Robust, Resilient Networked Communication in Challenged Environments

In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication

An Energy-Efficient Clustering Routing Protocol for WSN based on MRHC

currently the world is adopting Internet of Things (IoT) as the future technology and the interest IoT development is increasing. As it’s expected to be the leading technology by 2022 according to Gartner. WSN is the main technology component of the IoT since it rely on sensing and collecting data in a specific filed of interest. As the WSN main issue is the network life time due the limitation in sensors resource. Therefore, such lifetimeconstrained devices require enchantment on the existing routing protocols to prolong network life time as long as possible. In our paper we propose enhancement in the well know WSN routing protocol LEACH by proposing a new Energy aware algorithm in communication within cluster, hence reduce power consumption in communication process

Sensitive parameter analysis for solar irradiance short-term forecasting: application to LoRa-based monitoring technology

Due to the relevant penetration of solar PV power plants, an accurate power generation forecasting of these installations is crucial to provide both reliability and stability of current grids. At the same time, PV monitoring requirements are more and more demanded by different agents to provide reliable information regarding performances, efficiencies, and possible predictive maintenance tasks. Under this framework, this paper proposes a methodology to evaluate different LoRa-based PV monitoring architectures and node layouts in terms of short-term solar power generation forecasting. A random forest model is proposed as forecasting method, simplifying the forecasting problem especially when the time series exhibits heteroscedasticity, nonstationarity, and multiple seasonal cycles. This approach provides a sensitive analysis of LoRa parameters in terms of node layout, loss of data, spreading factor and short time intervals to evaluate their influence on PV forecasting accuracy. A case example located in the southeast of Spain is included in the paper to evaluate the proposed analysis. This methodology is applicable to other locations, as well as different LoRa configurations, parameters, and networks structures; providing detailed analysis regarding PV monitoring performances and short-term PV generation forecasting discrepancies.This research was funded by the Fondo Europeo de Desarrollo Regional/Ministerio de Ciencia e Innovación–Agencia Estatal de Investigación (FEDER/MICINN-AEI), project RTI2018–099139–B–C21

A network mobility management architecture for a heteregeneous network environment

Network mobility management enables mobility of personal area networks and vehicular networks across heterogeneous access networks using a Mobile Router. This dissertation presents a network mobility management architecture for minimizing the impact of handoffs on the communications of nodes in the mobile network. The architecture addresses mobility in legacy networks without infrastructure support, but can also exploit infrastructure support for improved handoff performance. Further, the proposed architecture increases the efficiency of communications of nodes in the mobile network with counter parts in the fixed network through the use of caching and route optimization. The performance and costs of the proposed architecture are evaluated through empirical and numerical analysis. The analysis shows the feasibility of the architecture in the networks of today and in those of the near future.Verkkojen liikkuuvudenhallinta mahdollistaa henkilökohtaisten ja ajoneuvoihin asennettujen verkkojen liikkuvuuden heterogeenisessä verkkoympäristössä käyttäen liikkuvaa reititintä. Tämä väitöskirja esittää uuden arkkitehtuurin verkkojen liikkuvuudenhallintaan, joka minimoi verkonvaihdon vaikutuksen päätelaitteiden yhteyksiin. Vanhoissa verkoissa, joiden infrastruktuuri ei tue verkkojen liikkuvuutta, verkonvaihdos täytyy hallita liikkuvassa reitittimessa. Standardoitu verkkojen liikkuvuudenhallintaprotokolla NEMO mahdollistaa tämän käyttäen ankkurisolmua kiinteässä verkossa pakettien toimittamiseen päätelaitteiden kommunikaatiokumppaneilta liikkuvalle reitittimelle. NEMO:ssa verkonvaihdos aiheuttaa käynnissä olevien yhteyksien keskeytymisen yli sekunnin mittaiseksi ajaksi, aiheuttaen merkittävää häiriötä viestintäsovelluksille. Esitetyssä arkkitehtuurissa verkonvaihdon vaikutus minimoidaan varustamalla liikkuva reititin kahdella radiolla. Käyttäen kahta radiota liikkuva reititin pystyy suorittamaan verkonvaihdon keskeyttämättä päätelaitteiden yhteyksiä, mikäli verkonvaihtoon on riittävästi aikaa. Käytettävissa oleva aika riippuu liikkuvan reitittimen nopeudesta ja radioverkon rakenteesta. Arkkitehtuuri osaa myös hyödyntää infrastruktuurin tukea saumattomaan verkonvaihtoon. Verkkoinfrastruktuurin tuki nopeuttaa verkonvaihdosprosessia, kasvattaenmaksimaalista verkonvaihdos tahtia. Tällöin liikkuva reitin voi käyttää lyhyen kantaman radioverkkoja, joiden solun säde on yli 80m, ajonopeuksilla 90m/s asti ilman, että verkonvaihdos keskeyttää päätelaitteiden yhteyksiä. Lisäksi ehdotettu arkkitehtuuri tehostaa kommunikaatiota käyttäen cache-palvelimia liikkuvassa ja kiinteässä verkossa ja optimoitua reititystä liikkuvien päätelaitteiden ja kiinteässä verkossa olevien kommunikaatiosolmujen välillä. Cache-palvelinarkkitehtuuri hyödyntää vapaita radioresursseja liikkuvan verkon cache-palvelimen välimuistin päivittämiseen. Heterogeenisessä verkkoympäristossä cache-palvelimen päivitys suoritetaan lyhyen kantaman laajakaistaisia radioverkkoja käyttäen. Liikkuvan reitittimen siirtyessä laajakaistaisen radioverkon peitealueen ulkopuolelle päätelaitteille palvellaan sisältöä, kuten www sivuja tai videota cache-palvelimelta, säästäen laajemman kantaman radioverkon rajoitetumpia resursseja. Arkkitehtuurissa käytetään optimoitua reititystä päätelaitteiden ja niiden kommunikaatiokumppaneiden välillä. Optimoitu reititysmekanismi vähentää liikkuvuudenhallintaan käytettyjen protokollien langattoman verkon resurssien kulutusta. Lisäksi optimoitu reititysmekanismi tehostaa pakettien reititystä käyttäen suorinta reittiä kommunikaatiosolmujen välillä. Esitetyn arkkitehtuurin suorituskyky arvioidaan empiirisen ja numeerisen analyysin avulla. Analyysi arvioi arkkitehtuurin suorituskykyä ja vertaa sitä aikaisemmin ehdotettuihin ratkaisuihin ja osoittaa arkkitehtuurin soveltuvan nykyisiin ja lähitulevaisuuden langattomiin verkkoihin.reviewe

Detecting Impersonation Attacks in a Static WSN

The current state of security found in the IoT domain is highly flawed, a major problem being that the cryptographic keys used for authentication can be easily extracted and thus enable a myriad of impersonation attacks. In this MSc thesis a study is done of an authentication mechanism called device fingerprinting. It is a mechanism which can derive the identity of a device without relying on device identity credentials and thus detect credential-based impersonation attacks. A proof of concept has been produced to showcase how a fingerprinting system can be designed to function in a resource constrained IoT environment. A novel approach has been taken where several fingerprinting techniques have been combined through machine learning to improve the system’s ability to deduce the identity of a device. The proof of concept yields high performant results, indicating that fingerprinting techniques are a viable approach to achieve security in an IoT system

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

Cognitive Radio and TV White Space (TVWS) Applications

As more user applications emerge for wireless devices, the corresponding amount of traffic is rapidly expanding, with the corollary that ever-greater spectrum capacity is required. Service providers are experiencing deployment blockages due to insufficient bandwidth being available to accommodate such devices. TV White Space (TVWS) represents an opportunity to supplement existing licensed spectrum by exploiting unlicensed resources. TVWS spectrum has materialised from the unused TV channels in the switchover from analogue to digital platforms. The main obstacles to TVWS adoption are reliable detection of primary users (PU) i.e., TV operators and consumers, allied with specifically, the hidden node problem. This chapter presents a new Generalised Enhanced Detection Algorithm (GEDA) that exploits the unique way Digital Terrestrial TV (DTT) channels are deployed in different geographical areas. GEDA effectively transforms an energy detector into a feature sensor to achieve significant improvements in detection probability of a DTT PU. Furthermore, by framing a novel margin strategy utilising a keep out contour, the hidden node issue is resolved, and a viable secondary user sensing solution formulated. Experimental results for a cognitive radio TVWS model have formalised both the bandwidth and throughput gains secured by TVWS users with this new paradigm

Development of a WiFi and RFID based indoor location and mobility tracking system

Ubiquitous positioning and people mobility tracking has become one of the critical parts of our daily life. As a core element of the Location Based Services (LBS), the ubiquitous positioning capability necessitates seamless positioning across both indoor and outdoor environments. Nowadays, tracking outdoor with a relatively high accuracy and reliability can be achieved using matured technologies such as Global Navigation Satellite Systems (GNSS). However, it is still challenging for tracking in indoor environments such as airports, shopping malls and museums. The demand for indoor tracking has driven the fast development of indoor positioning and tracking technologies, especially Wi-Fi, RFID and smartphone etc. All these technologies have significantly enhanced the convenience of people’s daily life and the competitiveness of business firms. With the rapidly increased ubiquity of Wi-Fi enabled mobile phones and tablets, developing a robust location and mobility tracking system utilising such technologies will have a great potential for industry innovation and applications. This research is part of an Australian Research Council (ARC) project that involves two universities and one industry partner who is a large global shopping mall management company located in Australia. The project aims to develop a smart system for robust modelling and analysing the shopping behaviours of customers so that value-added services can be effectively provided. A number of field tests have been conducted and a large amount of data has been acquired both in the shopping mall of interest and the RMIT Indoor Positioning Laboratory. A large cohort of real users in the shopping mall were recorded where only one Wi-Fi access point (AP) connection at a time for each mobile device user was provided for our research. This makes most of the conventional tracking and positioning methods inapplicable. To overcome this constraint, a new hybrid system for positioning and mobility tracking — called single AP-connection location tracking system (SCLTS) was developed, which utilised Wi-Fi, RFID and mobile device technologies and took advantage of both the cell of origin (CoO) and fingerprinting positioning methods. Three new algorithms for Wi-Fi based indoor positioning were developed during this research. They are the common handover point determination (CHOPD) algorithm for determining the boundary of the cell; the algorithm for positioning with the case of same-line-dual-connection (SLDC) in a long narrow space (e.g., a long corridor) and the algorithm for positioning with the case of perpendicular-dual-connection of APs in a T-shape corridor for improving the positioning accuracy. The architecture of the SCLTS system was also developed as part of the implementation of the SCLTS system. Various experiments were conducted in a simulated large shopping-mall-like environment (i.e., the RMIT Indoor Positioning Lab) and the results showed that the performance of the SCLTS developed was very promising and the original goal of the project has been achieved. In addition, the two most popular indoor positioning methods — trilateration and fingerprinting were also optimised and implemented in a real industrial product and promising results have been achieved

Spectrum Sensing in Cognitive Radio Using CNN-RNN and Transfer Learning

Cognitive radio has been proposed to improve spectrum utilization in wireless communication. Spectrum sensing is an essential component of cognitive radio. The traditional methods of spectrum sensing are based on feature extraction of a received signal at a given point. The development in artificial intelligence and deep learning have given an opportunity to improve the accuracy of spectrum sensing by using cooperative spectrum sensing and analyzing the radio scene. This research proposed a hybrid model of convolution and recurrent neural network for spectrum sensing. The research further enhances the accuracy of sensing for low SNR signals through transfer learning. The results of modelling show improvement in spectrum sensing using CNN-RNN compared to other models studied in this field. The complexity of an algorithm is analyzed to show an improvement in the performance of the algorithm.publishedVersio