Jens B. Schmitt

Sensor network calculus – a framework for worst case analysis

To our knowledge, at the time of writing no methodology exists to dimension a sensor network so that a worst case traffic scenario can be definitely supported. In this paper, the well known network calculus is tailored so that it can be used as a tool for worst case traffic analysis in sensor networks. To illustrate the usage of the resulting sensor network calculus, typical example scenarios are analyzed by this new methodology. Sensor network calculus provides the ability to derive deterministic statements about supportable operation modes of sensor networks and the design of sensor nodes.

Subjective impression of variations in layer encoded videos

Layer encoded video is an elegant way to allow adaptive transmissions in the face of varying network conditions as well as it supports heterogeneity in networks and clients. As a drawback quality degradation can occur, caused by variations in the amount of transmitted layers. Recent work on reducing these variations makes assumptions about the perceived quality of those videos. The main goal of this paper respectively its motivation is to investigate the validity of these assumptions by subjective assessment. However, the paper is also an attempt to investigate fundamental issues for the human perception of layer encoded video with time-varying quality characteristics. For this purpose, we built a test environment for the subjective assessment of layer encoded video and conducted an empirical experiment in which 66 test candidates took part. The results of this subjective assessment are presented and discussed. To a large degree we were able to validate existing (unproven) assumptions about quality degradation caused by variations in layer encoded videos, however there were also some interesting, at first sight counterintuitive findings from our experiment.

Short paper: reactive jamming in wireless networks: how realistic is the threat?

In this work, we take on the role of a wireless adversary and investigate one of its most powerful tools---radio frequency jamming. Although different jammer designs are discussed in the literature, reactive jamming, i.e., targeting only packets that are already on the air, is generally recognized as a stepping stone in implementing optimal jamming strategies. The reason is that, while destroying only selected packets, the adversary minimizes its risk of being detected. One might hope for reactive jamming to be too challenging or uneconomical for an attacker to conceive and implement due to its strict real-time requirements. Yet, in this work we disillusion from such hopes as we demonstrate that flexible and reliable software-defined reactive jamming is feasible by designing and implementing a reactive jammer against IEEE 802.15.4 networks. First, we identify the causes of loss at the physical layer of 802.15.4 and show how to achieve the best performance for reactive jamming. Then, we apply these insights to our USRP2-based reactive jamming prototype, enabling a classification of transmissions in real-time, and reliable and selective jamming. The prototype achieves a reaction time in the order of microseconds, a high precision (such as targeting individual symbols), and a 97.6% jamming rate in realistic indoor scenarios for a single reactive jammer, and over 99.9% for two concurrent jammers.

Node deployment in large wireless sensor networks: coverage, energy consumption, and worst-case delay

Node deployment is a fundamental issue to be solved in Wireless Sensor Networks (WSNs). A proper node deployment scheme can reduce the complexity of problems in WSNs as, for example, routing, data fusion, communication, etc. Furthermore, it can extend the lifetime of WSNs by minimizing energy consumption. In this paper, we investigate random and deterministic node deployments for large-scale WSNs under the following performance metrics: coverage, energy consumption, and message transfer delay. We consider three competitors: a uniform random, a square grid, and a pattern-based Tri-Hexagon Tiling (THT) node deployment. A simple energy model is formulated to study energy consumption for each deployment strategy. Using basic geometry we propose a novel strategy for calculating the relative frequency of exactly k-covered points, which uses k-coverage maps, for both a square grid and THT. To model and consequently control the worst-case delay of a given WSN we build upon the so-called sensor network calculus (a recent methodology introduced in [7]). Finally, we analyze tradeoffs between these performance metrics for each deployment strategy to show which strategy is preferable under what factors, e.g., the number of nodes.

On realistic network topologies for simulation

Simulations are an important tool in network research. As the selected topology often influences the outcome of the simulation, realistic topologies are needed to produce realistic simulation results. We first discuss the different types of topologies and present our collection of real-world topologies that can be used for simulation. We then define several similarity metrics to compare artificially generated topologies with real world topologies. We use them to find out what the input parameter range of the topology generators of BRITE, TIERS and GTITM are to create realistic topologies. These parameters can act as a valuable starting point for researchers that have to generate artificial topologies.

The DISCO network calculator: a toolbox for worst case analysis

In this paper we describe the design, implementation, and analytical background of the DISCO Network Calculator. The DISCO Network Calculator is an open-source toolbox written in Java™ which we developed for worst-case analyses based on network calculus. To our knowledge it is the first of its kind. It allows to do network analyses regarding performance characteristics such as delay and backlog bounds for piecewise linear arrival and service curves. We illustrate the tools usefulness by two comprehensive example applications.

Layer-encoded video in scalable adaptive streaming

Combining the concepts of caching and transmission control protocol (TCP)-friendly streaming of layer-encoded video bears the problem that those videos might not be cached in full quality. Therefore, we focus in this work on the scheduling of retransmissions of missing segments of a cached video in a manner that allows clients to receive the content in an improved quality. In a first step, we conducted subjective assessments of variations in layer-encoded video with the goal to validate existing quality metrics, including our own, which are based on certain assumptions. A statistical analysis of the subjective assessment validates these assumptions. We also show that the frequently used peak signal-to-noise ratio (PSNR) is not an appropriate metric for variations in layer-encoded video. With the insight from the subjective assessment we develop heuristics for retransmission scheduling and prove their applicability by conducting a series of simulations.

Jamming for good: a fresh approach to authentic communication in WSNs

While properties of wireless communications are often considered as a disadvantage from a security perspective, this work demonstrates how multipath propagation, a broadcast medium, and frequency jamming can be used as valuable security primitives. Instead of conventional message authentication by receiving, verifying, and then discarding fake data, sensor nodes are prevented from receiving fake data at all. The erratic nature of signal propagation distributes the jamming activity over the network which hinders an adversary in predicting jamming nodes and avoids selective battery-depletion attacks. By conducting real-world measurements, we justify the feasibility of such a security design and provide details on implementing it within a realistic wireless sensor network.

On the effect of node misbehavior in ad hoc networks

The dependability of the routing system in ad hoc networks inherently relies on node behavior. In order to support multihop operation in the network, most ad hoc routing algorithms assume well-behaving nodes. However, in reality there may exist constrained, selfish or malicious nodes. We discuss the influence of node misbehavior on the routing process. In particular, we derive a classification for misbehaving nodes and extend an analytical model of the route acquisition process executed by the ad hoc on-demand distance vector (AODV) routing protocol to cover different classes of misbehavior. The validation of the behavior model, and the clarification of the impact misbehaving nodes impose onto the routing process, is completed using an experimental analysis.

A Comprehensive Worst-Case Calculus for Wireless Sensor Networks with In-Network Processing

Todays wireless sensor networks (WSN) focus on energy-efficiency as the main metric to optimize. However, an increasing number of scenarios where sensor networks are considered for time-critical purposes in application scenarios like intrusion detection, industrial monitoring, or health care systems demands for an explicit support of performance guarantees in WSNs and, thus, in turn for a respective mathematical framework. In (J. Schmitt and U. Roedig, 2005) , a sensor network calculus was introduced in order to accommodate a worst-case analysis of WSNs. This sensor network calculus focused on the communication aspect in WSNs, but had not yet a possibility to treat in-network processing in WSNs. In this work, we now incorporate in-network processing features as they are typical for WSNs by taking into account computational resources on the sensor nodes. Furthermore, we propose a simple, yet effective priority queue management discipline which achieves a good balance of response times across sensor nodes in the field.