributed method can be used for small IoT groups if agreeing on a key is not time-sensitive.

The interconnectivity of devices on the Internet of Things (IoT) provides many new and smart applications. However, the integration of many devices - especially by inexperienced users - might introduce several security threats. Further, several often used communication protocols in the IoT domain are not out-of-the-boxsecured. On the other hand, security inherently introduces overhead, resulting in a decrease in performance. The Message QueuingTelemetry Transport (MQTT) protocol is a popular communication protocol for IoT applications - for example, in Industry 4.0, railways, automotive, or smart homes. This paper analyzes the influence on performance when using MQTT with TLS in terms of throughput, connection build-up times, and energy efficiency using a reproducible testbed based on a standard off-the-shelf microcontroller. The results indicate that the impact of TLS on performance across all QoS levels depends on (i) the network situation and (ii) the connection reestablishment frequency. Thus, a negative influence of TLS on the performance is noticeable only in deteriorated networksituations or at a high connection reestablishment frequency.

The number of devices connected to the Internet of Things (IoT) is continuously increasing to several billion nowadays. As those devices often share sensitive data, encryption of those data is an important issue. The pure volume of data and the complexity of communication patterns increases, and, accordingly, the importanceof group encryption is recently gaining more importance. Still, the choice of the best-suited group encryption scheme for a specific application is complicated. Benchmarks can support this choice. However, while literature distinguishes three categories for theschemes (central, decentral, and hybrid), a one-fits-all benchmark seems challenging to achieve. In this paper, we go the first step towards a structured benchmark for group encryption schemes by presenting a benchmark for centralized group encryption schemes in an IoT scenario. To this end, our benchmark includes a descriptionof workloads, a baseline scheme, a measurement setup, and metrics while also considering the requirements and features of centralized group encryption schemes.

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.

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.