A graph-theoretical approach in brain functional networks. Possible implications in EEG studies

Abstract Background Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory, that is a mathematical representation of a network, which is essentially reduced to nodes and connections between them. Methods We used high-resolution EEG technology to enhance the poor spatial information of the EEG activity on the scalp and it gives a measure of the electrical activity on the cortical surface. Afterwards, we used the Directed Transfer Function (DTF) that is a multivariate spectral measure for the estimation of the directional influences between any given pair of channels in a multivariate dataset. Finally, a graph theoretical approach was used to model the brain networks as graphs. These methods were used to analyze the structure of cortical connectivity during the attempt to move a paralyzed limb in a group (N=5) of spinal cord injured patients and during the movement execution in a group (N=5) of healthy subjects. Results Analysis performed on the cortical networks estimated from the group of normal and SCI patients revealed that both groups present few nodes with a high out-degree value (i.e. outgoing links). This property is valid in the networks estimated for all the frequency bands investigated. In particular, cingulate motor areas (CMAs) ROIs act as ‘‘hubs’’ for the outflow of information in both groups, SCI and healthy. Results also suggest that spinal cord injuries affect the functional architecture of the cortical network sub-serving the volition of motor acts mainly in its local feature property. In particular, a higher local efficiency El can be observed in the SCI patients for three frequency bands, theta (3-6 Hz), alpha (7-12 Hz) and beta (13-29 Hz). By taking into account all the possible pathways between different ROI couples, we were able to separate clearly the network properties of the SCI group from the CTRL group. In particular, we report a sort of compensatory mechanism in the SCI patients for the Theta (3-6 Hz) frequency band, indicating a higher level of “activation” Ω within the cortical network during the motor task. The activation index is directly related to diffusion, a type of dynamics that underlies several biological systems including possible spreading of neuronal activation across several cortical regions. Conclusions The present study aims at demonstrating the possible applications of graph theoretical approaches in the analyses of brain functional connectivity from EEG signals. In particular, the methodological aspects of the i) cortical activity from scalp EEG signals, ii) functional connectivity estimations iii) graph theoretical indexes are emphasized in the present paper to show their impact in a real application.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

Mapping virtual networks onto substrate networks

Network virtualization is a promising technique for building the Internet of the future since it enables the low cost introduction of new features into network elements. An open issue in such virtualization is how to effect an efficient mapping of virtual network elements onto those of the existing physical network, also called the substrate network. Mapping is an NP-hard problem and existing solutions ignore various real network characteristics in order to solve the problem in a reasonable time frame. This paper introduces new algorithms to solve this problem based on 0–1 integer linear programming, algorithms based on a whole new set of network parameters not taken into account by previous proposals. Approximative algorithms proposed here allow the mapping of virtual networks on large network substrates. Simulation experiments give evidence of the efficiency of the proposed algorithms.

Systematics of the Oswaldoi Complex (Anopheles, Nyssorhynchus) in South America

Abstract Background Effective malaria control relies on accurate identification of those Anopheles mosquitoes responsible for the transmission of Plasmodium parasites. Anopheles oswaldoi s.l. has been incriminated as a malaria vector in Colombia and some localities in Brazil, but not ubiquitously throughout its Neotropical range. This evidence together with variable morphological characters and genetic differences supports that An. oswaldoi s.l. compromises a species complex. The recent fully integrated redescription of An. oswaldoi s.s. provides a solid taxonomic foundation from which to molecularly determine other members of the complex. Methods DNA sequences of the Second Internal Transcribed Spacer (ITS2 - rDNA) (n = 192) and the barcoding region of the Cytochrome Oxidase I gene (COI - mtDNA) (n = 110) were generated from 255 specimens of An. oswaldoi s.l. from 33 localities: Brazil (8 localities, including the lectotype series of An. oswaldoi), Ecuador (4), Colombia (17), Trinidad and Tobago (1), and Peru (3). COI sequences were analyzed employing the Kimura-two-parameter model (K2P), Bayesian analysis (MrBayes), Mixed Yule-Coalescent model (MYC, for delimitation of clusters) and TCS genealogies. Results Separate and combined analysis of the COI and ITS2 data sets unequivocally supported four separate species: two previously determined (An. oswaldoi s.s. and An. oswaldoi B) and two newly designated species in the Oswaldoi Complex (An. oswaldoi A and An. sp. nr. konderi). The COI intra- and inter-specific genetic distances for the four taxa were non-overlapping, averaging 0.012 (0.007 to 0.020) and 0.052 (0.038 to 0.064), respectively. The concurring four clusters delineated by MrBayes and MYC, and four independent TCS networks, strongly confirmed their separate species status. In addition, An. konderi of Sallum should be regarded as unique with respect to the above. Despite initially being included as an outgroup taxon, this species falls well within the examined taxa, suggesting a combined analysis of these taxa would be most appropriate. Conclusions: Through novel data and retrospective comparison of available COI and ITS2 DNA sequences, evidence is shown to support the separate species status of An. oswaldoi s.s., An. oswaldoi A and An. oswaldoi B, and at least two species in the closely related An. konderi complex (An. sp. nr. konderi, An. konderi of Sallum). Although An. oswaldoi s.s. has never been implicated in malaria transmission, An. oswaldoi B is a confirmed vector and the new species An. oswaldoi A and An. sp. nr. konderi are circumstantially implicated, most likely acting as secondary vectors.

Essays on Bayesian Inference for Social Networks

This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time. A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation. The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step. In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications. Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.

Dynamic services in mobile ad hoc networks

The increasing diffusion of wireless-enabled portable devices is pushing toward the design of novel service scenarios, promoting temporary and opportunistic interactions in infrastructure-less environments. Mobile Ad Hoc Networks (MANET) are the general model of these higly dynamic networks that can be specialized, depending on application cases, in more specific and refined models such as Vehicular Ad Hoc Networks and Wireless Sensor Networks. Two interesting deployment cases are of increasing relevance: resource diffusion among users equipped with portable devices, such as laptops, smart phones or PDAs in crowded areas (termed dense MANET) and dissemination/indexing of monitoring information collected in Vehicular Sensor Networks. The extreme dynamicity of these scenarios calls for novel distributed protocols and services facilitating application development. To this aim we have designed middleware solutions supporting these challenging tasks. REDMAN manages, retrieves, and disseminates replicas of software resources in dense MANET; it implements novel lightweight protocols to maintain a desired replication degree despite participants mobility, and efficiently perform resource retrieval. REDMAN exploits the high-density assumption to achieve scalability and limited network overhead. Sensed data gathering and distributed indexing in Vehicular Networks raise similar issues: we propose a specific middleware support, called MobEyes, exploiting node mobility to opportunistically diffuse data summaries among neighbor vehicles. MobEyes creates a low-cost opportunistic distributed index to query the distributed storage and to determine the location of needed information. Extensive validation and testing of REDMAN and MobEyes prove the effectiveness of our original solutions in limiting communication overhead while maintaining the required accuracy of replication degree and indexing completeness, and demonstrates the feasibility of the middleware approach.

Motion control and real-time systems: an approach to trajectory rebuilding in non-deterministic networks

Motion control is a sub-field of automation, in which the position and/or velocity of machines are controlled using some type of device. In motion control the position, velocity, force, pressure, etc., profiles are designed in such a way that the different mechanical parts work as an harmonious whole in which a perfect synchronization must be achieved. The real-time exchange of information in the distributed system that is nowadays an industrial plant plays an important role in order to achieve always better performance, better effectiveness and better safety. The network for connecting field devices such as sensors, actuators, field controllers such as PLCs, regulators, drive controller etc., and man-machine interfaces is commonly called fieldbus. Since the motion transmission is now task of the communication system, and not more of kinematic chains as in the past, the communication protocol must assure that the desired profiles, and their properties, are correctly transmitted to the axes then reproduced or else the synchronization among the different parts is lost with all the resulting consequences. In this thesis, the problem of trajectory reconstruction in the case of an event-triggered communication system is faced. The most important feature that a real-time communication system must have is the preservation of the following temporal and spatial properties: absolute temporal consistency, relative temporal consistency, spatial consistency. Starting from the basic system composed by one master and one slave and passing through systems made up by many slaves and one master or many masters and one slave, the problems in the profile reconstruction and temporal properties preservation, and subsequently the synchronization of different profiles in network adopting an event-triggered communication system, have been shown. These networks are characterized by the fact that a common knowledge of the global time is not available. Therefore they are non-deterministic networks. Each topology is analyzed and the proposed solution based on phase-locked loops adopted for the basic master-slave case has been improved to face with the other configurations.

Cross-layer optimizations in multi-hop ad hoc networks

Unlike traditional wireless networks, characterized by the presence of last-mile, static and reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by collections of mobile and static terminals that exchange data by enabling each other's communication. Supporting multi-hop communication in a MANET is a challenging research area because it requires cooperation between different protocol layers (MAC, routing, transport). In particular, MAC and routing protocols could be considered mutually cooperative protocol layers. When a route is established, the exposed and hidden terminal problems at MAC layer may decrease the end-to-end performance proportionally with the length of each route. Conversely, the contention at MAC layer may cause a routing protocol to respond by initiating new routes queries and routing table updates. Multi-hop communication may also benefit the presence of pseudo-centralized virtual infrastructures obtained by grouping nodes into clusters. Clustering structures may facilitate the spatial reuse of resources by increasing the system capacity: at the same time, the clustering hierarchy may be used to coordinate transmissions events inside the network and to support intra-cluster routing schemes. Again, MAC and clustering protocols could be considered mutually cooperative protocol layers: the clustering scheme could support MAC layer coordination among nodes, by shifting the distributed MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the system benefits of the clustering scheme could be emphasized by the pseudo-centralized MAC layer with the support for differentiated access priorities and controlled contention. In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering and routing protocols in MANETs. As main contribution, we study and analyze the integration of MAC and clustering schemes to support multi-hop communication in large-scale ad hoc networks. A novel clustering protocol, named Availability Clustering (AC), is defined under general nodes' heterogeneity assumptions in terms of connectivity, available energy and relative mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol, named Differentiated Distributed Coordination Function (DDCF), whose focus is to implement adaptive access differentiation based on the node roles, which have been assigned by the upper-layer's clustering scheme. We extensively simulate the proposed clustering scheme by showing its effectiveness in dominating the network dynamics, under some stressing mobility models and different mobility rates. Based on these results, we propose a possible application of the cross-layer MAC+Clustering scheme to support the fast propagation of alert messages in a vehicular environment. At the same time, we investigate the integration of MAC and routing protocols in large scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by extending the AOMDV protocol with a novel load-balancing approach to concurrently distribute the traffic among the multiple paths. We also study the composition effect of a IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF), used to reduce the effects of self-contention among frames at the MAC layer. The protocol framework is modelled and extensively simulated for a large set of metrics and scenarios. For both the schemes, the simulation results reveal the benefits of the cross-layer MAC+routing and MAC+clustering approaches over single-layer solutions.

Management and routing algorithms for ad-hoc and sensor networks

Large scale wireless adhoc networks of computers, sensors, PDAs etc. (i.e. nodes) are revolutionizing connectivity and leading to a paradigm shift from centralized systems to highly distributed and dynamic environments. An example of adhoc networks are sensor networks, which are usually composed by small units able to sense and transmit to a sink elementary data which are successively processed by an external machine. Recent improvements in the memory and computational power of sensors, together with the reduction of energy consumptions, are rapidly changing the potential of such systems, moving the attention towards datacentric sensor networks. A plethora of routing and data management algorithms have been proposed for the network path discovery ranging from broadcasting/floodingbased approaches to those using global positioning systems (GPS). We studied WGrid, a novel decentralized infrastructure that organizes wireless devices in an adhoc manner, where each node has one or more virtual coordinates through which both message routing and data management occur without reliance on either flooding/broadcasting operations or GPS. The resulting adhoc network does not suffer from the deadend problem, which happens in geographicbased routing when a node is unable to locate a neighbor closer to the destination than itself. WGrid allow multidimensional data management capability since nodes' virtual coordinates can act as a distributed database without needing neither special implementation or reorganization. Any kind of data (both single and multidimensional) can be distributed, stored and managed. We will show how a location service can be easily implemented so that any search is reduced to a simple query, like for any other data type. WGrid has then been extended by adopting a replication methodology. We called the resulting algorithm WRGrid. Just like WGrid, WRGrid acts as a distributed database without needing neither special implementation nor reorganization and any kind of data can be distributed, stored and managed. We have evaluated the benefits of replication on data management, finding out, from experimental results, that it can halve the average number of hops in the network. The direct consequence of this fact are a significant improvement on energy consumption and a workload balancing among sensors (number of messages routed by each node). Finally, thanks to the replications, whose number can be arbitrarily chosen, the resulting sensor network can face sensors disconnections/connections, due to failures of sensors, without data loss. Another extension to {WGrid} is {W*Grid} which extends it by strongly improving network recovery performance from link and/or device failures that may happen due to crashes or battery exhaustion of devices or to temporary obstacles. W*Grid guarantees, by construction, at least two disjoint paths between each couple of nodes. This implies that the recovery in W*Grid occurs without broadcasting transmissions and guaranteeing robustness while drastically reducing the energy consumption. An extensive number of simulations shows the efficiency, robustness and traffic road of resulting networks under several scenarios of device density and of number of coordinates. Performance analysis have been compared to existent algorithms in order to validate the results.

Design of optical networks for advanced applications

Nowadays, computing is migrating from traditional high performance and distributed computing to pervasive and utility computing based on heterogeneous networks and clients. The current trend suggests that future IT services will rely on distributed resources and on fast communication of heterogeneous contents. The success of this new range of services is directly linked to the effectiveness of the infrastructure in delivering them. The communication infrastructure will be the aggregation of different technologies even though the current trend suggests the emergence of single IP based transport service. Optical networking is a key technology to answer the increasing requests for dynamic bandwidth allocation and configure multiple topologies over the same physical layer infrastructure, optical networks today are still “far” from accessible from directly configure and offer network services and need to be enriched with more “user oriented” functionalities. However, current Control Plane architectures only facilitate efficient end-to-end connectivity provisioning and certainly cannot meet future network service requirements, e.g. the coordinated control of resources. The overall objective of this work is to provide the network with the improved usability and accessibility of the services provided by the Optical Network. More precisely, the definition of a service-oriented architecture is the enable technology to allow user applications to gain benefit of advanced services over an underlying dynamic optical layer. The definition of a service oriented networking architecture based on advanced optical network technologies facilitates users and applications access to abstracted levels of information regarding offered advanced network services. This thesis faces the problem to define a Service Oriented Architecture and its relevant building blocks, protocols and languages. In particular, this work has been focused on the use of the SIP protocol as a inter-layers signalling protocol which defines the Session Plane in conjunction with the Network Resource Description language. On the other hand, an advantage optical network must accommodate high data bandwidth with different granularities. Currently, two main technologies are emerging promoting the development of the future optical transport network, Optical Burst and Packet Switching. Both technologies respectively promise to provide all optical burst or packet switching instead of the current circuit switching. However, the electronic domain is still present in the scheduler forwarding and routing decision. Because of the high optics transmission frequency the burst or packet scheduler faces a difficult challenge, consequentially, high performance and time focused design of both memory and forwarding logic is need. This open issue has been faced in this thesis proposing an high efficiently implementation of burst and packet scheduler. The main novelty of the proposed implementation is that the scheduling problem has turned into simple calculation of a min/max function and the function complexity is almost independent of on the traffic conditions.

Packet erasure correcting codes for wireless sensor networks: implementation and field trial measurements

This thesis regards the Wireless Sensor Network (WSN), as one of the most important technologies for the twenty-first century and the implementation of different packet correcting erasure codes to cope with the ”bursty” nature of the transmission channel and the possibility of packet losses during the transmission. The limited battery capacity of each sensor node makes the minimization of the power consumption one of the primary concerns in WSN. Considering also the fact that in each sensor node the communication is considerably more expensive than computation, this motivates the core idea to invest computation within the network whenever possible to safe on communication costs. The goal of the research was to evaluate a parameter, for example the Packet Erasure Ratio (PER), that permit to verify the functionality and the behavior of the created network, validate the theoretical expectations and evaluate the convenience of introducing the recovery packet techniques using different types of packet erasure codes in different types of networks. Thus, considering all the constrains of energy consumption in WSN, the topic of this thesis is to try to minimize it by introducing encoding/decoding algorithms in the transmission chain in order to prevent the retransmission of the erased packets through the Packet Erasure Channel and save the energy used for each retransmitted packet. In this way it is possible extend the lifetime of entire network.

The swelling behaviour of polyelectrolyte networks

Being basic ingredients of numerous daily-life products with significant industrial importance as well as basic building blocks for biomaterials, charged hydrogels continue to pose a series of unanswered challenges for scientists even after decades of practical applications and intensive research efforts. Despite a rather simple internal structure it is mainly the unique combination of short- and long-range forces which render scientific investigations of their characteristic properties to be quite difficult. Hence early on computer simulations were used to link analytical theory and empirical experiments, bridging the gap between the simplifying assumptions of the models and the complexity of real world measurements. Due to the immense numerical effort, even for high performance supercomputers, system sizes and time scales were rather restricted until recently, whereas it only now has become possible to also simulate a network of charged macromolecules. This is the topic of the presented thesis which investigates one of the fundamental and at the same time highly fascinating phenomenon of polymer research: The swelling behaviour of polyelectrolyte networks. For this an extensible simulation package for the research on soft matter systems, ESPResSo for short, was created which puts a particular emphasis on mesoscopic bead-spring-models of complex systems. Highly efficient algorithms and a consistent parallelization reduced the necessary computation time for solving equations of motion even in case of long-ranged electrostatics and large number of particles, allowing to tackle even expensive calculations and applications. Nevertheless, the program has a modular and simple structure, enabling a continuous process of adding new potentials, interactions, degrees of freedom, ensembles, and integrators, while staying easily accessible for newcomers due to a Tcl-script steering level controlling the C-implemented simulation core. Numerous analysis routines provide means to investigate system properties and observables on-the-fly. Even though analytical theories agreed on the modeling of networks in the past years, our numerical MD-simulations show that even in case of simple model systems fundamental theoretical assumptions no longer apply except for a small parameter regime, prohibiting correct predictions of observables. Applying a "microscopic" analysis of the isolated contributions of individual system components, one of the particular strengths of computer simulations, it was then possible to describe the behaviour of charged polymer networks at swelling equilibrium in good solvent and close to the Theta-point by introducing appropriate model modifications. This became possible by enhancing known simple scaling arguments with components deemed crucial in our detailed study, through which a generalized model could be constructed. Herewith an agreement of the final system volume of swollen polyelectrolyte gels with results of computer simulations could be shown successfully over the entire investigated range of parameters, for different network sizes, charge fractions, and interaction strengths. In addition, the "cell under tension" was presented as a self-regulating approach for predicting the amount of swelling based on the used system parameters only. Without the need for measured observables as input, minimizing the free energy alone already allows to determine the the equilibrium behaviour. In poor solvent the shape of the network chains changes considerably, as now their hydrophobicity counteracts the repulsion of like-wise charged monomers and pursues collapsing the polyelectrolytes. Depending on the chosen parameters a fragile balance emerges, giving rise to fascinating geometrical structures such as the so-called pear-necklaces. This behaviour, known from single chain polyelectrolytes under similar environmental conditions and also theoretically predicted, could be detected for the first time for networks as well. An analysis of the total structure factors confirmed first evidences for the existence of such structures found in experimental results.

Fiber-Optic Technologies for Wireline and Wireless In-building Networks

This doctoral dissertation aims to establish fiber-optic technologies overcoming the limiting issues of data communications in indoor environments. Specific applications are broadband mobile distribution in different in-building scenarios and high-speed digital transmission over short-range wired optical systems. Two key enabling technologies are considered: Radio over Fiber (RoF) techniques over standard silica fibers for distributed antenna systems (DAS) and plastic optical fibers (POFs) for short-range communications. Hence, the objectives and achievements of this thesis are related to the application of RoF and POF technologies in different in-building scenarios. On one hand, a theoretical and experimental analysis combined with demonstration activities has been performed on cost-effective RoF systems. An extensive modeling on modal noise impact both on linear and non-linear characteristics of RoF link over silica multimode fiber has been performed to achieve link design rules for an optimum choice of the transmitter, receiver and launching technique. A successful transmission of Long Term Evolution (LTE) mobile signals on the resulting optimized RoF system over silica multimode fiber employing a Fabry-Perot LD, central launch technique and a photodiode with a built-in ball lens was demonstrated up to 525m with performances well compliant with standard requirements. On the other hand, digital signal processing techniques to overcome the bandwidth limitation of POF have been investigated. An uncoded net bit-rate of 5.15Gbit/s was obtained on a 50m long POF link employing an eye-safe transmitter, a silicon photodiode, and DMT modulation with bit and power loading algorithm. With the insertion of 3x2N quadrature amplitude modulation constellation formats, an uncoded net-bit-rate of 5.4Gbit/s was obtained on a 50 m long POF link employing an eye-safe transmitter and a silicon avalanche photodiode. Moreover, simultaneous transmission of baseband 2Gbit/s with DMT and 200Mbit/s with an ultra-wideband radio signal has been validated over a 50m long POF link.

Wireless Sensor Networks for Monitoring Applications

Wireless Sensor Networks (WSNs) are getting wide-spread attention since they became easily accessible with their low costs. One of the key elements of WSNs is distributed sensing. When the precise location of a signal of interest is unknown across the monitored region, distributing many sensors randomly/uniformly may yield with a better representation of the monitored random process than a traditional sensor deployment. In a typical WSN application the data sensed by nodes is usually sent to one (or more) central device, denoted as sink, which collects the information and can either act as a gateway towards other networks (e.g. Internet), where data can be stored, or be processed in order to command the actuators to perform special tasks. In such a scenario, a dense sensor deployment may create bottlenecks when many nodes competing to access the channel. Even though there are mitigation methods on the channel access, concurrent (parallel) transmissions may occur. In this study, always on the scope of monitoring applications, the involved development progress of two industrial projects with dense sensor deployments (eDIANA Project funded by European Commission and Centrale Adritica Project funded by Coop Italy) and the measurement results coming from several different test-beds evoked the necessity of a mathematical analysis on concurrent transmissions. To the best of our knowledge, in the literature there is no mathematical analysis of concurrent transmission in 2.4 GHz PHY of IEEE 802.15.4. In the thesis, experience stories of eDIANA and Centrale Adriatica Projects and a mathematical analysis of concurrent transmissions starting from O-QPSK chip demodulation to the packet reception rate with several different types of theoretical demodulators, are presented. There is a very good agreement between the measurements so far in the literature and the mathematical analysis.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.