Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Distributed detection, localization, and estimation in time-critical wireless sensor networks

In this thesis the problem of distributed detection, localization, and estimation (DDLE) of a stationary target in a fusion center (FC) based wireless sensor network (WSN) is considered. The communication process is subject to time-critical operation, restricted power and bandwidth (BW) resources operating over a shared communication channel Buffering from Rayleigh fading and phase noise. A novel algorithm is proposed to solve the DDLE problem consisting of two dependent stages: distributed detection and distributed estimation. The WSN performs distributed detection first and based on the global detection decision the distributed estimation stage is performed. The communication between the SNs and the FC occurs over a shared channel via a slotted Aloha MAC protocol to conserve BW. In distributed detection, hard decision fusion is adopted, using the counting rule (CR), and sensor censoring in order to save power and BW. The effect of Rayleigh fading on distributed detection is also considered and accounted for by using distributed diversity combining techniques where the diversity combining is among the sensor nodes (SNs) in lieu of having the processing done at the FC. Two distributed techniques are proposed: the distributed maximum ratio combining (dMRC) and the distributed Equal Gain Combining (dEGC). Both techniques show superior detection performance when compared to conventional diversity combining procedures that take place at the FC. In distributed estimation, the segmented distributed localization and estimation (SDLE) framework is proposed. The SDLE enables efficient power and BW processing. The SOLE hinges on the idea of introducing intermediate parameters that are estimated locally by the SNs and transmitted to the FC instead of the actual measurements. This concept decouples the main problem into a simpler set of local estimation problems solved at the SNs and a global estimation problem solved at the FC. Two algorithms are proposed for solving the local problem: a nonlinear least squares (NLS) algorithm using the variable projection (VP) method and a simpler gird search (GS) method. Also, Four algorithms are proposed to solve the global problem: NLS, GS, hyperspherical intersection method (HSI), and robust hyperspherical intersection (RHSI) method. Thus, the SDLE can be solved through local and global algorithm combinations. Five combinations are tied: NLS2 (NLS-NLS), NLS-HSI, NLS-RHSI, GS2, and GS-N LS. It turns out that the last algorithm combination delivers the best localization and estimation performance. In fact , the target can be localized with less than one meter error. The SNs send their local estimates to the FC over a shared channel using the slotted-Aloha MAC protocol, which suits WSNs since it requires only one channel. However, Aloha is known for its relatively high medium access or contention delay given the medium access probability is poorly chosen. This fact significantly hinders the time-critical operation of the system. Hence, multi-packet reception (MPR) is used with slotted Aloha protocol, in which several channels are used for contention. The contention delay is analyzed for slotted Aloha with and without MPR. More specifically, the mean and variance have been analytically computed and the contention delay distribution is approximated. Having theoretical expressions for the contention delay statistics enables optimizing both the medium access probability and the number of MPR channels in order to strike a trade-off between delay performance and complexity

Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

This research developed a method for multiple Unmanned Aircraft Systems (UAS) to efficiently collect data from a Wireless Sensor Networks (WSN). WSN are composed of any number of fixed, ground-based sensors that collect and upload local environmental data to over flying UAS. The three-step method first uniquely assigns aircraft to specific sensors on the ground. Second, an efficient flight path is calculated to minimize the aircraft flight time required to verify their assigned sensors. Finally, sensors reporting relatively higher rates of local environmental activity are re-assigned to dedicated aircraft tasked with concentrating on only those sensors. This work was sponsored by the Air Force Research Laboratory, Control Sciences branch, at Wright Patterson AFB. Based on simulated scenarios and preliminary flight tests, optimal flight paths resulted in a 14 to 32 reduction in flight time and distance when compared to traditional flight planning methods

Reliability Evaluation for Clustered WSNs under Malware Propagation.

We consider a clustered wireless sensor network (WSN) under epidemic-malware propagation conditions and solve the problem of how to evaluate its reliability so as to ensure efficient, continuous, and dependable transmission of sensed data from sensor nodes to the sink. Facing the contradiction between malware intention and continuous-time Markov chain (CTMC) randomness, we introduce a strategic game that can predict malware infection in order to model a successful infection as a CTMC state transition. Next, we devise a novel measure to compute the Mean Time to Failure (MTTF) of a sensor node, which represents the reliability of a sensor node continuously performing tasks such as sensing, transmitting, and fusing data. Since clustered WSNs can be regarded as parallel-serial-parallel systems, the reliability of a clustered WSN can be evaluated via classical reliability theory. Numerical results show the influence of parameters such as the true positive rate and the false positive rate on a sensor node's MTTF. Furthermore, we validate the method of reliability evaluation for a clustered WSN according to the number of sensor nodes in a cluster, the number of clusters in a route, and the number of routes in the WSN

An Extensive Validation of a SIR Epidemic Model to Study the Propagation of Jamming Attacks against IoT Wireless Networks.

This paper describes the utilization of an epidemic approach to study the propagation of jamming attacks, which can affect to different communication layers of all nodes in a variety of Internet of Things (IoT) wireless networks, regardless of the complexity and computing power of the devices. The jamming term considers both the more classical approach of interfering signals focusing on the physical level of the systems, and the cybersecurity approach that includes the attacks generated in upper layers like Medium Access Control (MAC), producing the same effect on the communication channel. In order to study the accuracy of the proposed epidemic model to estimate the propagation of jamming attacks, this paper uses the results of public simulations and experiments. It is of special interest the data obtained from experiments based on protocols such as Multi-Parent Hierarchical Protocol (MPH), Ad-hoc On-demand Distance Vector (AODV), and Dynamic Source Routing (DSR), working over the IEEE 802.15.4 standard. Then, using the formulation of the deterministic epidemiological model Susceptible–Infected–Recovered (SIR), together the abovementioned simulation, it has been seen that the proposed epidemic model could be used to estimate in that kind of IoT networks, the impact of the jamming attack in terms of attack severity and attack persistenceThis research has been partially supported by Ministerio de Economía, Industria y Competitividad (MINECO), Agencia Estatal de Investigación (AEI), and Fondo Europeo de Desarrollo Regional (FEDER, UE) under projects TIN2017-84844-C2-1-R and PGC2018-098813-B-C32

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Monitoring and Self-diagnosis of Civil Engineering Structures: Classical and Innovative Applications

Eventi estremi come esplosioni o terremoti possono avere un profondo impatto nella sicurezza degli edifici. Le zone sismiche devono convivere con questi tragici eventi, per questo monitorare in maniera continua le condizioni di salute di una struttura è necessario e auspicabile in molti casi. Il monitoraggio strutturale (Structural Health Monitoring – SHM) rappresenta un potente strumento per la valutazione del comportamento dinamico della struttura monitorata. Fino a pochi anni fa queste tecniche erano impiegate prevalentemente in ambito meccanico, aeronautico e nell’ingegneria aerospaziale. Al giorno d’oggi, la riduzione dei costi della strumentazione, sistemi di acquisizione dati di nuova generazione e l’incremento continuo dell’efficienta nelle analisi numeriche hanno reso possibile l’applicazione di queste tecniche anche a strutture civili ordinarie. Le tecniche di monitoraggio strutturale vengono applicate non solo in grandi infrastrutture come ponti, dighe o grattacieli, ma anche in strutture storiche o edifici residenziali. In questo contesto questa tesi tenta di esaminare differenti aspetti del monitoraggio strutturale, in particolar modo riferite a edifici ordinari. Attraverso tecniche Output-Only (Operational Modal Analysis – OMA) sono state monitorate diverse strutture civili con reti di sensori cablate, al fine di ottenere il comportamento dinamico strutturale nelle reali condizioni opertive. Particolare attenzione è stata focalizzata in un altra importante tematica dell’ingegneria strutturale: il danneggiamento strutturale. Attraverso un approccio numerico viene presentato un nuovo metodo per la localizzazione e quantificazione del danno a seguito di un evento sismico. In alternativa alla classica rete cablata, è stato sviluppato un sistema di acquisizione con sensori wireless (Wireless Sensor Network – WSN). I principali risultati ottenuti con questa applicazione vengono riportati nella presente tesi, unitamente al design dei sensori low-cost. Con l’ausilio della sensoristica sviluppata è stato monitorato un edificio storico in muratura, mostrando i risultati positivi ottenuti a seguito della campagna di acquisizione di rumore ambientale (Ambient Vibration Survey -AVS).Extreme events like explosions and earthquakes may have a deep impact on building safety. Seismic regions must live with these tragic events, so that continuous monitoring of structure health conditions is necessary in many cases. Structural Health Monitoring (SHM) represents a powerful tool for the evaluation of dynamic behavior of monitored structures. Until a few years ago these techniques were widely employed especially in mechanical, aeronautical and aerospace engineering. Nowadays, the reduction of equipment costs, the new generation of data acquisition systems, together with the continuous improvement of computational analysis have made it possible to apply SHM also to civil structures without strategic importance. SHM has moved from large infrastructures like bridges, dams and skyscrapers to historical heritage and residential buildings. In this background, the present work tries to examine different aspects of SHM applications, especially referred to ordinary buildings. Using Operational Modal Analysis (OMA) techniques, several civil structures have been monitored through a wired network sensor, in order to obtain the dynamic behavior in operating conditions. The relevant data collection provides a useful tool for calibrating the accuracy and sensitivity of similar SHM case studies. Specific attention is focused in another important issue in civil and in mechanical engineering: detection of structural damages. Through a numerical approach, a new method for damage localization and quantification is proposed. Besides the traditional wired acquisition system a Wireless Sensor Network (WSN) has been developed. The issues related to the usage of low-cost sensors and new generation data acquisition tools for non-destructive structural testing are discussed. Using the WSN an historical masonry building has been monitored, showing the positive results obtained following the Ambient Vibration Survey (AVS)

Distributed Detection and Estimation in Wireless Sensor Networks

In this article we consider the problems of distributed detection and estimation in wireless sensor networks. In the first part, we provide a general framework aimed to show how an efficient design of a sensor network requires a joint organization of in-network processing and communication. Then, we recall the basic features of consensus algorithm, which is a basic tool to reach globally optimal decisions through a distributed approach. The main part of the paper starts addressing the distributed estimation problem. We show first an entirely decentralized approach, where observations and estimations are performed without the intervention of a fusion center. Then, we consider the case where the estimation is performed at a fusion center, showing how to allocate quantization bits and transmit powers in the links between the nodes and the fusion center, in order to accommodate the requirement on the maximum estimation variance, under a constraint on the global transmit power. We extend the approach to the detection problem. Also in this case, we consider the distributed approach, where every node can achieve a globally optimal decision, and the case where the decision is taken at a central node. In the latter case, we show how to allocate coding bits and transmit power in order to maximize the detection probability, under constraints on the false alarm rate and the global transmit power. Then, we generalize consensus algorithms illustrating a distributed procedure that converges to the projection of the observation vector onto a signal subspace. We then address the issue of energy consumption in sensor networks, thus showing how to optimize the network topology in order to minimize the energy necessary to achieve a global consensus. Finally, we address the problem of matching the topology of the network to the graph describing the statistical dependencies among the observed variables.Comment: 92 pages, 24 figures. To appear in E-Reference Signal Processing, R. Chellapa and S. Theodoridis, Eds., Elsevier, 201