FF-DBF-WIN: On the Forced-Forward Demand-Bound Function Analysis for Wireless Industrial Networks

Wireless Industrial Networks (WINs) have brought to the forefront the need for real-time strategies to ensure network schedulability. The Demand Bound Function (DBF) has recently been borrowed from the multicore scheduling theory and adapted to the wireless industrial domain to compute the network demand. However, a more precise estimation can be obtained by using alternative supply/demand analyses. This paper proposes the forced-forward demand bound function to estimate the network demand and better determine the schedulability of WINs.info:eu-repo/semantics/publishedVersio

Dynamic power allocation and scheduling for MIMO RF energy harvesting wireless sensor platforms

Radio frequency (RF) energy harvesting systems are enabling new evolution towards charging low energy wireless devices, especially wireless sensor networks (WSN). This evolution is sparked by the development of low-energy micro-controller units (MCU). This article presents a practical multiple input multiple output (MIMO) RF energy-harvesting platform for WSN. The RF energy is sourced from a dedicated access point (AP). The sensor node is equipped with multiple antennas with diverse frequency responses. Moreover, the platform allows for simultaneous information and energy transfer without sacrificing system duplexity, unlike time-switching RF harvesting systems where data is transmitted only for a portion of the total transmission duty cycle, or power-splitting systems where the power difference between the information signal (IS) and energy signal (ES) is neglected. The proposed platform addresses the gap between those two. Furthermore, system simulation and two energy scheduling methods between AP and sensor node (SN) are presented, namely, Continuous power stream (CPS) and intermittent power stream (IPS)

iSensA - A System for Collecting and Integrating Sensor Data

The idea of monitoring several types of parameters in various environments has been motivating significant research works in Internet of Things (IoT). This paper presents the design and construction of iSensA, a system for integrating and collecting information from sensors. The solution implements a multi-sensor monitoring system and then expands the monitoring concept to an IoT solution, by employing multi-network access, Web services, database and web and mobile applications for user interaction. iSensA system is highly configurable, enabling several monitoring solutions with different types of sensors. Experiments have been performed on real application scenarios to validate and evaluate our proposition.info:eu-repo/semantics/acceptedVersio

On the use of Wireless Sensor Networks in Preventative Maintenance for Industry 4.0

The goal of this paper is to present a literature study on the use of Wireless Sensor Networks (WSNs) in Preventative Maintenance applications for Industry 4.0. Requirements for industrial applications are discussed along with a comparative of the characteristics of the existing and emerging WSN technology enablers. The design considerations inherent to WSNs becoming a tool to drive maintenance efficiencies are discussed in the context of implementations in the research literature and commercial solutions available on the market

Is Link-Layer Anycast Scheduling Relevant for IEEE802.15.4-TSCH Networks?

International audienceWith the wide adoption of low-power wireless transmissions , industrial networks have started to incorporate wireless devices in their communication infrastructure. Specifically, IEEE802.15.4-TSCH enables slow channel hopping to increase the robustness, and relies on a strict schedule of the transmissions to increase the energy efficiency. Anycast is a link-layer technique to improve the reliability when using lossy links. Several receivers are associated to a single transmission. That way, a transmission is considered erroneous when none of the receivers was able to decode and acknowledge it. Appropriately exploited by the routing layer, we can also increase the fault-tolerance. However, most of the anycast schemes have been evaluated by simulations, for a sake of simplicity. Besides, most evaluation models assume that packet drops are independent events, which may not be the case for packet drops due to e.g. external interference. Here, we use a large dataset obtained through an indoor testbed to assess the gain of using anycast in real conditions. We also propose a strategy to select the set of forwarding nodes: they must increase the reliability by providing the most independent packet losses. We demonstrate using our experimental dataset that anycast improves really the performance, but only when respecting a set of rules to select the next hops in the routing layer

TOMAC-WSN: A new WSN efficient protocol for monitoring big distributed mechanical systems

International audienceThis paper addresses a wireless sensor network dedicated to monitor a large mechanical system. The chosen system for the scenario is a chairlift. In this case the wireless sensor network special feature is the mobility of nodes following an invariant path traveled repeatedly. A sensor node is put on each chair and a sink node is at ground at the upper end of the chairlift. A new protocol called TOMAC-WSN is designed in order to schedule frames transmission using token concept. This avoids collision at the medium access. The second concept used by TOMAC-WSN is frame aggregation. This new protocol has been modelled using Finite State Automata. An experimental implementation on Arduino boards shows the correct operation of the network. Network performance in terms of delivery time and packet loss rate is evaluated using simulation. The results show that the proposed TOMAC-WSN protocol delivers the appropriate quality of service for the monitoring of large physical systems

Cybersecurity of Industrial Cyber-Physical Systems: A Review

Industrial cyber-physical systems (ICPSs) manage critical infrastructures by controlling the processes based on the "physics" data gathered by edge sensor networks. Recent innovations in ubiquitous computing and communication technologies have prompted the rapid integration of highly interconnected systems to ICPSs. Hence, the "security by obscurity" principle provided by air-gapping is no longer followed. As the interconnectivity in ICPSs increases, so does the attack surface. Industrial vulnerability assessment reports have shown that a variety of new vulnerabilities have occurred due to this transition while the most common ones are related to weak boundary protection. Although there are existing surveys in this context, very little is mentioned regarding these reports. This paper bridges this gap by defining and reviewing ICPSs from a cybersecurity perspective. In particular, multi-dimensional adaptive attack taxonomy is presented and utilized for evaluating real-life ICPS cyber incidents. We also identify the general shortcomings and highlight the points that cause a gap in existing literature while defining future research directions.Comment: 32 pages, 10 figure

Modelización Matemática de la propagación de malware: Un nuevo enfoque basado en la seguridad de la información

[ES] En esta tesis se estudian modelos que simulan la propagación del malware. Uno de los objetivos de estos modelos es prever si una epidemia desaparece o permanece a lo largo del tiempo. Para ello se realiza un estudio de la estabilidad del modelo y se calcula el número reproductivo básico, denotado por R0. Para estudiar la estabilidad se usan los valores propios de las matrices Jacobianas, las funciones de Liapunov y el enfoque geométrico, mientras que para obtener el número reproductivo básico se utiliza el método de la siguiente generación. De este modo, se obtiene que la epidemia desaparece si R0 es menor o igual a 1 y la epidemia se mantiene si R0 > 1, entre otras propiedades. Haciendo un análisis de estos modelos se han propuesto tres mejoras en esta tesis: 1. La creación de una familia de modelos que tiene en cuenta el compartimento de los portadores, es decir, aquellos dispositivos que están infectados pero el malware no les afecta. 2. El estudio del número reproductivo básico en varias variables. 3. La redefinición de los parámetros de los modelos teniendo en cuenta las características del malware