Benjamin Beichler

ViPMesh: A virtual prototyping framework for IEEE 802.11s wireless mesh networks

WLAN mesh networks are characterized by their flexible and low-cost deployment, scalability, and self-healing capabilities. The new WLAN standard IEEE 802.11s introduces low-level mesh interoperability. However, building large-scale real-world test beds and reproducible setups is challenging and costly. In the majority of research works, network simulation is preferred over practical measurements. Here, the main disadvantage exists in simplified device and protocol models restricting the comparability to practical implementations. In contrast, using device emulation still requires the simulation of wireless channel and environment models. Consequently, a combination of both emulation and simulation is needed to enable virtual prototyping of real applications and protocols in WLAN mesh networks. Nevertheless, the computation of complex wireless channel effects requires a decoupling of wall clock and simulation time. Therefore, we present ViPMesh, a virtual prototyping framework for IEEE 802.11s and its Linux reference implementation. ViPMesh relies on WLAN device emulation and nested virtualization using QEMU and Linux containers to support the analysis of real applications on top of an unmodified protocol stack. Adopting an alternative time source approach for QEMU, ViPMesh acts as discrete-event simulator. It further integrates channel and environment models with support for IEEE 802.11n MIMO techniques, high throughput modes, multi-channel operation, and node mobility. To the best of our knowledge, this is the first approach that combines the IEEE 802.11s reference implementation with the described simulation features. The functionality of ViPMesh is demonstrated in different example scenarios.

Evaluating Cross-Layer Cooperation of Congestion and Flow Control in IEEE 802.11s Networks

The new standard IEEE 802.11s enables vendor-independent wireless mesh networks based on the 802.11 WLAN technology. Transmission Control Protocol (TCP) is the most widespread transport protocol for reliable data delivery and still the basis for many network applications. TCP supports different mechanisms for flow and congestion control. However, designed for wired networks, it does not consider the dynamics of wireless networks and especially multi-hop wireless mesh networks. In addition, 802.11s provides own mechanisms such as Automatic Repeat Request (ARQ) for frame retransmissions to hide wireless loss from the upper layers. Being transparent to each other, retransmission schemes on both layers may interfere and operate redundantly, if not properly adjusted. We study the effects of ARQ retry limit variation on TCP throughput in a real-world multi-hop 802.11s test bed. As a result, we suggest ARQ adaptation based on the 802.11s standards Airtime Link Metric (ALM) for path selection, serving as indicator for overall frame travel time. Our proposed approach solely relies on standard features and imposes no modifications to 802.11s or TCP.

Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals

Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.

Dataflow-based modeling and performance analysis for online gesture recognition

Cyber-Physical Systems (CPS) are tightly coupled with the environment, and therefore it is important that interactions with the surroundings like Human-Computer-Interactions are performed very responsive. Since CPS are often embedded without traditional input devices, like in medical or automotive contexts, gesture recognition approaches are emerging. As those algorithms are computationally complex especially when implemented on multi-core architectures, design decisions have to be taken carefully in order to meet performance and energy constraints. In this paper, we present a Scenario-Aware Dataflow model to estimate the performance of a template-based hand gesture recognition system based on Dynamic Time Warping (DTW). Our model enables us to estimate the important characteristics like real-time capabilities for online recognition and response time of the system when implemented on a multi-core architecture. Moreover, we introduce an extension to existing SADF performance analysis tools, which enables us to acquire processor utilization from our model. Based on the performance estimations the real-time capability for online recognition was validated for different configurations and verified in our experiments.

A Parametric Dataflow Model for the Speed and Distance Monitoring in Novel Train Control Systems

The Speed and Distance Monitoring (SaDM) in a train control system is a cyber physical system, which constantly has to process information about the train and its environment. The specification of such systems, however, is often done in an informal way, hindering formal analysis and optimization. In this paper, we propose to use Parametric Synchronous Dataflow Graphs (PSDF) to formally specify the SaDM. For this purpose, the information about the environment is modeled via piecewise constant functions, where each discontinuity corresponds to a physical location. As the number of relevant locations depends on the actual track side and, thus, is unknown a priori, we use parameters to construct consistent PSDF models. Based on our formal model, we have implemented the SaDM using SCADE.