Showing papers presented at "Static Analysis Symposium in 2015"

Fault tolerant and scalable IoT-based architecture for health monitoring

Abstract: A novel Internet of Things based architecture supporting scalability and fault tolerance for healthcare is presented in this paper The wireless system is constructed on top of 6LoWPAN energy efficient communication infrastructure to maximize the operation time Fault tolerance is achieved via backup routing between nodes and advanced service mechanisms to maintain connectivity in case of failing connections between system nodes The presented fault tolerance approach covers many fault situations such as malfunction of sink node hardware and traffic bottleneck at a node due to a high receiving data rate A method for extending the number of medical sensing nodes at a single gateway is presented A complete system architecture providing a quantity of features from bio-signal acquisition such as Electrocardiogram (ECG), Electroencephalography (EEG), and Electromyography (EMG) to the representation of graphical waveforms of these gathered bio-signals for remote real-time monitoring is proposed

Design of sensor node for air quality crowdsensing

Abstract: Information on air-quality in urban environments is typically measured only at limited number of sites, due to cost of measurement of atmospheric concentrations of toxic gases (CO, NO 2 , SO 2 ) within accuracy boundaries defined by regulative bodies. Low spatial resolution of the mentioned environmental parameters hinders their applications in localization of the air-pollution sources, traffic regulation or studies of chronic respiratory diseases related to personal pollution exposure. Thus, we propose complementing the existing air quality monitoring infrastructure by a network of mobile sensors enabling the citizens to participate in measurement (e.g. “crowdsensing”). In this paper, we present the design of such battery-powered, wearable sensor node, housing two electrochemical gas sensors, temperature, relative humidity and atmospheric pressure sensors, with Bluetooth connectivity. Electrical, mechanical and software design are shown. Next, sensor node was characterized by evaluating the sensing accuracy and the autonomy in laboratory conditions. Accuracy within ±1 °C, ±2% RH, ±2 hPa, and ±0.6 ppm CO is shown. Autonomy is estimated at 65 h. Preliminary results of the outdoor functional test are demonstrated.

A first look at vehicle data collection via smartphone sensors

Abstract: Smartphones serve as a technical interface to the outside world These devices have embedded, on-board sensors (such as accelerometers, WiFi, and GPSes) that can provide valuable information for investigating users' needs and behavioral patterns Similarly, computers that are embedded in vehicles are capable of collecting valuable sensor data that can be accessed by smartphones through the use of On-Board Diagnostics (OBD) sensors This paper describes a prototype of a mobile computing platform that provides access to vehicles' sensors by using smartphones and tablets, without compromising these devices' security Data such as speed, engine RPM, fuel consumption, GPS locations, etc are collected from moving vehicles by using a WiFi On-Board Diagnostics (OBD) sensor, and then backhauled to a remote server for both real-time and offline analysis We describe the design and implementation details of our platform, for which we developed a library for in-vehicle sensor access and created a non-relational database for scalable backend data storage We propose that our data collection and visualization tools are useful for analyzing driving behaviors; we also discuss future applications, security, and privacy concerns specific to vehicular networks

Safety Verification and Refutation by k-invariants and k-induction

Abstract: Most software verification tools can be classified into one of a number of established families, each of which has their own focus and strengths. For example, concrete counterexample generation in model checking, invariant inference in abstract interpretation and completeness via annotation for deductive verification. This creates a significant and fundamental usability problem as users may have to learn and use one technique to find potential problems but then need an entirely different one to show that they have been fixed. This paper presents a single, unified algorithm kIkI, which strictly generalises abstract interpretation, bounded model checking and k-induction. This not only combines the strengths of these techniques but allows them to interact and reinforce each other, giving a ‘single-tool’ approach to verification.

Energy aware adaptive sampling algorithm for energy harvesting wireless sensor networks

Abstract: Wireless sensor nodes have a limited power budget, while they are often expected to be functional for a very long period of time once deployed in the field. Therefore, the minimization of energy consumption and energy harvesting technology are key tools for maximization of network lifetime and achieving self sustainability in Wireless Sensor Networks (WSN). This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities. An existing ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using an in-field testbed with a sensor node which incorporates a wind harvester and a power hungry wind speed/direction sensor. Simulation and comparison between an existing ASA and the energy aware ASA in terms of energy durability are carried out using the measured wind energy and the wind speed over a period of a month. The simulation results have shown that using ASA in combination with energy aware function on the nodes can drastically increase the lifetime of a WSN node. Moreover, the energy aware ASA in conjunction with the node energy harvesting capability can lead towards a perpetual operation of WSN and significantly outperform state-of-the-art ASA.

Smart meters as part of a sensor network for monitoring the low voltage grid

Abstract: Traditional low voltage grids are equipped with meters for the accounting of the energy consumed by customers. Recently, the use of electronic meters offers the possibility of the remote reading. This paper deals with smart sensing: a second-generation Smart Meters replacing traditional metering device, and the first generation of electronic meters, in order to extract a richer and near real-time information. This information in then transferred on a fast communication network where is needed. In other words, the Smart Meters deployed over the distribution grid create a Sensor Network used for grid control and management. The intelligent unit employed in the proposed system is able to communicate using standard metering protocols like DLMS/COSEM, allowing high-level integration with systems that use this information for both billing and customer relationship management — as is today with Automatic Meter Management systems — and for the technical management of the LV power infrastructure like Distribution Management Systems. The paper presents a pilot installation in a real grid of the smart sensor network composed about 50 new-generation Smart Meters using fast — broad-band — communication. The network of Smart Meters has been used to monitor, during a measurement campaign of two months, the Power Quality of a part of the distribution grid. During the campaign, the grid voltage is below the 5 % of the nominal value only for the 3 % of the time, despite the large presence of distributed renewable resources.

Effective Soundness-Guided Reflection Analysis

Abstract: We introduce Solar, the first reflection analysis that allows its soundness to be reasoned about when some assumptions are met and produces significantly improved under-approximations otherwise. In both settings, Solar has three novel aspects: (1) lazy heap modeling for reflective allocation sites, (2) collective inference for improving the inferences on related reflective calls, and (3) automatic identification of “problematic” reflective calls that may threaten its soundness, precision and scalability, thereby enabling their improvement via lightweight annotations. We evaluate Solar against two state-of-the-art solutions, Doop and Elf, with the three treated as under-approximate reflection analyses, using 11 large Java benchmarks and applications. Solar is significantly more sound while achieving nearly the same precision and running only several-fold more slowly, subject to only 7 annotations in 3 programs.

Synchronisation using wireless trigger-broadcast for impedance spectroscopy of battery cells

Abstract: In electric vehicles, batteries with many cells are used to supply the high voltages needed for the power train. The battery is controlled by a battery management system (BMS) which needs measurement data from each individual cell. Up to now, wired solutions with specialized measurement controllers for battery modules are in use. Some of these communicate over data bus structures. Our group proposes as an alternative solution the use of wireless communication in the near RF field area. The basics of this solutions have already been published [1]. In this article we present more advanced functionality for the wireless sensors approach. A functional module has been developed for impedance spectroscopy of each individual cell in the battery stack during automotive operation. Electrochemical impedance spectroscopy is a powerful method to determine the battery state beyond common and simple models. This technique needs precise and synchronized measurements of the common current and the voltages of the individual cells. A communication and control protocol has been implemented in hard- and software, including a trigger-broadcast operating mode. This solution has to fulfill the time precision requirements of the distributed measurements in the range of a few μs. Therefore, proprietary protocol solutions have been developed. Additional modules in the sensor system allow other functions such as cell balancing and an energy saving wake-up function for the sensor modules. These sensor modules are designed as tailored hardware for integration inside the individual battery cells.

b+WSN: Smart beehive for agriculture, environmental, and honey bee health monitoring — Preliminary results and analysis

Abstract: In recent years, various United Nations reports have stressed the growing constraint of food supply for Earth's growing human population. Honey bees are a vital part of the food chain as the most important pollinator insect for a wide range of crops. It is clear that protecting the population of honey bees worldwide, as well as enabling them to maximise their productivity, is an important concern. The work described in this paper utilised heterogeneous wireless sensor networks technologies to gather data unobtrusively from a beehive, describing the conditions and activity of the honey bee colony. A wide range of sensors were deployed for monitoring the multidimensional conditions within a living beehive (including oxygen, carbon dioxide, pollutant levels, temperature, and humidity). Meteorological and environmental conditions outside the hive were also monitored throughout the deployment. The data were then analysed from a biological perspective to provide insights into honey bee behaviour and health. This led to the development of an algorithm for automatically determining the status of the bee colony. Analysis was also undertaken from a meteorological perspective, which led to the development of an algorithm for predicting short term external weather conditions (rain) based on the conditions observed within the hive. The meteorological conditions were seen to have an impact on the data provided by biological sensors (bees) and physical sensors. This can be exploited to improve the accuracy of local weather prediction. Applications of this algorithm include agricultural and environmental monitoring for accurate short term forecasts for the area local to the beehive.

Unmanned aerial gas leakage localization and mapping using microdrones

Abstract: We present an autonomous-mobile gas detection system to assess the measurement of specific gas concentrations in a wide range of outdoor applications. This is especially of interest in those harsh environments where it is impractical or uneconomical to install a fixed array of gas sensors. The system is able to work in potentially hazardous emissions areas — toxic gas leakages — in completely secure working conditions for the operators. Used as payload on a Unmanned Aerial Vehicle (UAV), it can provide gas measurements with adaptive and high resolution sampling rates in accordance to gas concentration and carrier speed. Each measurement is associated with the location provided by the embedded GPS module. Remarkable features are the small size, the low power consumption and costs, compared to traditional systems. Finally, we presents a novel approach to optimize the speed of the vehicle and the system power consumption based on gas sampling frequency, which allows lifetime maximization and leakage detection reliability.

A Simple Abstraction of Arrays and Maps by Program Translation

Abstract: We present an approach for the static analysis of programs handling arrays, with a Galois connection between the semantics of the array program and semantics of purely scalar operations. The simplest way to implement it is by automatic, syntactic transformation of the array program into a scalar program followed analysis of the scalar program with any static analysis technique (abstract interpretation, acceleration, predicate abstraction,...). The scalars invariants thus obtained are translated back onto the original program as universally quantified array invariants. We illustrate our approach on a variety of examples, leading to the “Dutch flag” algorithm.

Non-intrusive Zigbee power meter for load monitoring in smart buildings

Abstract: Energy efficiency in smart buildings requires distributed sensing infrastructure to monitor the power consumption of appliances, machines and lighting sources. The analysis of current and voltage waveforms is fundamental for gathering diagnostic information about the power quality and for reducing power wastage. Moreover, it enables Non-intrusive Load Monitoring (NILM), which is the process of disaggregating a household's total electricity consumption into its contributing appliances, by analysing the voltage and current changes. In this paper, an innovative full Energy-neutral (i.e. battery free) and Non-intrusive Wireless Energy Meter (NIWEM) is presented to measure current, voltage and power factor. As key features, the NIWEM is completely non-invasive and it can self-sustain its operations by harvesting energy from the monitored load. It also features a standard (Zigbee) wireless interface for communication with the smart-building system. Experimental results have confirmed that complete energy sustainability can be achieved also with very low-power loads.

SVM-based fall detection method for elderly people using Android low-cost smartphones

Abstract: Nowadays society is moving to a scenery where autonomous elderly live alone in their houses. An automatic remote monitoring system using wearable and ambient sensors is becoming even more important, and is a challenge for the future in WSNs, AAL, and Home Automation areas. Relating to this, one of the most critical events for the safety and the health of the elderly is the fall. Lot of methods, applications, and stand-alone devices have been presented so far. This work proposes a novel method based on the Support Vector Machine technique and addressed to Android low-cost smartphones. Our method starts from data acquired from accelerometer and magnetometer, now available in all the low-end devices, and uses a set of features extracted from a processing of the two signals. After an initial training, the classification of fall events and non-fall events is performed by the Support Vector Machine algorithm. Since we have decided to use the smartphone as monitoring device, the use of other invasive wearable sensors is avoided, and the user have simply to hold the phone on his pocket. Moreover, we can use the cellular network for the eventual sending of notifications and alerts to relatives in case of falls. Actually, our tests show a good performance with a sensitivity of 99.3% and a specificity of 96%.

Unbounded-Time Analysis of Guarded LTI Systems with Inputs by Abstract Acceleration

Abstract: Linear Time Invariant (LTI) systems are ubiquitous in software systems and control applications. Unbounded-time reachability analysis that can cope with industrial-scale models with thousands of variables is needed. To tackle this general problem, we use abstract acceleration, a method for unbounded-time polyhedral reachability analysis for linear systems. Existing variants of the method are restricted to closed systems, i.e., dynamical models without inputs or non-determinism. In this paper, we present an extension of abstract acceleration to linear loops with inputs, which correspond to discrete-time LTI control systems, and further study the interaction with guard conditions. The new method relies on a relaxation of the solution of the linear dynamical equation that leads to a precise over-approximation of the set of reachable states, which are evaluated using support functions. In order to increase scalability, we use floating-point computations and ensure soundness by interval arithmetic. Our experiments show that performance increases by several orders of magnitude over alternative approaches in the literature. In turn, this tremendous speedup allows us to improve on precision by computing more expensive abstractions. We outperform state-of-the-art tools for unbounded-time analysis of LTI system with inputs in speed as well as in precision.

How could sensor networks help with agricultural water management issues? Optimizing irrigation scheduling through networked soil-moisture sensors

Abstract: Irrigated agriculture provides 40% of the World's food from 20% of the agricultural land but uses 70% of all global freshwater withdrawals. However, even supposedly efficient and well-managed irrigation systems waste up to 50% of the water applied to the crops under them. Meeting the food needs of an increasing world population from a static or even decreasing land base will, therefore require improved efficiencies in irrigated agriculture and better use of these finite water resources. The first part of this paper reports on a field-based research project which examined a suite of conventional and alternative irrigation systems which were installed at a farm in south west Australia and assessed and compared in terms of their Water Use Efficiency. All “alternative” systems outperformed the conventional surface (flood) irrigation systems with comparative water savings of around 50%. The second part of the paper assesses the potential Water Use Efficiency improvements at farm and system-scales which could be achieved through linking these irrigation systems to wireless soil-moisture sensor networks which are being developed by the authors and which are reported in detail in associate papers. Improving irrigation scheduling and management by better (and, where appropriate, automatic) links to near real-time soil moisture data is shown to produce water savings of up to 30 GL per year at the irrigation system scale.

Sustainable energy harvesting for robust wireless sensor networks in industrial applications

Abstract: Wireless Sensor Networks (WSNs) are at the verge of a broad acceptance in demanding industrial applications Nodes must fulfill key requirements like reliability and deterministic communication, but also energy autarky in order to allow maintenance-free systems In this paper a system combining low power, robust communication with appropriate methods for energy harvesting and energy management is suggested By comparing two alternative variants for powermanagement, constraints of a solar-cell powered node design are derived The resulting system demonstrates energy sufficiency at standard industrial indoor lighting conditions of 1300 lx for sensor nodes sampling temperature values at 10 Hz and transmitting once per second

Measurement system for determining the magnetic polarizability tensor of small metal targets

Abstract: This paper presents an apparatus to measure the spectroscopic magnetic response of small metallic objects and deduce the magnetic polarizability tensor. The measured transimpedances of a .222 Remington rifle cartridge and titanium cube are compared to simulated results and are found to match well providing verification of the method. The eigenvalues of the two objects are calculated and discussed highlighting the potential discriminatory aspect. The results support the proposed use of the eigenvalue spectra to provide subsurface classification and discrimination between landmines and clutter.

Operating frequency selection for low-power magnetic induction-based wireless underground sensor networks

Abstract: The possibility of employing sensor nodes that wireless communicate under the ground, through concrete, or under-the-debris (disaster scenario) has been recently highlighted at the Wireless Underground Sensor Networks (WUSN) literature. Nonetheless, the best operating frequency for such systems is still an open research aspect. In this work, we address this question for mid-range distances (e.g., 15‥30m) by proposing a soil path attenuation model for an underground magnetic induction (MI)-based system involving a pair of nodes. The model is empirically validated and based on simulation results it is possible to conclude that for mid-range MI systems it is strategic to adopt a dynamic frequency selection scheme where audio frequencies are chosen whenever high soil moisture levels are detected.

De-icing system with integrated ice detection and temperature sensing for meteorological devices

Abstract: We present a de-icing system indented for application with meteorological sensors in harsh environments. The heating unit is implemented as a double-meander structure on a printed circuit board. The double-meander structure allows for measuring capacitance in the differential mode. The presence of ice (and water) leads to an increase of the capacitance and can thus be detected. Additionally, the temperature of the heating unit can be obtained from the temperature dependent variation of the ohmic resistance of the heating structure. With this information the heating unit can be controlled efficiently as excessive heating or heating in the absence of ice can be avoided.

Refinement Type Inference via Horn Constraint Optimization

Abstract: We propose a novel method for inferring refinement types of higher-order functional programs. The main advantage of the proposed method is that it can infer maximally preferred (i.e., Pareto optimal) refinement types with respect to a user-specified preference order. The flexible optimization of refinement types enabled by the proposed method paves the way for interesting applications, such as inferring most-general characterization of inputs for which a given program satisfies (or violates) a given safety (or termination) property. Our method reduces such a type optimization problem to a Horn constraint optimization problem by using a new refinement type system that can flexibly reason about non-determinism in programs. Our method then solves the constraint optimization problem by repeatedly improving a current solution until convergence via template-based invariant generation. We have implemented a prototype inference system based on our method, and obtained promising results in preliminary experiments.

Steven D. Levitt & Stephen J. Dubner, Freakonomics: A rogue economist explores the hidden side of everything

Abstract: CONTENTS AN EXPLANATORY NOTE In which the origins of this book are clarified. INTRODUCTION: The Hidden Side of Everything In which the book’s central idea is set forth: namely, if morality represents how people would like the world to work, then economics shows how it actually does work. Why the conventional wisdom is so often wrong...How “experts”—from criminologists to real-estate agents to political scientists—bend the facts...Why knowing what to measure, and how to measure it, is the key to understanding modern life...What is “freakonomics,” anyway? 1. What Do Schoolteachers and Sumo Wrestlers Have in Common?

SJS: A Type System for JavaScript with Fixed Object Layout

Abstract: We propose a static type system for a significant subset of JavaScript, dubbed SJS, with the goal of ensuring that objects have a statically known layout at the allocation time, which in turn can enable an ahead-of-time (AOT) compiler to generate efficient code.The main technical challenge we address is to ensure fixed object layout, while supporting popular language features such as objects with prototype inheritance, structural subtyping, and method updates, with the additional constraint that SJS programs can run on any available standard JavaScript engine, with no deviation from JavaScript’s standard operational semantics. The core difficulty arises from the way standard JavaScript semantics implements object attribute update with prototype-based inheritance. To our knowledge, combining a fixed object layout property with prototype inheritance and subtyping has not been achieved previously.

Self-powered wireless sensor nodes for monitoring radioactivity in contaminated areas using unmanned aerial vehicles

Abstract: A self-sustainable wireless sensor node for the monitoring radiation in contaminated and poorly accessible areas is presented. The node is designed to work in collaboration with an unmanned aerial vehicle used for two essential mission steps: air-deploying the wireless sensor nodes at suitable locations and acquiring data logs via ultra-low power, short-range radio communication in fly-by mode, after a wake-up routine. The system allows for the use of off-the-shelf components for defining mission, drop-zone and trajectory, for compressing data, and for communication management. The node is equipped with a low-power nuclear radiation sensor and it was designed and implemented with self-sustainability in mind as it will be deployed in hazardous, inaccessible areas. To this end, the proposed node uses a combination of complementary techniques: a low-power microcontroller with non-volatile memory, energy harvesting, adaptive power management and duty cycling, and a nano-watt wake-up radio. Experimental results show the power consumption efficiency of the solution, which achieves 70uW in sleep mode and 500uW in active mode. Finally, simulations based on actual field measurements confirm the solution's self-sustainability and illustrate the impact of different sampling rates and that of the wake-up radio.

A Kinect-based system to enable interaction by pointing in smart spaces

Abstract: Pointing is a universal gesture that naturally expresses interest or attraction towards the pointed items. If some ‘magic’ is added, the gesture may also make these items perform actions. In this paper, we describe a system that enables to interact by pointing with digital or physical controllable resources distributed in a smart space. The system facilitates building an interactive room using COTS devices, in particular a pair of Kinect sensors. The pointing direction is inferred from the user's elbow-wrist vector, which together with a secondary elbow-object vector serves to filter the controllable objects in the area of pointing. Experiments with 8 users in a real setting demonstrate the feasibility of the concept and show that the accuracy of the system is very dependent on the relative position user-resource and on the user behaviour itself.

Property-based Polynomial Invariant Generation Using Sums-of-Squares Optimization

Abstract: While abstract interpretation is not theoretically restricted to specific kinds of properties, it is, in practice, mainly developed to compute linear over-approximations of reachable sets, aka. the collecting semantics of the program. The verification of user-provided properties is not easily compatible with the usual forward fixpoint computation using numerical abstract domains.

Capacitive sensor for respiration monitoring

Abstract: Respiration monitoring of patients with chronic diseases, children, elderly, or sportsmen can be a useful tool in health condition assessment, early diagnosis of various diseases, and real-time prediction of possibly dangerous health conditions. In this paper we present a low-cost solution of respiration monitoring system, based on a custom designed capacitive sensor, which comprises of two moveable electrodes, mounted on a rigid belt attached around the person's chest. One electrode is fixed while the other one moves in a rhythm of breathing, with restriction of movement in one axis only. The electrode geometry was optimized by numeric electromagnetic simulations to provide linearity and measurable level in change of capacitance, even for case of shallow breathing. Input measuring chain is based on capacitance-to-digital (CDC) integrated circuit and it is able to capture the changes of up to several hundreds of femtofarads in full scale, with enough resolution to enable breathing rate detection, and discrimination of cases of deep, shallow, and no breathing by signal processing algorithms. The prototype measurement system was designed and tested in laboratory on several test subjects. Preliminary experiments showed that the proposed measurement system for respiration monitoring can be used for low-cost and low-power integrated solution for continuous monitoring of patient's respiration.

Prediction of the asymptotical magnetic polarization tensors for cylindrical samples using the boundary element method

Abstract: The magnetic polarization tensor is a frequency-dependent, rotation-invariant and object-specific property of a metallic object This paper presents an approach to compute the magnetic polarization tensor of a metallic object based on the Boundary Element Method (BEM), which treats the object as a perfect electrical conductor (PEC) and therefore is able to predict the limiting cases where very high frequency and/or high conductivity is assumed A uniform magnetic field is applied to an object and the scattered field at a certain distance is obtained in the simulations The magnetic tensor can then be deduced from the scattered field The simulated results agree well with an analytical solution for spheres and with measured results for a number of cylinders for limiting cases

A Binary Decision Tree Abstract Domain Functor

Abstract: We present an abstract domain functor whose elements are binary decision trees. It is parameterized by decision nodes which are a set of boolean tests appearing in the programs and by a numerical or symbolic abstract domain whose elements are the leaves. We first define the branch condition path abstraction which forms the decision nodes of the binary decision trees. It also provides a new prospective on partitioning the trace semantics of programs as well as separating properties in the leaves. We then discuss our binary decision tree abstract domain functor by giving algorithms for inclusion test, meet and join, transfer functions and extrapolation operators. We think the binary decision tree abstract domain functor may provide a flexible way of adjusting the cost/precision ratio in path-dependent static analysis.

The impact of elimination of the most critical node on Wireless Sensor Network lifetime

Abstract: Wireless Sensor Network (WSN) paradigm is an integral component of ubiquitous computing and Machine-to-Machine communications. Since WSNs are widely used in homeland security, military applications, next generation power lines, critical infrastructure monitoring and smart spaces, they are naturally attractive to the adversaries and vulnerable to natural conditions because of their harsh topologies. Although, there are some solutions against Denial of Service (DoS) attacks conducted against single or multiple sensor nodes in WSNs, WSNs are, at best, weakly defended against more sophisticated attack types. Therefore, the period that the sensor network will stand out against such attacks has a crucial importance to calculate intervention or backup times for WSNs. In this study, we propose a linear programming (LP) approach for modeling the impact of single node attacks on network lifetime in WSNs. We explored the parameter space through the numerical evaluations of the LP model to quantify the impact of elimination of the most critical node on WSN lifetime.