arXiv subjects

Jens B. Schmitt

Publications and source records attributed to Jens B. Schmitt.

7 recordsLinked to original sources

arXiv2025

Minimal Per-Flow Backlog Bounds at an Aggregate FIFO Server under Piecewise-Linear Arrival Curves

Network Calculus (NC) is a versatile methodology based on min-plus algebra to derive worst-case per-flow performance bounds in networked systems with many concurrent flows. In particular, NC can analyze many scheduling disciplines; yet, somewhat surprisingly, an aggregate FIFO server is a notoriously hard case due to its min-plus non-linearity. A resort is to represent the FIFO residual service by a family of functions with a free parameter instead of just a single curve. For simple token-bucket arrival curves, literature provides optimal choices for that free parameter to minimize delay and backlog bounds. In this paper, we tackle the challenge of more general arrival curves than just token buckets. In particular, we derive residual service curves resulting in minimal backlog bounds for general piecewise-linear arrival curves. To that end, we first show that a backlog bound can always be calculated at a breakpoint of either the arrival curve of the flow of interest or its residual service curve. Further, we define a set of curves that characterize the backlog for a fixed breakpoint, depending on the free parameter of the residual service curve. We show that the backlog-minimizing residual service curve family parameter corresponds to the largest intersection of those curves with the arrival curve. In more complex scenarios finding this largest intersection can become inefficient as the search space grows in the number of flows. Therefore, we present an efficient heuristic that finds, in many cases, the optimal parameter or at least a close conservative approximation. This heuristic is evaluated in terms of accuracy and execution time. Finally, we utilize these backlog-minimizing residual service curves to enhance the DiscoDNC tool and observe considerable reductions in the corresponding backlog bounds.

cs.NI↗

arXiv2024

Extending Network Calculus To Deal With Partially Negative And Decreasing Service Curves

Network Calculus (NC) is a versatile analytical methodology to efficiently compute performance bounds in networked systems. The arrival and service curve abstractions allow to model diverse and heterogeneous distributed systems. The operations to compute residual service curves and to concatenate sequences of systems enable an efficient and accurate calculation of per-flow timing guarantees. Yet, in some scenarios involving multiple concurrent flows at a system, the central notion of so-called min-plus service curves is too weak to still be able to compute a meaningful residual service curve. In these cases, one usually resorts to so-called strict service curves that enable the computation of per-flow bounds. However, strict service curves are restrictive: (1) there are service elements for which only min-plus service curves can be provided but not strict ones and (2) strict service curves generally have no concatenation property, i.e., a sequence of two strict systems does not yield a strict service curve. In this report, we extend NC to deal with systems only offering aggregate min-plus service curves to multiple flows. The key to this extension is the exploitation of minimal arrival curves, i.e., lower bounds on the arrival process. Technically speaking, we provide basic performance bounds (backlog and delay) for the case of negative service curves. We also discuss their accuracy and show them to be tight. In order to illustrate their usefulness we also present patterns of application of these new results for: (1) heterogeneous systems involving computation and communication resources and (2) finite buffers that are shared between multiple flows.

cs.NI↗

arXiv2017

Quality and Cost of Deterministic Network Calculus - Design and Evaluation of an Accurate and Fast Analysis

Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of DNC results has been improved steadily, resulting in two DNC branches: the classical algebraic analysis and the more recent optimization-based analysis. The optimization-based branch provides a theoretical solution for tight bounds. Its computational cost grows, however, (possibly super-)exponentially with the network size. Consequently, a heuristic optimization formulation trading accuracy against computational costs was proposed. In this paper, we challenge optimization-based DNC with a new algebraic DNC algorithm. We show that: (i) no current optimization formulation scales well with the network size and (ii) algebraic DNC can be considerably improved in both aspects, accuracy and computational cost. To that end, we contribute a novel DNC algorithm that transfers the optimization's search for best attainable delay bounds to algebraic DNC. It achieves a high degree of accuracy and our novel efficiency improvements reduce the cost of the analysis dramatically. In extensive numerical experiments, we observe that our delay bounds deviate from the optimization-based ones by only 1.142% on average while computation times simultaneously decrease by several orders of magnitude.

cs.NI↗

arXiv2014

An Analytical Model of Packet Collisions in IEEE 802.15.4 Wireless Networks

Numerous studies showed that concurrent transmissions can boost wireless network performance despite collisions. While these works provide empirical evidence that concurrent transmissions may be received reliably, existing signal capture models only partially explain the root causes of this phenomenon. We present a comprehensive mathematical model that reveals the reasons and provides insights on the key parameters affecting the performance of MSK-modulated transmissions. A major contribution is a closed-form derivation of the receiver bit decision variable for arbitrary numbers of colliding signals and constellations of power ratios, timing offsets, and carrier phase offsets. We systematically explore the root causes for successful packet delivery under concurrent transmissions across the whole parameter space of the model. We confirm the capture threshold behavior observed in previous studies but also reveal new insights relevant for the design of optimal protocols: We identify capture zones depending not only on the signal power ratio but also on time and phase offsets.

cs.NI↗

arXiv2013

Measurement and Prediction of Centrical/Peripheral Network Properties based on Regression Analysis - A Parametric Foundation for Performance Self-Management in WSNs

Predicting performance-related behavior of the underlying network structure becomes more and more indispensable in terms of the aspired application outcome quality. However, the reliable forecast of QoS metrics like packet transfer delay in wireless network systems is still a challenging task. Even though existing approaches are technically capable of determining such network properties under certain assumptions, they mostly abstract away from primal aspects that inherently have an essential impact on temporal network performance dynamics. Also, they usually require auxiliary resources to be implemented and deployed along with the actual network components. In the course of developing a lightweight measurement-based alternative for the self-inspection and prediction of volatile performance characteristics in environments of any kind, we selectively investigate the duration of message delivery and packet loss rate against various parameters peculiar to common radio network technologies like Wireless Sensor Networks (WSNs). Our hands-on experiments reveal the relations between the oftentimes underestimated medium access delay and a variety of main influencing factors including packet size, backoff period, and number of neighbor nodes contending for the communication medium. A closed formulation of selected weighted drivers facilitates the average-case prediction of inter-node packet transfer delays for arbitrary configurations of given network parameters even on resource-scarce WSN devices. We validate our prediction method against basic multi-hop networking scenarios. Yield field test results proof the basic feasibility and high precision of our approach to network property estimation in virtue of self-governed local measurements and regression-based calculations paving the way for a prospective self-management of network properties based upon autonomous distributed coordination.

cs.PF↗

arXiv2013

Air Dominance in Sensor Networks: Guarding Sensor Motes using Selective Interference

Securing wireless sensor networks (WSNs) is a hard problem. In particular, network access control is notoriously difficult to achieve due to the inherent broadcast characteristics of wireless communications: an attacker can easily target any node in its transmission range and affect large parts of a sensor network simultaneously. In this paper, we therefore propose a distributed guardian system to protect a WSN based on physically regulating channel access by means of selective interference. The guardians are deployed alongside a sensor network, inspecting all local traffic, classifying packets based on their content, and destroying any malicious packet while still on the air. In that sense, the system tries to gain "air dominance" over attackers. A key challenge in implementing the guardian system is the resulting real-time requirement in order to classify and destroy packets during transmission. We present a USRP2 software radio based guardian implementation for IEEE 802.15.4 that meets this challenge; using an FPGA-based design we can even check for the content of the very last payload byte of a packet and still prevent its reception by a potential victim mote. Our evaluation shows that the guardians effectively block 99.9% of unauthorized traffic in 802.15.4 networks in our experiments, without disturbing the legitimate operations of the WSN.

cs.NI↗

arXiv2010

Key Generation in Wireless Sensor Networks Based on Frequency-selective Channels - Design, Implementation, and Analysis

Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the error correction property of the protocol mitigates the effects of measurement errors and other temporal effects, giving rise to an agreement rate of over 97%. We show the applicability of our protocol by implementing it on MICAz motes, and evaluate its robustness and secrecy through experiments and analysis.

cs.CR↗