19 resultados para distributed application

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Actual trends in software development are pushing the need to face a multiplicity of diverse activities and interaction styles characterizing complex and distributed application domains, in such a way that the resulting dynamics exhibits some grade of order, i.e. in terms of evolution of the system and desired equilibrium. Autonomous agents and Multiagent Systems are argued in literature as one of the most immediate approaches for describing such a kind of challenges. Actually, agent research seems to converge towards the definition of renewed abstraction tools aimed at better capturing the new demands of open systems. Besides agents, which are assumed as autonomous entities purposing a series of design objectives, Multiagent Systems account new notions as first-class entities, aimed, above all, at modeling institutional/organizational entities, placed for normative regulation, interaction and teamwork management, as well as environmental entities, placed as resources to further support and regulate agent work. The starting point of this thesis is recognizing that both organizations and environments can be rooted in a unifying perspective. Whereas recent research in agent systems seems to account a set of diverse approaches to specifically face with at least one aspect within the above mentioned, this work aims at proposing a unifying approach where both agents and their organizations can be straightforwardly situated in properly designed working environments. In this line, this work pursues reconciliation of environments with sociality, social interaction with environment based interaction, environmental resources with organizational functionalities with the aim to smoothly integrate the various aspects of complex and situated organizations in a coherent programming approach. Rooted in Agents and Artifacts (A&A) meta-model, which has been recently introduced both in the context of agent oriented software engineering and programming, the thesis promotes the notion of Embodied Organizations, characterized by computational infrastructures attaining a seamless integration between agents, organizations and environmental entities.

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Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

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The research activity carried out during the PhD course in Electrical Engineering belongs to the branch of electric and electronic measurements. The main subject of the present thesis is a distributed measurement system to be installed in Medium Voltage power networks, as well as the method developed to analyze data acquired by the measurement system itself and to monitor power quality. In chapter 2 the increasing interest towards power quality in electrical systems is illustrated, by reporting the international research activity inherent to the problem and the relevant standards and guidelines emitted. The aspect of the quality of voltage provided by utilities and influenced by customers in the various points of a network came out only in recent years, in particular as a consequence of the energy market liberalization. Usually, the concept of quality of the delivered energy has been associated mostly to its continuity. Hence the reliability was the main characteristic to be ensured for power systems. Nowadays, the number and duration of interruptions are the “quality indicators” commonly perceived by most customers; for this reason, a short section is dedicated also to network reliability and its regulation. In this contest it should be noted that although the measurement system developed during the research activity belongs to the field of power quality evaluation systems, the information registered in real time by its remote stations can be used to improve the system reliability too. Given the vast scenario of power quality degrading phenomena that usually can occur in distribution networks, the study has been focused on electromagnetic transients affecting line voltages. The outcome of such a study has been the design and realization of a distributed measurement system which continuously monitor the phase signals in different points of a network, detect the occurrence of transients superposed to the fundamental steady state component and register the time of occurrence of such events. The data set is finally used to locate the source of the transient disturbance propagating along the network lines. Most of the oscillatory transients affecting line voltages are due to faults occurring in any point of the distribution system and have to be seen before protection equipment intervention. An important conclusion is that the method can improve the monitored network reliability, since the knowledge of the location of a fault allows the energy manager to reduce as much as possible both the area of the network to be disconnected for protection purposes and the time spent by technical staff to recover the abnormal condition and/or the damage. The part of the thesis presenting the results of such a study and activity is structured as follows: chapter 3 deals with the propagation of electromagnetic transients in power systems by defining characteristics and causes of the phenomena and briefly reporting the theory and approaches used to study transients propagation. Then the state of the art concerning methods to detect and locate faults in distribution networks is presented. Finally the attention is paid on the particular technique adopted for the same purpose during the thesis, and the methods developed on the basis of such approach. Chapter 4 reports the configuration of the distribution networks on which the fault location method has been applied by means of simulations as well as the results obtained case by case. In this way the performance featured by the location procedure firstly in ideal then in realistic operating conditions are tested. In chapter 5 the measurement system designed to implement the transients detection and fault location method is presented. The hardware belonging to the measurement chain of every acquisition channel in remote stations is described. Then, the global measurement system is characterized by considering the non ideal aspects of each device that can concur to the final combined uncertainty on the estimated position of the fault in the network under test. Finally, such parameter is computed according to the Guide to the Expression of Uncertainty in Measurements, by means of a numeric procedure. In the last chapter a device is described that has been designed and realized during the PhD activity aiming at substituting the commercial capacitive voltage divider belonging to the conditioning block of the measurement chain. Such a study has been carried out aiming at providing an alternative to the used transducer that could feature equivalent performance and lower cost. In this way, the economical impact of the investment associated to the whole measurement system would be significantly reduced, making the method application much more feasible.

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Recent progress in microelectronic and wireless communications have enabled the development of low cost, low power, multifunctional sensors, which has allowed the birth of new type of networks named wireless sensor networks (WSNs). The main features of such networks are: the nodes can be positioned randomly over a given field with a high density; each node operates both like sensor (for collection of environmental data) as well as transceiver (for transmission of information to the data retrieval); the nodes have limited energy resources. The use of wireless communications and the small size of nodes, make this type of networks suitable for a large number of applications. For example, sensor nodes can be used to monitor a high risk region, as near a volcano; in a hospital they could be used to monitor physical conditions of patients. For each of these possible application scenarios, it is necessary to guarantee a trade-off between energy consumptions and communication reliability. The thesis investigates the use of WSNs in two possible scenarios and for each of them suggests a solution that permits to solve relating problems considering the trade-off introduced. The first scenario considers a network with a high number of nodes deployed in a given geographical area without detailed planning that have to transmit data toward a coordinator node, named sink, that we assume to be located onboard an unmanned aerial vehicle (UAV). This is a practical example of reachback communication, characterized by the high density of nodes that have to transmit data reliably and efficiently towards a far receiver. It is considered that each node transmits a common shared message directly to the receiver onboard the UAV whenever it receives a broadcast message (triggered for example by the vehicle). We assume that the communication channels between the local nodes and the receiver are subject to fading and noise. The receiver onboard the UAV must be able to fuse the weak and noisy signals in a coherent way to receive the data reliably. It is proposed a cooperative diversity concept as an effective solution to the reachback problem. In particular, it is considered a spread spectrum (SS) transmission scheme in conjunction with a fusion center that can exploit cooperative diversity, without requiring stringent synchronization between nodes. The idea consists of simultaneous transmission of the common message among the nodes and a Rake reception at the fusion center. The proposed solution is mainly motivated by two goals: the necessity to have simple nodes (to this aim we move the computational complexity to the receiver onboard the UAV), and the importance to guarantee high levels of energy efficiency of the network, thus increasing the network lifetime. The proposed scheme is analyzed in order to better understand the effectiveness of the approach presented. The performance metrics considered are both the theoretical limit on the maximum amount of data that can be collected by the receiver, as well as the error probability with a given modulation scheme. Since we deal with a WSN, both of these performance are evaluated taking into consideration the energy efficiency of the network. The second scenario considers the use of a chain network for the detection of fires by using nodes that have a double function of sensors and routers. The first one is relative to the monitoring of a temperature parameter that allows to take a local binary decision of target (fire) absent/present. The second one considers that each node receives a decision made by the previous node of the chain, compares this with that deriving by the observation of the phenomenon, and transmits the final result to the next node. The chain ends at the sink node that transmits the received decision to the user. In this network the goals are to limit throughput in each sensor-to-sensor link and minimize probability of error at the last stage of the chain. This is a typical scenario of distributed detection. To obtain good performance it is necessary to define some fusion rules for each node to summarize local observations and decisions of the previous nodes, to get a final decision that it is transmitted to the next node. WSNs have been studied also under a practical point of view, describing both the main characteristics of IEEE802:15:4 standard and two commercial WSN platforms. By using a commercial WSN platform it is realized an agricultural application that has been tested in a six months on-field experimentation.

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With the business environments no longer confined to geographical borders, the new wave of digital technologies has given organizations an enormous opportunity to bring together their distributed workforce and develop the ability to work together despite being apart (Prasad & Akhilesh, 2002). resupposing creativity to be a social process, the way that this phenomenon occurs when the configuration of the team is substantially modified will be questioned. Very little is known about the impact of interpersonal relationships in the creativity (Kurtzberg & Amabile, 2001). In order to analyse the ways in which the creative process may be developed, we ought to be taken into consideration the fact that participants are dealing with a quite an atypical situation. Firstly, in these cases socialization takes place amongst individuals belonging to a geographically dispersed workplace, where interpersonal relationships are mediated by the computer, and where trust must be developed among persons who have never met one another. Participants not only have multiple addresses and locations, but above all different nationalities, and different cultures, attitudes, thoughts, and working patterns, and languages. Therefore, the central research question of this thesis is as follows: “How does the creative process unfold in globally distributed teams?” With a qualitative approach, we used the case study of the Business Unit of Volvo 3P, an arm of Volvo Group. Throughout this research, we interviewed seven teams engaged in the development of a new product in the chassis and cab areas, for the brands Volvo and Renault Trucks, teams that were geographically distributed in Brazil, Sweden, France and India. Our research suggests that corporate values, alongside with intrinsic motivation and task which lay down the necessary foundations for the development of the creative process in GDT.

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Beamforming entails joint processing of multiple signals received or transmitted by an array of antennas. This thesis addresses the implementation of beamforming in two distinct systems, namely a distributed network of independent sensors, and a broad-band multi-beam satellite network. With the rising popularity of wireless sensors, scientists are taking advantage of the flexibility of these devices, which come with very low implementation costs. Simplicity, however, is intertwined with scarce power resources, which must be carefully rationed to ensure successful measurement campaigns throughout the whole duration of the application. In this scenario, distributed beamforming is a cooperative communication technique, which allows nodes in the network to emulate a virtual antenna array seeking power gains in the order of the size of the network itself, when required to deliver a common message signal to the receiver. To achieve a desired beamforming configuration, however, all nodes in the network must agree upon the same phase reference, which is challenging in a distributed set-up where all devices are independent. The first part of this thesis presents new algorithms for phase alignment, which prove to be more energy efficient than existing solutions. With the ever-growing demand for broad-band connectivity, satellite systems have the great potential to guarantee service where terrestrial systems can not penetrate. In order to satisfy the constantly increasing demand for throughput, satellites are equipped with multi-fed reflector antennas to resolve spatially separated signals. However, incrementing the number of feeds on the payload corresponds to burdening the link between the satellite and the gateway with an extensive amount of signaling, and to possibly calling for much more expensive multiple-gateway infrastructures. This thesis focuses on an on-board non-adaptive signal processing scheme denoted as Coarse Beamforming, whose objective is to reduce the communication load on the link between the ground station and space segment.

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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.

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The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.

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Modern software systems, in particular distributed ones, are everywhere around us and are at the basis of our everyday activities. Hence, guaranteeing their cor- rectness, consistency and safety is of paramount importance. Their complexity makes the verification of such properties a very challenging task. It is natural to expect that these systems are reliable and above all usable. i) In order to be reliable, compositional models of software systems need to account for consistent dynamic reconfiguration, i.e., changing at runtime the communication patterns of a program. ii) In order to be useful, compositional models of software systems need to account for interaction, which can be seen as communication patterns among components which collaborate together to achieve a common task. The aim of the Ph.D. was to develop powerful techniques based on formal methods for the verification of correctness, consistency and safety properties related to dynamic reconfiguration and communication in complex distributed systems. In particular, static analysis techniques based on types and type systems appeared to be an adequate methodology, considering their success in guaranteeing not only basic safety properties, but also more sophisticated ones like, deadlock or livelock freedom in a concurrent setting. The main contributions of this dissertation are twofold. i) On the components side: we design types and a type system for a concurrent object-oriented calculus to statically ensure consistency of dynamic reconfigurations related to modifications of communication patterns in a program during execution time. ii) On the communication side: we study advanced safety properties related to communication in complex distributed systems like deadlock-freedom, livelock- freedom and progress. Most importantly, we exploit an encoding of types and terms of a typical distributed language, session π-calculus, into the standard typed π- calculus, in order to understand their expressive power.

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A Smart City is a high-performance urban context, where citizens live independently and are more aware of the surrounding opportunities, thanks to forward-looking development of economy politics, governance, mobility and environment. ICT infrastructures play a key-role in this new research field being also a mean for society to allow new ideas to prosper and new, more efficient approaches to be developed. The aim of this work is to research and develop novel solutions, here called smart services, in order to solve several upcoming problems and known issues in urban areas and more in general in the modern society context. A specific focus is posed on smart governance and on privacy issues which have been arisen in the cellular age.

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The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition. The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support. We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers.

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Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

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The advent of Bitcoin suggested a disintermediated economy in which Internet users can take part directly. The conceptual disruption brought about by this Internet of Money (IoM) mirrors the cross-industry impacts of blockchain and distributed ledger technologies (DLTs). While related instances of non-centralisation thwart regulatory efforts to establish accountability, in the financial domain further challenges arise from the presence in the IoM of two seemingly opposing traits: anonymity and transparency. Indeed, DLTs are often described as architecturally transparent, but the perceived level of anonymity of cryptocurrency transfers fuels fears of illicit exploitation. This is a primary concern for the framework to prevent money laundering and the financing of terrorism and proliferation (AML/CFT/CPF), and a top priority both globally and at the EU level. Nevertheless, the anonymous and transparent features of the IoM are far from clear-cut, and the same is true for its levels of disintermediation and non-centralisation. Almost fifteen years after the first Bitcoin transaction, the IoM today comprises a diverse set of socio-technical ecosystems. Building on an analysis of their phenomenology, this dissertation shows how there is more to their traits of anonymity and transparency than it may seem, and how these features range across a spectrum of combinations and degrees. In this context, trade-offs can be evaluated by referring to techno-legal benchmarks, established through socio-technical assessments grounded on teleological interpretation. Against this backdrop, this work provides framework-level recommendations for the EU to respond to the twofold nature of the IoM legitimately and effectively. The methodology cherishes the mutual interaction between regulation and technology when drafting regulation whose compliance can be eased by design. This approach mitigates the risk of overfitting in a fast-changing environment, while acknowledging specificities in compliance with the risk-based approach that sits at the core of the AML/CFT/CPF regime.