Design and Energy Management Optimizations for Wireless Sensor Networks

Real-time monitoring of the temperature in supermarket refrigerators, testing air quality, detecting presence or position of a person indoors, monitoring the structural integrity of bridges, and measuring soil humidity for precision agriculture are only a few applications of wireless sensor networks. A wireless sensor network (WSN) is a system of spatially distributed autonomously powered embedded devices that are used to measure and collect one or more magnitudes, detect events, or both. Those devices are called wireless sensor nodes and can perform measurement or detection either independently or in cooperation with other sensor nodes of the network. WSN systems are used in applications that require distributed measurement points or mobility of the measurement points during operation. The subject of this thesis is the design of energy-efficient wireless sensor nodes and wireless sensor networks for the sub-GHz industrial scientific and medical (ISM) band, focusing on the hardware, firmware and communication protocol. Hence, the contributions span several different aspects of wireless sensor network design. A new robust wireless sensor node platform is presented; it was fully characterized and used to build a demonstration WSN that is in operation providing field results for more than two and a half years. The development, production and testing of the new wireless sensor node named RoSe (Round Sensor) is presented. Details are given on the choices of components, design priorities, production, and testing of a small prototype series. The node features a robust overmolded antenna-housing and two battery configurations. The parameters of the node are compared with those of an existing commercial sensor node that inspired the new development. During development of the low-level routines, a new technique was introduced that enables debugging and troubleshooting of an operating sensor node by using the supply current waveform measurement and a logic output. The second part of the thesis presents per-task charge consumption measurements of the RoSe node both in test conditions and while operating in the demo WSN. These measurements serve as a base for estimating the battery lifetime for a known application and communication protocol. The battery lifetimes of the nodes operating as a part of the demo WSN are reported, and by analyzing those results, battery lifetime estimations for different measurement intervals are calculated. Furthermore, a generalized overview of the ensemble of WSN parameters is given. Those parameters are then classified in groups and their interconnections are explained. Then, the network capacity limitations in terms of the number of sensor nodes and measurement intervals are derived based on radio frequency regulations and parameter interconnections. Recognizing that compliance with radio frequency regulations in Europe is one of the key constraints in single channel sub-GHz WSN development at present, we propose a new approach to regulatory compliance by introducing a firmware module for ensuring real-time regulatory compliance. The proposed firmware module was implemented and its memory and energy footprints were evaluated. Finally, we identified the need for a hardware module that will serve as an energy usage optimization block between the battery and the rest of the sensor node. The implementation of such a module requires both hardware and firmware development. To demonstrate the concept, a simplified hardware module was designed using a commercial off-the-shelf DC-DC converter and supercapacitors. The module was implemented and characterized in a new design iteration of the RoSe node and showed a possible battery autonomy extension of 19–28 %. Practical aspects of designing and building sensor nodes and a WSN are interwoven into the chapters of the thesis for completeness.

Time-Synchronization Attacks against Critical Infrastructures and their Mitigation

Marguerite Marie Nathalie Delcourt

This work focuses on the security of critical infrastructures against time-synchronization attacks (TSA). A TSA can impact any network that relies on the dynamic analysis of data, by altering the time synchronization between its nodes. Such attacked networks can start failing. Some TSAs are thwarted by cyber-security tools such as authentication and confidentiality algorithms. However, such tools cannot counter TSAs that are implemented physically. Such TSAs are undetectable but they may be detected if they lead to non-plausible observations. The identification of TSAs requires in-depth knowledge of the system's operation.We focus on TSAs in two settings. First, we consider smart grids. Their control and operation require the timely knowledge of the system state, which is inferred from an estimate computed from measurements. We consider phasor measurements taken from phasor measurement units (PMUs). However, they require a precise time synchronization, which is a weakness as existing synchronization methods are vulnerable to attacks. We aim to assess the vulnerability of the synchrophasor-based state estimation of a system, by exploring the feasibility and detectability of TSAs on PMUs. A widespread technique to make the state estimation more robust is to couple it with a bad-data detection (BDD) scheme. However, it is known that false data injection attacks and TSAs can impact the state estimation without being detected by the BDD algorithms. We present practical attack strategies for undetectable TSAs and novel vulnerability conditions. One of them is a static condition that does not depend on the measurement values. We propose a security requirement that prevents it and a greedy offline algorithm that enforces it. If this requirement is satisfied, the grid may still be attacked, although we reason that it is unlikely. We identify two sufficient and necessary vulnerability conditions which depend on the measurement values. For each, we provide a metric that shows the distance between the observed and vulnerability conditions. Enforcing our requirement requires increasing the amount of measurement points of the grid. We investigate the benefits of utilizing the three-phase model instead of the direct-sequence model for security. We show that if the power system is unbalanced, then the use of the three-phase model enables to detect attacks that are undetectable if the direct-sequence model is used. Numerical results from simulations with real load profiles from the Lausanne grid, confirm our findings. Second, we consider sensor networks for passive-source localization. We focus on the localization of a passive source from time difference of arrival (TDOA) measurements. Such measurements are highly sensitive to time-synchronization offsets. We first illustrate that TSAs can affect the localization and we show that residual analysis does not enable the detection and identification of TSAs. Second, we propose a two-step TDOA-localization technique that is robust against TSAs. It uses a known source to define a weight for each pair of sensors, reflecting the confidence in their synchronization. We then use the weighted least-squares estimator with the new weights and the TDOA measurements received from the unknown source. Our method either identifies the network as being too corrupt, or gives a corrected estimate of the unknown position along with a confidence metric. Numerical results illustrate the performance of our technique.

EPFL2021

Bringing physical layer cooperation closer to practical wireless systems

Emre Atsan

Nowadays the demand for communication over the wireless medium is significantly increasing, while the available wireless spectrum is already limited. In this thesis, we introduce new practical physical layer designs that employ node cooperation for more efficient wireless spectrum utilization. First, a cooperative scheme is introduced that takes advantage of the existence of simultaneous multiple frequency band operation in modern wireless devices. The main idea of this scheme is to use one frequency band for sharing data among collaborating nodes, and another one for cooperatively transmitting to a common destination. The benefits of such a cooperative design across frequency bands are evaluated on a testbed of software-defined radios, where we investigate and identify the possible network conditions under which our scheme enables better throughput compared to the traditional operation. Second, we present a practical design that facilitates physical layer cooperation in Long Term Evolution (LTE) networks. The main idea here is to adapt the inherent Hybrid Automatic Repeat-reQuest (H-ARQ) in standard LTE operation, so that multiple relays can cooperate over the transmission of one encoded block. Performance evaluation of the design reveals significant throughout gains under asymmetric channel conditions for parallel relay networks in LTE framework. Finally, we look at the node cooperation from a privacy perspective in wireless sensor networks. To this end, we design and evaluate a low-overhead message encryption protocol based on network coding. The main idea of the protocol is to employ node cooperation to increase the inherent weak security that network coding offers. Results show up to 60% increase in terms of extra security added on top of the inherent one.

EPFL2015

Rate allocation and optimized decoding in inter-session network coding

Eirina Bourtsoulatze

Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offers a best effort mechanism for data delivery. The emergence of new distributed network architectures, such as peer-to-peer networks and wireless mesh networks, and the need for efficient data delivery mechanisms have motivated researchers to reconsider the way that information is communicated and processed in the networks. This has given rise to a new research field called network coding. The network coding paradigm departs from the traditional routing principle where information is simply relayed by the network nodes towards the destination, and introduces some intelligence in the network through coding at the intermediate nodes. This in-network data processing has been proved to substantially improve the performance of data delivery systems in terms of throughput and error resilience in networks with high path diversity. Motivated by the promising results in the network coding research, we focus in this thesis on the design of network coding algorithms for simultaneous transmission of multiple data sources in overlay networks. We investigate several problems that arise in the context of inter-session network coding, namely (i) decoding delay minimization in inter-session network coding, (ii) distributed rate allocation for inter-session network coding and (iii) correlation-aware decoding of incomplete network coded data. We start by proposing a novel framework for data delivery from multiple sources to multiple clients in an overlay wireline network, where intermediate nodes employ randomized inter-session network coding. We consider networks with high resource diversity, which creates network coding opportunities with possibly large gains in terms of throughput, delay and error robustness. However, the coding operations in the intermediate nodes must be carefully designed in order to enable efficient data delivery. We look at the problem from the decoding delay perspective and design solutions that lead to a small decoding delay at clients through proper coding and rate allocation. We cast the optimization problem as a rate allocation problem, which seeks for the coding operations that minimize the average decoding delay in the client population. We demonstrate the validity of our algorithm through simulations in representative network topologies. The results show that an effective combination of intra- and inter-session network coding based on randomized linear coding permits to reach small decoding delays and to better exploit the available network resources even in challenging network settings. Next, we design a distributed rate allocation algorithm where the users decide locally how many intra- and inter-session network coded packets should be requested from the parent nodes in order to get minimal decoding delay. The capability to take coding decisions locally with only a partial knowledge of the network statistics is of crucial importance for applications where users are organized in dynamic overlay networks. We propose a receiver-driven communication protocol that operates in two rounds. First, the users request and obtain information regarding the network conditions and packet availability in their local neighborhood. Then, every user independently optimizes the rate allocation among different possible intra- and inter-session packet combinations to be requested from its parents. We also introduce the novel concept of equivalent flows, which permits to efficiently estimate the expected number of packets that are necessary for decoding and hence to simplify the rate allocation process. Experimental results indicate that our algorithm is capable of eliminating the bottlenecks and reducing the decoding delay of users with limited resources. We further investigate the application of the proposed distributed rate allocation algorithm to the transmission of video sequences and validate the performance of our system using the NS-3 simulator. The simulation results show that the proposed rate allocation algorithm is successful in improving the quality of the delivered video compared to intra-session network coding based solutions. Finally, we investigate the problem of decoding the source information from an incomplete set of network coded data with the help of source priors in a finite algebraic field. The inability to form a complete decoding system can be often caused by transmission losses or timing constraints imposed by the application. In this case, exact reconstruction of the source data by conventional algorithms such as Gaussian elimination is not feasible; however, partial recovery of the source data may still be possible, which can be useful in applications where approximate reconstruction is informative. We use the statistical characteristics of the source data in order to perform approximate decoding. We first analyze the performance of a hypothetical maximum a posteriori decoder, which recovers the source data from an incomplete set of network coded data given the joint statistics of the sources. We derive an upper bound on the probability of erroneous source sequence decoding as a function of the system parameters. We then propose a constructive solution to the approximate decoding problem and design an iterative decoding algorithm based on message passing, which jointly considers the network coding and the correlation constraints. We illustrate the performance of our decoding algorithm through extensive simulations on synthetic and real data sets. The results demonstrate that, even by using a simple correlation model expressed as a correlation noise between pairs of sources, the original source data can be partially decoded in practice from an incomplete set of network coded symbols. Overall, this thesis addresses several important issues related to the design of efficient data delivery methods with inter-session network coding. Our novel framework for decoding delay minimization can impact the development of practical inter-session network coding algorithms that are appropriate for applications with low delay requirements. Our rate allocation algorithms are able to exploit the high resource diversity of modern networking systems and represent an effective alternative in the development of distributed communication systems. Finally, our algorithm for data recovery from incomplete network coded data using correlation priors can contribute significantly to the improvement of the delivered data quality and provide new insights towards the design of joint source and network coding algorithms.