Energy-Efficient Routing Protocol for Selecting Relay Nodes in Underwater Sensor Networks Based on Fuzzy Analytical Hierarchy Process

The use of underwater sensor networks (UWSNs) offers great advantages in many automatic observation services such as water monitoring (ocean, sea, etc.) and registering of geological events (landslides, earthquakes). However, UWSNs have many more limitations than terrestrial sensor networks (smaller bandwidth, higher delays, etc.) with new requirements such as low power consumption by nodes or being able to select appropriate routes in a dynamic topology due to water currents and movements. To cope with these problems, the use of a routing protocol is very important. In this paper we propose a routing technique that adapts to changes in the network topology, avoiding multiple retransmissions that would affect its overall performance. This protocol is energy-efficient and is implemented using a fuzzy analytical hierarchical process (FAHP) under multi-criteria decision making (MCDM) to make an intelligent routing decision based on objectives, criteria and alternatives. To select the next node on the route, several comparison matrices are used: number of hops, distances to the sink node, and number of neighbors. The results show that the proposed setup behaves similarly to other existing underwater sensor network routing schemes using fuzzy schemes such as SPRINT.This research was funded in part by the Spanish Ministry of Science and Innovation through the project “NAUTILUS: Swarms of underwater autonomous vehicles guided by artificial intelligence: its time has come” (Grant: PID2020-112502RB/AEI/10.13039/501100011033). Partial funding for open access charge: Universidad de Málag

Modelling and Design of Resilient Networks under Challenges

Communication networks, in particular the Internet, face a variety of challenges that can disrupt our daily lives resulting in the loss of human lives and significant financial costs in the worst cases. We define challenges as external events that trigger faults that eventually result in service failures. Understanding these challenges accordingly is essential for improvement of the current networks and for designing Future Internet architectures. This dissertation presents a taxonomy of challenges that can help evaluate design choices for the current and Future Internet. Graph models to analyse critical infrastructures are examined and a multilevel graph model is developed to study interdependencies between different networks. Furthermore, graph-theoretic heuristic optimisation algorithms are developed. These heuristic algorithms add links to increase the resilience of networks in the least costly manner and they are computationally less expensive than an exhaustive search algorithm. The performance of networks under random failures, targeted attacks, and correlated area-based challenges are evaluated by the challenge simulation module that we developed. The GpENI Future Internet testbed is used to conduct experiments to evaluate the performance of the heuristic algorithms developed

Development of a simulation tool for measurements and analysis of simulated and real data to identify ADLs and behavioral trends through statistics techniques and ML algorithms

openCon una popolazione di anziani in crescita, il numero di soggetti a rischio di patologia è in rapido aumento. Molti gruppi di ricerca stanno studiando soluzioni pervasive per monitorare continuamente e discretamente i soggetti fragili nelle loro case, riducendo i costi sanitari e supportando la diagnosi medica. Comportamenti anomali durante l'esecuzione di attività di vita quotidiana (ADL) o variazioni sulle tendenze comportamentali sono di grande importanza.With a growing population of elderly people, the number of subjects at risk of pathology is rapidly increasing. Many research groups are studying pervasive solutions to continuously and unobtrusively monitor fragile subjects in their homes, reducing health-care costs and supporting the medical diagnosis. Anomalous behaviors while performing activities of daily living (ADLs) or variations on behavioral trends are of great importance. To measure ADLs a significant number of parameters need to be considering affecting the measurement such as sensors and environment characteristics or sensors disposition. To face the impossibility to study in the real context the best configuration of sensors able to minimize costs and maximize accuracy, simulation tools are being developed as powerful means. This thesis presents several contributions on this topic. In the following research work, a study of a measurement chain aimed to measure ADLs and represented by PIRs sensors and ML algorithm is conducted and a simulation tool in form of Web Application has been developed to generate datasets and to simulate how the measurement chain reacts varying the configuration of the sensors. Starting from eWare project results, the simulation tool has been thought to provide support for technicians, developers and installers being able to speed up analysis and monitoring times, to allow rapid identification of changes in behavioral trends, to guarantee system performance monitoring and to study the best configuration of the sensors network for a given environment. The UNIVPM Home Care Web App offers the chance to create ad hoc datasets related to ADLs and to conduct analysis thanks to statistical algorithms applied on data. To measure ADLs, machine learning algorithms have been implemented in the tool. Five different tasks have been identified. To test the validity of the developed instrument six case studies divided into two categories have been considered. To the first category belong those studies related to: 1) discover the best configuration of the sensors keeping environmental characteristics and user behavior as constants; 2) define the most performant ML algorithms. The second category aims to proof the stability of the algorithm implemented and its collapse condition by varying user habits. Noise perturbation on data has been applied to all case studies. Results show the validity of the generated datasets. By maximizing the sensors network is it possible to minimize the ML error to 0.8%. Due to cost is a key factor in this scenario, the fourth case studied considered has shown that minimizing the configuration of the sensors it is possible to reduce drastically the cost with a more than reasonable value for the ML error around 11.8%. Results in ADLs measurement can be considered more than satisfactory.INGEGNERIA INDUSTRIALEopenPirozzi, Michel

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Recent Advances in Motion Analysis

The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as wearables, inertial measurement units, ambient sensors, and cameras or depth sensors, have been adopted on a wide scale. Furthermore, computational intelligence (CI) methods, such as artificial neural networks, have recently emerged as promising tools for the development and application of intelligent systems in motion analysis. Thus, the synergy of classic instrumentation and novel smart devices and techniques has created unique capabilities in the continuous monitoring of motor behaviors in different fields, such as clinics, sports, and ergonomics. However, real-time sensing, signal processing, human activity recognition, and characterization and interpretation of motion metrics and behaviors from sensor data still representing a challenging problem not only in laboratories but also at home and in the community. This book addresses open research issues related to the improvement of classic approaches and the development of novel technologies and techniques in the domain of motion analysis in all the various fields of application

Context Aware Computing or the Sense of Context

ITALIANO: I sistemi ubiquitous e pervasivi, speciali categorie di sistemi embedded (immersi), possono essere utilizzati per rilevare il contesto che li circonda. In particolare, i sistemi context-aware sono in grado di alterare il loro stato interno e il loro comportamento in base all’ambiente (context) che percepiscono. Per aiutare le persone nell’espletare le proprie attivitá, tali sistemi possono utilizzare le conoscenze raccolte attorno a loro. Un grande sforzo industriale e di ricerca, orientato all’innovazione dei sensori, processori, sistemi operativi, protocolli di comunicazione, e framework, offre molte tecnologie definibili abilitanti, come le reti di sensori wireless o gli Smartphone. Tuttavia, nonostante tale sforzo significativo, l’adozione di sistemi pervasivi che permettano di migliorare il monitoraggio dello sport, l’allenamento e le tecnologie assistive é ancora piuttosto limitato. Questa tesi individua due fattori determinanti per questo basso utilizzo delle tecnologie pervasive, principalmente relativi agli utenti. Da un lato il tentativo degli esperti e dei ricercatori dell’informatica di indurre l’adozione di soluzioni informatiche, trascurando parzialmente l’interazione con gli utenti finali, dall’altro lato una scarsa attenzione all’interazione tra uomo e computer. Il primo fattore puó essere tradotto nella mancanza di attenzione a ció che é rilevante nel contesto dei bisogni (speciali) dell’utente. Il secondo é rappresentato dall’utilizzo diffuso di interfacce grafiche di presentazione delle informazioni, che richiede un elevato livello di sforzo cognitivo da parte degli utenti. Mentre lo studio della letteratura puó fornire conoscenze sul contesto dell’utente, solo il contatto diretto con lui arricchisce la conoscenza di consapevolezza, fornendo una precisa identificazione dei fattori che sono piú rilevanti per il destinatario dell’applicazione. Per applicare con successo le tecnologie pervasive al campo dello sport e delle tecnologie assistive, l’identificazione dei fattori rilevanti é una premessa necessaria, Tale processo di identificazione rappresenta l’approccio metodologico principale utilizzato per questa tesi. Nella tesi si analizzano diversi sport (canottaggio, nuoto, corsa ) e una disabilitá (la cecitá), per mostrare come la metodologia di investigazione e di progettazione proposta venga messa in pratica. Infatti i fattori rilevanti sono stati identificati grazie alla stretta collaborazione con gli utenti e gli esperti nei rispettivi campi. Si descrive il processo di identificazione, insieme alle soluzioni elaborate su misura per il particolare campo d’uso. L’uso della sonificazione, cioé la trasmissione di informazioni attraverso il suono, si propone di affrontare il secondo problema presentato, riguardante le interfacce utente. L’uso della sonificazione puó facilitare la fruizione in tempo reale delle informazioni sulle prestazioni di attivitá sportive, e puó contribuire ad alleviare parzialmente la disabilitá degli utenti non vedenti. Nel canottaggio, si é identificato nel livello di sincronia del team uno dei fattori rilevanti per una propulsione efficace dell’imbarcazione. Il problema di rilevare il livello di sincronia viene analizzato mediante una rete di accelerometri wireless, proponendo due diverse soluzioni. La prima soluzione é basata sull’indice di correlazione di Pearson e la seconda su un approccio emergente chiamato stigmergia. Entrambi gli approcci sono stati testati con successo in laboratorio e sul campo. Inoltre sono state sviluppate due applicazioni, per smartphone e PC, per fornire la telemetria e la sonificazione del moto di una barca a remi. Nel campo del nuoto é stata condotta una ricerca in letteratura riguardo la convinzione diffusa di considerare la cinematica come il fattore rilevante della propulsione efficace dei nuotatori. Questa indagine ha richiamato l’attenzione sull’importanza di studiare il cosiddetto feel-for-water (sensazione-dell’-acqua) percepito dai nuotatori d’alto livello. É stato progettato un innovativo sistema, per rilevare e comunicare gli effetti fluidodinamici causati dallo spostamento delle masse d’acqua intorno alle mani dei nuotatori. Il sistema é in grado di trasformare la pressione dell’acqua, misurata con sonde Piezo intorno alle mani, in un bio-feedback auditivo, pensato per i nuotatori e gli allenatori, come base per un nuovo modo di comunicare la sensazione-dell’acqua. Il sistema é stato testato con successo nel campo e ha dimostrato di fornire informazioni in tempo reale per il nuotatore e il formatore. Nello sport della corsa sono stati individuati due parametri rilevanti: il tempo di volo e di contatto dei piedi. É stato progettato un sistema innovativo per ottenere questi parametri attraverso un unico accelerometro montato sul tronco del corridore ed é stato implementato su uno smartphone. Per ottenere il risultato voluto é stato necessario progettare e realizzare un sistema per riallineare virtualmente gli assi dell’accelerometro e per estrarre il tempo di volo e di contatto dal segnale dell’accelerometro riallineato. L’applicazione per smartphone completa é stata testata con successo sul campo, confrontando i valori con quelli di attrezzature specializzate, dimostrando la sua idoneitá come ausilio pervasivo all’allenamento di corridori. Per esplorare le possibilitá della sonificazione usata come una base per tecnologia assistiva, abbiamo iniziato una collaborazione con un gruppo di ricerca presso l’Universitá di Scienze Applicate, Ginevra, in Svizzera. Tale collaborazione si é concentrata su un progetto chiamato SeeColOr (See Color with an Orchestra - vedere i colori con un’orchestra). In particolare, abbiamo avuto l’opportunitá di implementare il sistema SeeColOr su smartphone, al fine di consentire agli utenti non vedenti di utilizzare tale tecnologia su dispositivi leggeri e a basso costo. Inoltre, la tesi esplora alcune questioni relative al campo del rilevamento ambientale in ambienti estremi, come i ghiacciai, utilizzando la tecnologia delle Wireless Sensor Networks. Considerando che la tecnologia é simile a quella usata in altri contesti presentati, le considerazioni possono facilmente essere riutilizzate. Si sottolinea infatti che i problemi principali sono legati alla elevata difficoltá e scarsa affidabilitá di questa tecnologia innovativa rispetto alle altre soluzioni disponibili in commercio , definite legacy, basate solitamente su dispositivi piú grandi e costosi, chiamati datalogger. La tesi presenta i problemi esposti e le soluzioni proposte per mostrare l’applicazione dell’approccio progettuale cercato e definito durante lo sviluppo delle attività sperimentali e la ricerca che le ha implementate. ---------------------------------------- ENGLISH: Ubiquitous and pervasive systems, special categories of embedded systems, can be used to sense the context in their surrounding. In particular, context-aware systems are able to alter their internal state and their behaviour based on the context they perceive. To help people in better performing their activities, such systems must use the knowledge gathered about the context. A big research and industrial effort, geared towards the innovation of sensors, processors, operating systems, communication protocols, and frameworks, provides many "enabling" technologies, such as Wireless Sensor Networks or Smartphones. However, despite that significant effort, the adoption of pervasive systems to enhance sports monitoring, training and assistive technologies is still rather small. This thesis identifies two main issues concerning this low usage of pervasive technologies, both mainly related to users. On one side the attempt of computer science experts and researchers to induce the adoption of information technology based solutions, partially neglecting interaction with end users; on the other side a scarce attention to the interaction between humans and computers. The first can be translated into the lack of attention at what is relevant in the context of the user’s (special) needs. The second is represented by the widespread usage of graphical user interfaces to present information, requiring a high level of cognitive effort. While literature studies can provide knowledge about the user’s context, only direct contact with users enriches knowledge with awareness, providing a precise identification of the factors that are more relevant to the user. To successfully apply pervasive technologies to the field of sports engineering and assistive technology, the identification of relevant factors is an obliged premise, and represents the main methodological approach used throughout this thesis. This thesis analyses different sports (rowing, swimming, running) and a disability (blindness), to show how the proposed design methodology is put in practice. Relevant factors were identified thanks to the tight collaboration with users and experts in the respective fields. The process of identification is described, together with the proposed application tailored for the special field. The use of sonification, i.e. conveying information as sound, is proposed to leverage the second presented issue, that regards the user interfaces. The usage of sonification can ease the exploitation of information about performance in real-time for sport activities and can help to partially leverage the disability of blind users. In rowing, the synchrony level of the team was identified as one of the relevant factors for effective propulsion. The problem of detecting the synchrony level is analysed by means of a network of wireless accelerometers, proposing two different solutions. The first solution is based on Pearson’s correlation index and the second on an emergent approach called stigmergy. Both approaches were successfully tested in laboratory and in the field. Moreover two applications, for smartphones and PCs, were developed to provide telemetry and sonification of a rowing boat’s motion. In the field of swimming, an investigation about the widespread belief considering kinematics as the relevant factor of effective propulsion of swimmers drew attention to the importance of studying the so called "feel-for-water" experienced by elite swimmers. An innovative system was designed to sense and communicate fluid-dynamic effects caused by moving water masses around swimmers hands. The system is able to transform water pressure, measured with Piezo-probes, around hands into an auditive biofeedback, to be used by swimmers and trainers, as the base for a new way of communication about the "feel-for-water". The system was successfully tested in the field and proved to provide real-time information for the swimmer and the trainer. In running sports two relevant parameters are time of flight and contact of feet. An innovative system was designed to obtain these parameters using a single trunk mounted accelerometer and was implemented on a smartphone. To achieve the intended result it was necessary to design and implement a system to virtually realign the axes of the accelerometer and to extract time of flight and time of contact phases from the realigned accelerometer signal. The complete smartphone application was successfully tested in the field with specialized equipment, proving its suitability in enhancing training of runners with a pervasive system. To explore possibilities of sonification applied as an assistive technology, we started a collaboration with research group from University of Applied Science, Geneva, Switzerland, focused on a project called SeeColOr (See Color with an Orchestra). In particular we had the opportunity to implement the SeeColOr system on smartphones, in order to enable blind users to use that technology on low cost and lightweight devices. Moreover, the thesis exposes some issues related to a field, environmental sensing in extreme environments, like glaciers, using the innovative Wireless Sensor Networks technology. Considering that the technology is similar to the one used in other presented contexts, learned lessons can easily be reused. It is emphasized that the main problems are related to the high difficulty and low reliability of that innovative technology with respect to other "legacy" commercially available solutions, based on expensive and bigger devices, called dataloggers. The thesis presents the exposed problems and proposed solutions to show the application of the design approach strived during the development and research

Performance Evaluation of Network Anomaly Detection Systems

Nowadays, there is a huge and growing concern about security in information and communication technology (ICT) among the scientific community because any attack or anomaly in the network can greatly affect many domains such as national security, private data storage, social welfare, economic issues, and so on. Therefore, the anomaly detection domain is a broad research area, and many different techniques and approaches for this purpose have emerged through the years. Attacks, problems, and internal failures when not detected early may badly harm an entire Network system. Thus, this thesis presents an autonomous profile-based anomaly detection system based on the statistical method Principal Component Analysis (PCADS-AD). This approach creates a network profile called Digital Signature of Network Segment using Flow Analysis (DSNSF) that denotes the predicted normal behavior of a network traffic activity through historical data analysis. That digital signature is used as a threshold for volume anomaly detection to detect disparities in the normal traffic trend. The proposed system uses seven traffic flow attributes: Bits, Packets and Number of Flows to detect problems, and Source and Destination IP addresses and Ports, to provides the network administrator necessary information to solve them. Via evaluation techniques, addition of a different anomaly detection approach, and comparisons to other methods performed in this thesis using real network traffic data, results showed good traffic prediction by the DSNSF and encouraging false alarm generation and detection accuracy on the detection schema. The observed results seek to contribute to the advance of the state of the art in methods and strategies for anomaly detection that aim to surpass some challenges that emerge from the constant growth in complexity, speed and size of today’s large scale networks, also providing high-value results for a better detection in real time.Atualmente, existe uma enorme e crescente preocupação com segurança em tecnologia da informação e comunicação (TIC) entre a comunidade científica. Isto porque qualquer ataque ou anomalia na rede pode afetar a qualidade, interoperabilidade, disponibilidade, e integridade em muitos domínios, como segurança nacional, armazenamento de dados privados, bem-estar social, questões econômicas, e assim por diante. Portanto, a deteção de anomalias é uma ampla área de pesquisa, e muitas técnicas e abordagens diferentes para esse propósito surgiram ao longo dos anos. Ataques, problemas e falhas internas quando não detetados precocemente podem prejudicar gravemente todo um sistema de rede. Assim, esta Tese apresenta um sistema autônomo de deteção de anomalias baseado em perfil utilizando o método estatístico Análise de Componentes Principais (PCADS-AD). Essa abordagem cria um perfil de rede chamado Assinatura Digital do Segmento de Rede usando Análise de Fluxos (DSNSF) que denota o comportamento normal previsto de uma atividade de tráfego de rede por meio da análise de dados históricos. Essa assinatura digital é utilizada como um limiar para deteção de anomalia de volume e identificar disparidades na tendência de tráfego normal. O sistema proposto utiliza sete atributos de fluxo de tráfego: bits, pacotes e número de fluxos para detetar problemas, além de endereços IP e portas de origem e destino para fornecer ao administrador de rede as informações necessárias para resolvê-los. Por meio da utilização de métricas de avaliação, do acrescimento de uma abordagem de deteção distinta da proposta principal e comparações com outros métodos realizados nesta tese usando dados reais de tráfego de rede, os resultados mostraram boas previsões de tráfego pelo DSNSF e resultados encorajadores quanto a geração de alarmes falsos e precisão de deteção. Com os resultados observados nesta tese, este trabalho de doutoramento busca contribuir para o avanço do estado da arte em métodos e estratégias de deteção de anomalias, visando superar alguns desafios que emergem do constante crescimento em complexidade, velocidade e tamanho das redes de grande porte da atualidade, proporcionando também alta performance. Ainda, a baixa complexidade e agilidade do sistema proposto contribuem para que possa ser aplicado a deteção em tempo real

Formulation, implementation considerations, and first performance evaluation of algorithmic solutions - D4.1

Deliverable D4.1 del projecte Europeu OneFIT (ICT-2009-257385)This deliverable contains a first version of the algorithmic solutions for enabling opportunistic networks. The presented algorithms cover the full range of identified management tasks: suitability, creation, QoS control, reconfiguration and forced terminations. Preliminary evaluations complement the proposed algorithms. Implementation considerations towards the practicality of the considered algorithms are also included.Preprin