Secure Geo-location Techniques using Trusted Hyper-visor

Για πολλούς, η γεωγραφική θέση είναι μια απλή διαδικασία όπου με τη χρήση του GPS ένα άτομο μπορεί να εντοπιστεί όπου και όποτε ζητείται. Ωστόσο, ακόμη και αν η χρήση του GPS για γεωγραφική τοποθέτηση είναι ο πιο συνηθισμένος τρόπος και ταυτόχρονα ακριβής ως σύστημα, αποτελεί μια τεράστια κατανάλωση ενέργειας για να επιτευχθεί αυτή η διαδικασία και υστερεί σε μηχανισμούς και τεχνικές ασφαλείας. Σκοπός αυτής της εργασίας είναι να παρουσιάσουμε μια άλλη όψη για το πώς μπορούμε να εντοπίσουμε μια άγνωστη θέση ενός κόμβου σε ένα σύστημα και πώς θα μπορούσε να δημιουργηθεί ένα ασφαλές περιβάλλον για αυτόν τον κόμβο. Βασική μας ιδέα ήταν η δημιουργία ενός μηχανισμού όπου θα μπορούσαμε να δημιουργήσουμε ένα τρισδιάστατο πεδίο στο οποίο θα μπορούσε να εντοπιστεί άγνωστος κόμβος και στη συνέχεια θα δημιουργηθεί ένα ασφαλές περιβάλλον για τον νέο κόμβο. Μετά από μια έρευνα σε δημοσιεύσεις σχετικά με τρισδιάστατους μηχανισμούς και τεχνικές γεω-εντοπισμού, παράλληλα με την έννοια των hypervisors για τη δημιουργία ασφαλούς περιβάλλοντος με την αξιοποίηση της κρυπτογραφίας, καταλήξαμε στο συμπέρασμα της δημιουργίας ενός πλαισίου που θα ικανοποιούσε αυτά απαιτήσεις. Δημιουργήσαμε ένα τρισδιάστατο πεδίο τεσσάρων σταθμών κόμβων, όπου χρησιμοποιήσαμε δύο αλγορίθμους εντοπισμού, χωρίς GPS, για τον εντοπισμό της θέση ενός πέμπτου άγνωστου κόμβου παράλληλα με έναν hypervisor για τη δημιουργία περιβάλλοντος εμπιστοσύνης. Χρησιμοποιήσαμε ένα TPM για τη δημιουργία κρυπτογραφικών μηχανισμών και κλειδιών ασφαλείας. Σε αυτή την εργασία δημιουργήσαμε μια προσομοίωση όπου συγκρίνουμε την απόδοση αυτών των δύο αλγορίθμων γεωγραφικής τοποθέτησης από την άποψη της ταχύτητας και της ακρίβειας του υπολογισμού, παράλληλα με την απόδοση των μηχανισμών ασφαλείας του hypervisor και την ικανότητά του για ασφάλιση ακεραιότητας δεδομένων. Εκτός από τα συστατικά του προτεινόμενου μηχανισμού, παρουσιάζουμε και άλλες πληροφορίες που βρήκαμε σε σχετικά έγγραφα, όπως μια ποικιλία από hypervisors και μια ποικιλία τεχνικών εντοπισμού, για περισσότερες πληροφορίες για μελλοντικές εργασίες παράλληλα με τα βήματα υλοποίησης και εκτέλεσης.For many, geo-location is a simple process where with the utilization of GPS a person can be located wherever and whenever is requested. However, even if the utilization of GPS for geolocation is the most common way and accurate as a system, it is a huge consumption of energy in order to achieve this process and it lucks on safety mechanisms and techniques. The purpose of this paper is to present another view of how we could locate an unknown node position in a system and how a safe environment could be created for this node. Our main idea was about the creation of a framework where we could create a three-dimensional field in which an unknown node could be located and afterwards a safe environment would be created for the new node. After a research on papers relevant with three-dimensional geo-localization mechanisms and techniques, alongside with the concept of hypervisors for the creation of safe environment with the utilization of cryptography, we came to the conclusion of the creation of a framework which would satisfy those requirements. We created a 3-Dimentional field of four base nodes stations, where we utilized two localization GPS-free algorithms for the location of a fifth unknown node alongside with a hypervisor for the trust environment creation. We utilized a TPM for the cryptography mechanisms and safety keys creation. In this paper we created a simulation where we compare the performance of those two geolocation algorithms in terms of accuracy and computation speed and accuracy, alongside with the hypervisor’s security mechanisms performance and its ability for data integrity insurance. Except our proposed framework components, we present also further information that we found in relevant papers, such as a variety of hypervisors and a variety of localization techniques, for more information for future work alongside with implementation steps and guidanc

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Modeling and Implementation of Wireless Sensor Networks for Logistics Applications

Logistics has experienced a long time of developments and improvements based on the advanced vehicle technologies, transportation systems, traffic network extension and logistics processes. In the last decades, the complexity has increased significantly and this has created complex logistics networks over multiple continents. Because of the close cooperation, these logistics networks are highly dependent on each other in sharing and processing the logistics information. Every customer has many suppliers and vice versa. The conventional centralized control continues but reaches some limitations such as the different distribution of suppliers, the complexity and flexibility of processing orders or the dynamics of the logistic objects. In order to overcome these disadvantages, the paradigm of autonomous logistics is proposed and promises a better technical solution for current logistics systems. In autonomous logistics, the decision making is shifted toward the logistic objects which are defined as material items (e.g., vehicles, containers) or immaterial items (e.g., customer orders) of a networked logistics system. These objects have the ability to interact with each other and make decisions according to their own objectives. In the technical aspect, with the rapid development of innovative sensor technology, namely Wireless Sensor Networks (WSNs), each element in the network can self-organize and interact with other elements for information transmission. The attachment of an electronic sensor element into a logistic object will create an autonomous environment in both the communication and the logistic domain. With this idea, the requirements of logistics can be fulfilled; for example, the monitoring data can be precise, comprehensive and timely. In addition, the goods flow management can be transferred to the information logistic object management, which is easier by the help of information technologies. However, in order to transmit information between these logistic objects, one requirement is that a routing protocol is necessary. The Opportunistic relative Distance-Enabled Uni-cast Routing (ODEUR ) protocol which is proposed and investigated in this thesis shows that it can be used in autonomous environments like autonomous logistics. Moreover, the support of mobility, multiple sinks and auto-connection in this protocol enhances the dynamics of logistic objects. With a general model which covers a range from low-level issues to high-level protocols, many services such as real time monitoring of environmental conditions, context-aware applications and localization make the logistic objects (embedded with sensor equipment) more advanced in information communication and data processing. The distributed management service in each sensor node allows the flexible configuration of logistic items at any time during the transportation. All of these integrated features introduce a new technical solution for smart logistic items and intelligent transportation systems. In parallel, a management system, WSN data Collection and Management System (WiSeCoMaSys), is designed to interact with the deployed Wireless Sensor Networks. This tool allows the user to easily manipulate the sensor networks remotely. With its rich set of features such as real time data monitoring, data analysis and visualization, per-node management, and alerts, this tool helps both developers and users in the design and deployment of a sensor network. In addition, an analytical model is developed for comparison with the results from simulations and experiments. Focusing on the use of probability theory to model the network links, this model considers several important factors such as packet reception rate and network traffic which are used in the simulation and experiment parts. Moreover, the comparison between simulation, experiment and analytical results is also carried out to estimate the accuracy of the design and make several improvements of the simulation accuracy. Finally, all of the above parts are integrated in one unique system. This system is verified by both simulations in logistic scenarios (e.g., harbors, warehouses and containers) and experiments. The results show that the proposed model and protocol have a good packet delivery rate, little memory requirements and low delay. Accordingly, this system design is practical and applicable in logistics

Cooperative Vehicle Tracking in Large Environments

Vehicle position tracking and prediction over large areas is of significant importance in many industrial applications, such as mining operations. In a small area, this can be easily achieved by providing vehicles with a constant communication link to a control centre and having the vehicles broadcast their position. The problem changes dramatically when vehicles operate within a large environment of potentially hundreds of square kilometres and in difficult terrain. This thesis presents algorithms for cooperative tracking of vehicles based on a vehicle motion model that incorporates the properties of the working area, and information collected by infrastructure collection points and other mobile agents. The probabilistic motion prediction approach provides long-term estimates of vehicle positions using motion profiles built for the particular environment and considering the vehicle stopping probability. A limited number of data collection points distributed around the field are used to update the position estimates, with negative information also used to improve the estimation. The thesis introduces the concept of observation harvesting, a process in which peer-to-peer communication between vehicles allows egocentric position updates and inter-vehicle measurements to be relayed among vehicles and finally conveyed to the collection points for an improved position estimate. It uses a store-and-synchronise concept to deal with intermittent communication and aims to disseminate data in an opportunistic manner. A nonparametric filtering algorithm for cooperative tracking is proposed to incorporate the information harvested, including the negative, relative, and time delayed observations. An important contribution of this thesis is to enable the optimisation of fleet scheduling when full coverage networks are not available or feasible. The proposed approaches were validated with comprehensive experimental results using data collected from a large-scale mining operation

Cooperative Vehicle Tracking in Large Environments

Vehicle position tracking and prediction over large areas is of significant importance in many industrial applications, such as mining operations. In a small area, this can be easily achieved by providing vehicles with a constant communication link to a control centre and having the vehicles broadcast their position. The problem changes dramatically when vehicles operate within a large environment of potentially hundreds of square kilometres and in difficult terrain. This thesis presents algorithms for cooperative tracking of vehicles based on a vehicle motion model that incorporates the properties of the working area, and information collected by infrastructure collection points and other mobile agents. The probabilistic motion prediction approach provides long-term estimates of vehicle positions using motion profiles built for the particular environment and considering the vehicle stopping probability. A limited number of data collection points distributed around the field are used to update the position estimates, with negative information also used to improve the estimation. The thesis introduces the concept of observation harvesting, a process in which peer-to-peer communication between vehicles allows egocentric position updates and inter-vehicle measurements to be relayed among vehicles and finally conveyed to the collection points for an improved position estimate. It uses a store-and-synchronise concept to deal with intermittent communication and aims to disseminate data in an opportunistic manner. A nonparametric filtering algorithm for cooperative tracking is proposed to incorporate the information harvested, including the negative, relative, and time delayed observations. An important contribution of this thesis is to enable the optimisation of fleet scheduling when full coverage networks are not available or feasible. The proposed approaches were validated with comprehensive experimental results using data collected from a large-scale mining operation

Control for Localization and Visibility Maintenance of an Independent Agent using Robotic Teams

Given a non-cooperative agent, we seek to formulate a control strategy to enable a team of robots to localize and track the agent in a complex but known environment while maintaining a continuously optimized line-of-sight communication chain to a fixed base station. We focus on two aspects of the problem. First, we investigate the estimation of the agent\u27s location by using nonlinear sensing modalities, in particular that of range-only sensing, and formulate a control strategy based on improving this estimation using one or more robots working to independently gather information. Second, we develop methods to plan and sequence robot deployments that will establish and maintain line-of-sight chains for communication between the independent agent and the fixed base station using a minimum number of robots. These methods will lead to feedback control laws that can realize this plan and ensure proper navigation and collision avoidance

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Advanced Wireless Localisation Methods Dealing with Incomplete Measurements

Positioning techniques have become an essential part of modern engineering, and the improvement in computing devices brings great potential for more advanced and complicated algorithms. This thesis first studies the existing radio signal based positioning techniques and then presents three developed methods in the sense of dealing with incomplete data. Firstly, on the basis of received signal strength (RSS) location fingerprinting techniques, the Kriging interpolation methods are applied to generate complete fingerprint databases of denser reference locations from sparse or incomplete data sets, as a solution of reducing the workload and cost of offline data collection. Secondly, with incomplete knowledge of shadowing correlation, a new approach of Bayesian inference on RSS based multiple target localisation is proposed taking advantage of the inverse Wishart conjugate prior. The MCMC method (Metropolis-within-Gibbs) and the maximum a posterior (MAP) / maximum likelihood (ML) method are then considered to produce target location estimates. Thirdly, a new information fusion approach is developed for the time difference of arrival (TDOF) and frequency difference of arrival (FDOA) based dual-satellite geolocation system, as a solution to the unknown time and frequency offsets. All proposed methods are studied and validated through simulations. Result analyses and future work directions are discussed

A multi-hypothesis approach for range-only simultaneous localization and mapping with aerial robots

Los sistemas de Range-only SLAM (o RO-SLAM) tienen como objetivo la construcción de un mapa formado por la posición de un conjunto de sensores de distancia y la localización simultánea del robot con respecto a dicho mapa, utilizando únicamente para ello medidas de distancia. Los sensores de distancia son dispositivos capaces de medir la distancia relativa entre cada par de dispositivos. Estos sensores son especialmente interesantes para su applicación a vehículos aéreos debido a su reducido tamaño y peso. Además, estos dispositivos son capaces de operar en interiores o zonas con carencia de señal GPS y no requieren de una línea de visión directa entre cada par de dispositivos a diferencia de otros sensores como cámaras o sensores laser, permitiendo así obtener una lectura de datos continuada sin oclusiones. Sin embargo, estos sensores presentan un modelo de observación no lineal con una deficiencia de rango debido a la carencia de información de orientación relativa entre cada par de sensores. Además, cuando se incrementa la dimensionalidad del problema de 2D a 3D para su aplicación a vehículos aéreos, el número de variables ocultas del modelo aumenta haciendo el problema más costoso computacionalmente especialmente ante implementaciones multi-hipótesis. Esta tesis estudia y propone diferentes métodos que permitan la aplicación eficiente de estos sistemas RO-SLAM con vehículos terrestres o aéreos en entornos reales. Para ello se estudia la escalabilidad del sistema en relación al número de variables ocultas y el número de dispositivos a posicionar en el mapa. A diferencia de otros métodos descritos en la literatura de RO-SLAM, los algoritmos propuestos en esta tesis tienen en cuenta las correlaciones existentes entre cada par de dispositivos especialmente para la integración de medidas estÃa˛ticas entre pares de sensores del mapa. Además, esta tesis estudia el ruido y las medidas espúreas que puedan generar los sensores de distancia para mejorar la robustez de los algoritmos propuestos con técnicas de detección y filtración. También se proponen métodos de integración de medidas de otros sensores como cámaras, altímetros o GPS para refinar las estimaciones realizadas por el sistema RO-SLAM. Otros capítulos estudian y proponen técnicas para la integración de los algoritmos RO-SLAM presentados a sistemas con múltiples robots, así como el uso de técnicas de percepción activa que permitan reducir la incertidumbre del sistema ante trayectorias con carencia de trilateración entre el robot y los sensores de destancia estáticos del mapa. Todos los métodos propuestos han sido validados mediante simulaciones y experimentos con sistemas reales detallados en esta tesis. Además, todos los sistemas software implementados, así como los conjuntos de datos registrados durante la experimentación han sido publicados y documentados para su uso en la comunidad científica