11 research outputs found

    Network Service Availability and Continuity Management in the Context of Network Function Virtualization

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    In legacy computer systems, network functions (e.g., routers, firewalls, etc.) have been provided by specialized hardware appliances to realize Network Services (NS). In recent years, the rise of Network Function Virtualization (NFV) has changed how we realize NSs. With NFV, commercial off-the-shelf hardware and virtualization technologies are used to create Virtual Network Functions (VNF). In the context of NFV, an NS is realized by interconnecting VNFs using Virtual Links (VL). Service availability and continuity are among the important non-functional characteristics of NSs. Availability is defined as the fraction of time the NS functionality is provided in a period. Current work on NS availability, in the NFV context, focuses on determining the appropriate number of redundant VNFs and their deployment in the virtualized environment, and the redundancy of network paths. Such solutions are necessary but insufficient because redundancy does not guarantee that the overall service outage time for an NS functionality remains below a certain threshold. Moreover, service disruption which impacts the service continuity is not addressed in the current work quantitatively. In addition, NSs and VNFs elasticity and the dynamicity of virtualized infrastructures which can impact the availability of NS functionalities, are not considered in the current state of the art. In this thesis, we propose a framework for NS availability and continuity management, which consists of two approaches, one for design time and another for runtime adaptation. For this, we define service disruption time for an NS functionality as the amount of time for which the service data is lost due to service outages for a given period. We also define the service data disruption for an NS functionality as the maximum amount of data lost due to a service outage. The design-time approach includes analytical methods which take acceptable service disruption and availability requirements of the tenant, a designed NS, and a given infrastructure as inputs to adjust the NS design and map these requirements to constraints on low-level configuration parameters. Design-time approach guarantees the service availability and continuity requirements will be met as long as the availability characteristics of the infrastructure resources used by the NS constituents do not change at runtime. However, changes in the supporting infrastructure may happen at runtime due to multiple reasons like failover, upgrades, and aging. Therefore, we propose a runtime adaptation approach that reacts to changes at runtime and adjusts the configuration parameters accordingly to satisfy the same service availability and continuity requirements. The runtime approach uses machine learning models, which are created at design time, to determine the required adjustments at runtime. To demonstrate the feasibility of the proposed solutions and to experiment with them, we present a proof of concept, including prototypes of our approaches and their application in a small NFV cloud environment created for validation purposes. We conduct multiple experiments for two case studies with different service availability and continuity requirements. The results from the conducted experiments show that our approaches can guarantee the fulfillment of the service availability and continuity requirements

    Actas del XXIV Workshop de Investigadores en Ciencias de la Computación: WICC 2022

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    Compilación de las ponencias presentadas en el XXIV Workshop de Investigadores en Ciencias de la Computación (WICC), llevado a cabo en Mendoza en abril de 2022.Red de Universidades con Carreras en Informátic

    XXIII Edición del Workshop de Investigadores en Ciencias de la Computación : Libro de actas

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    Compilación de las ponencias presentadas en el XXIII Workshop de Investigadores en Ciencias de la Computación (WICC), llevado a cabo en Chilecito (La Rioja) en abril de 2021.Red de Universidades con Carreras en Informátic

    Addressing training data sparsity and interpretability challenges in AI based cellular networks

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    To meet the diverse and stringent communication requirements for emerging networks use cases, zero-touch arti cial intelligence (AI) based deep automation in cellular networks is envisioned. However, the full potential of AI in cellular networks remains hindered by two key challenges: (i) training data is not as freely available in cellular networks as in other fields where AI has made a profound impact and (ii) current AI models tend to have black box behavior making operators reluctant to entrust the operation of multibillion mission critical networks to a black box AI engine, which allow little insights and discovery of relationships between the configuration and optimization parameters and key performance indicators. This dissertation systematically addresses and proposes solutions to these two key problems faced by emerging networks. A framework towards addressing the training data sparsity challenge in cellular networks is developed, that can assist network operators and researchers in choosing the optimal data enrichment technique for different network scenarios, based on the available information. The framework encompasses classical interpolation techniques, like inverse distance weighted and kriging to more advanced ML-based methods, like transfer learning and generative adversarial networks, several new techniques, such as matrix completion theory and leveraging different types of network geometries, and simulators and testbeds, among others. The proposed framework will lead to more accurate ML models, that rely on sufficient amount of representative training data. Moreover, solutions are proposed to address the data sparsity challenge specifically in Minimization of drive test (MDT) based automation approaches. MDT allows coverage to be estimated at the base station by exploiting measurement reports gathered by the user equipment without the need for drive tests. Thus, MDT is a key enabling feature for data and artificial intelligence driven autonomous operation and optimization in current and emerging cellular networks. However, to date, the utility of MDT feature remains thwarted by issues such as sparsity of user reports and user positioning inaccuracy. For the first time, this dissertation reveals the existence of an optimal bin width for coverage estimation in the presence of inaccurate user positioning, scarcity of user reports and quantization error. The presented framework can enable network operators to configure the bin size for given positioning accuracy and user density that results in the most accurate MDT based coverage estimation. The lack of interpretability in AI-enabled networks is addressed by proposing a first of its kind novel neural network architecture leveraging analytical modeling, domain knowledge, big data and machine learning to turn black box machine learning models into more interpretable models. The proposed approach combines analytical modeling and domain knowledge to custom design machine learning models with the aim of moving towards interpretable machine learning models, that not only require a lesser training time, but can also deal with issues such as sparsity of training data and determination of model hyperparameters. The approach is tested using both simulated data and real data and results show that the proposed approach outperforms existing mathematical models, while also remaining interpretable when compared with black-box ML models. Thus, the proposed approach can be used to derive better mathematical models of complex systems. The findings from this dissertation can help solve the challenges in emerging AI-based cellular networks and thus aid in their design, operation and optimization

    A Light Signalling Approach to Node Grouping for Massive MIMO IoT Networks

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    Massive MIMO is a promising technology to connect very large numbers of energy constrained nodes, as it offers both extensive spatial multiplexing and large array gain. A challenge resides in partitioning the many nodes in groups that can communicate simultaneously such that the mutual interference is minimized. We here propose node partitioning strategies that do not require full channel state information, but rather are based on nodes' respective directional channel properties. In our considered scenarios, these typically have a time constant that is far larger than the coherence time of the channel. We developed both an optimal and an approximation algorithm to partition users based on directional channel properties, and evaluated them numerically. Our results show that both algorithms, despite using only these directional channel properties, achieve similar performance in terms of the minimum signal-to-interference-plus-noise ratio for any user, compared with a reference method using full channel knowledge. In particular, we demonstrate that grouping nodes with related directional properties is to be avoided. We hence realise a simple partitioning method requiring minimal information to be collected from the nodes, and where this information typically remains stable over a long term, thus promoting their autonomy and energy efficiency

    IoT & environmental analytical chemistry: Towards a profitable symbiosis

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    [EN] In a constantly evolving world, where the rising population and increased social awareness have led to a higher concern for the environment, research in this field (most notably in Environmental Analytical Chemistry) should take advantage of the great opportunities offered by new technologies such as Internet of Things (IoT) and Cloud-based services. Both of them are especially suitable when chemical sensors and related devices are used in the continuous in-line monitoring of environmental parameters. In this sense, it is very important to obtain spatially distributed information of these parameters as well as their temporal evolution. In this work, a friendly approach to IoT world for environmental applications is carried out. To get a global vision of these concepts, the starting point is their historical evolution. New trends are also identified along with associated challenges and potential threats. Furthermore, not only there will be (in the near future) a need to rely on distributed analytical sensors but also on even more complex, lab-based techniques that are connected to the IoT through appropriate mechanisms. A revision of the recent literature relating IoT with environmental issues has also been performed, the most relevant contributions being discussed. Finally, the need of a mutual cooperation between IoT and Environmental Analytical Chemistry is outlined and commented in detail. Ignoring the new capabilities offered by Cloud computing and IoT environments is no further an option. In this sense, the main contribution of this paper consists of highlighting the fact that the wiser course is to embrace these opportunities consciously for mutual profit.Capella Hernández, JV.; Bonastre Pina, AM.; Campelo Rivadulla, JC.; Ors Carot, R.; Peris Tortajada, M. (2020). IoT & environmental analytical chemistry: Towards a profitable symbiosis. Trends in Environmental Analytical Chemistry. 27:1-8. https://doi.org/10.1016/j.teac.2020.e00095S182

    Routing Protocols Evaluation Review in Simple and Cloud Environment

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    In the field of information technology there are many computer jargons like cloud computing Ad-hoc, Software Define Network (SDN), network function virtualization (NFV) , and virtual machine (VM), etc. This review paper is basically a blend of brief study and review of many routing protocols used for Mobile ad hoc Networks (MANET) in the cloud as well as in simple network environment i.e. without cloud computing. This paper would also suggest the different challenges that are facing in cloud computing. The description of the different network simulators used in networking like NS2 tool, Opnet and Cisco packet tracer. The different metrics that are used in the networking are briefly explained. MANET is a group of wireless nodes that do not need centralized controlling entity as it rapidly moveschanges and forms networks to the nearest networking nodes

    Quality of experience characterization and provisioning in mobile cellular networks

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    Παραδοσιακά, οι προηγούμενες γενεές κινητών κυψελωτών δικτύων έχουν σχεδιαστεί με κριτήρια Ποιότητας Υπηρεσίας, έτσι ώστε να πληρούν συγκεκριμένες απαιτήσεις διαφόρων υπηρεσιών. Η «Ποιότητα Εμπειρίας» έχει, ωστόσο, πρόσφατα εμφανιστεί ως έννοια, επηρεάζοντας το σχεδιασμό των μελλοντικών γενεών των δικτύων, δίνοντας σαφή έμφαση στην πραγματικά επιτευχθείσα εμπειρία του τελικού χρήστη. Η εμφάνιση της έννοιας της Ποιότητας Εμπειρίας οφείλεται στην αναπόφευκτη, ισχυρή μετάβαση που βιώνει η βιομηχανία των Τηλεπικοινωνιών από συστημο-κεντρικά δίκτυα σε πιο χρηστο-κεντρικές λύσεις και στόχους. Οι πάροχοι κινητών δικτύων, οι πάροχοι υπηρεσιών, οι προγραμματιστές εφαρμογών, αλλά και άλλα ενδιαφερόμενα μέλη που εμπλέκονται στην αλυσίδα παροχής υπηρεσιών προσελκύονται από τις ευκαιρίες που μπορεί να προσφέρει η ενσωμάτωση γνώσης Ποιότητας Εμπειρίας στο επιχειρηματικό τους μοντέλο. Πράγματι, η παρεχόμενη Ποιότητα Εμπειρίας αποτελεί έναν καθοριστικό παράγοντα διαφοροποίησης μεταξύ των διαφόρων παικτών, μία τάση που αναμένεται να γίνει ακόμη πιο έντονη τα επόμενα χρόνια. Υποκινούμενη από αυτή την χρηστο-κεντρική τάση, η έρευνα που διεξάγεται σε αυτή τη διατριβή έχει ως στόχο την διερεύνηση των προκλήσεων και των ευκαιριών που προκύπτουν στα σύγχρονα κινητά κυψελωτά δίκτυα όταν λαμβάνεται υπόψιν η έννοια της Ποιότητας Εμπειρίας. Τέτοιες ευκαιρίες αφορούν, καταρχήν, τη δυνατότητα κατανόησης της Ποιότητας Εμπειρίας που επιτυγχάνει ένας πάροχος κατά την προσφορά μίας υπηρεσίας. Αυτό μπορεί να επιτευχθεί με την υλοποίηση και ενσωμάτωση μεθόδων αξιολόγησης Ποιότητας Εμπειρίας στην πραγματικού-χρόνου λειτουργία ενός δικτύου. Εν συνεχεία, ακολουθεί η εκμετάλλευση της συλλεγμένης ευφυΐας που σχετίζεται με την Ποιότητα Εμπειρίας, προκειμένου να επανεξεταστούν υφιστάμενοι μηχανισμοί επιπέδου δικτύου (π.χ., χρονο-προγραμματισμός ραδιοπόρων) ή μηχανισμοί επιπέδου εφαρμογής (π.χ., ροή βίντεο), αλλά και να προταθούν καινοτόμες διαστρωματικές προσεγγίσεις προς όφελος της Ποιότητας Εμπειρίας. Επιπλέον, υπάρχει η δυνατότητα πρότασης νέων αλγορίθμων που προκύπτουν από τα εγγενή χαρακτηριστικά της Ποιότητας Εμπειρίας, όπως η μη γραμμική επίδραση μετρικών Ποιότητας Υπηρεσίας στην Ποιότητα Εμπειρίας, με στόχο την περαιτέρω βελτίωσή της. Σε αυτή την κατεύθυνση, στην παρούσα διατριβή, διερευνώνται και αξιοποιούνται μοντέλα και μετρικές εκτίμησης Ποιότητας Εμπειρίας με στόχο την ποσοτικοποίησή της, έχοντας ως απώτερο στόχο την εισαγωγή βελτιώσεων στους υφιστάμενους μηχανισμούς κινητών κυψελωτών δικτύων. Ο πυρήνας αυτής της διατριβής είναι η πρόταση μίας κυκλικής διεργασίας παροχής Ποιότητας Εμπειρίας που επιτρέπει τον έλεγχο, την παρακολούθηση (ήτοι, τη μοντελοποίηση) και τη διαχείριση της Ποιότητας Εμπειρίας σε ένα κυψελωτό δίκτυο. Κάθε μία από αυτές τις λειτουργίες αναλύεται περαιτέρω, ενώ έμφαση δίνεται στις λειτουργίες μοντελοποίησης και διαχείρισης. Όσον αφορά τη μοντελοποίηση, γίνεται περιγραφή και ταξινόμηση των μεθόδων εκτίμησης και των δεικτών επιδόσεων Ποιότητας Εμπειρίας. Η παραμετρική εκτίμηση της ποιότητας αναδεικνύεται ως η πιο ελκυστική κατηγορία μοντελοποίησης Ποιότητας Εμπειρίας σε κινητά κυψελωτά δίκτυα, οπότε και περιγράφεται διεξοδικά για ευρέως χρησιμοποιούμενους τύπους υπηρεσιών, όπως η συνομιλία (φωνή) μέσω Internet Protocol (IP) και η μετάδοση βίντεο. Όσον αφορά τη διαχείριση Ποιότητας Εμπειρίας, προτείνονται νέοι μηχανισμοί που επιδεικνύουν βελτιώσεις στην εμπειρία των τελικών χρηστών, και συγκεκριμένα: α) ένα σχήμα ελέγχου των επικοινωνιών συσκευής-προς-συσκευή που λαμβάνει υπόψιν την εμπειρία των χρηστών, β) ένας «συνεπής» αλγόριθμος χρονο-προγραμματισμού ραδιοπόρων που βελτιώνει την Ποιότητα Εμπειρίας του χρήστη μετριάζοντας τις διακυμάνσεις της ρυθμαπόδοσης του δικτύου, και γ) ένας μηχανισμός προσαρμοστικής ροής βίντεο με γνώσεις «πλαισίου», ο οποίος επιτυγχάνει την εξάλειψη διακοπών του βίντεο σε συνθήκες χαμηλού εύρους ζώνης. Επιπλέον, προτείνεται μία εφαρμογή Ποιότητας Εμπειρίας βασισμένη στην αρχιτεκτονική Software-Defined Networking (SDN), ονόματι “QoE-SDN APP”, η οποία επιτρέπει την ανάδραση πληροφοριών δικτύου από παρόχους κινητής τηλεφωνίας σε παρόχους υπηρεσιών βίντεο, αναδεικνύοντας πλεονεκτήματα ως προς την Ποιότητα Εμπειρίας για τους πελάτες των παρόχων βίντεο αλλά και ως προς την εξοικονόμηση εύρους ζώνης για τους φορείς εκμετάλλευσης δικτύου. Εν κατακλείδι, η παρούσα διατριβή προωθεί την ενοποίηση του ερευνητικού πεδίου της Ποιότητας Εμπειρίας με τον τομέα των κινητών επικοινωνιών, καθώς και τη συνεργασία αμοιβαίου ενδιαφέροντος μεταξύ των παρόχων δικτύου (επίπεδο δικτύου) με τους παρόχους υπηρεσιών (επίπεδο εφαρμογής), αναδεικνύοντας την δυναμική από τέτοιου είδους προσεγγίσεις για όλους τους εμπλεκόμενους φορείς.Traditionally, previous generations of mobile cellular networks have been designed with Quality of Service (QoS) criteria in mind, so that they manage to meet specific service requirements. Quality of Experience (QoE) has, however, recently emerged as a concept, disrupting the design of future network generations by giving clear emphasis on the actually achieved user experience. The emergence of the QoE concept has been a result of the inevitable strong transition that the Telecom industry is currently experiencing from system-centric networks to more user-centric solutions and objectives. Mobile network operators, service providers, application developers, as well as other stakeholders involved in the service provisioning chain have been attracted by the opportunities that the integration of the QoE concept could bring to their business; indeed, the provisioned QoE constitutes a determining factor of differentiation among different stakeholders, a tendency which is expected to become even more intense in the years to come. Motivated by this boost towards user-centricity, the objective of the research conducted in this thesis is to explore the challenges and opportunities that arise in modern mobile cellular networks when QoE is considered. Such opportunities concern, first of all, the possibility to comprehend the QoE that a provider achieves when provisioning a service. This can be enabled by the implementation and integration of QoE assessment methods into the real-time operation of a network. Then, the next step is the exploitation of collected QoE-related intelligence in order to re-examine existing network-layer mechanisms (e.g., radio scheduling), or application-layer mechanisms (e.g., video streaming), as well as propose novel cross-layer approaches towards ameliorating the achieved QoE. Moreover, the opportunity emerges to propose novel algorithms that stem from the inherent idiosyncrasies of QoE, such as the non-linear impact of QoS-related parameters on QoE, as a way to further enhance the users’ QoE. In this direction, throughout this thesis, QoE estimation models and metrics are explored and exploited in order to quantify QoE and thus, to improve existing mechanisms of mobile cellular networks. The core of this thesis is the proposal of a QoE provisioning cycle that allows the control, monitoring (i.e., modeling) and management of QoE in a cellular network. Each one of these functions is further analyzed, while emphasis is given on the modeling and management operations. In terms of modeling, QoE assessment methods and QoE-related performance indicators are described and classified. Parametric quality estimation is identified as the most appealing type of QoE estimation in mobile cellular networks, thus, it is thoroughly described for widely used types of services, such as Voice over IP (VoIP) and video streaming. In terms of QoE management, novel QoE-aware mechanisms that demonstrate QoE improvements for the users are proposed, namely: a) a QoE-driven Device-to-Device (D2D) communication management scheme that enhances end-user QoE, b) a “consistent” radio scheduling algorithm that improves the end-user QoE by mitigating throughput fluctuations, and c) a context-aware HTTP Adaptive Streaming (HAS) mechanism that successfully mitigates stallings (i.e., video freezing events) in the context of bandwidth-challenging scenarios. Moreover, a programmable QoE-SDN APP into the Software-Defined Networking (SDN) architecture is introduced, which enables network feedback exposure from mobile network operators to video service providers, revealing QoE benefits for the customers of video providers and bandwidth savings for the network operators. Overall, this thesis promotes the uniting of the domain of QoE with the domain of mobile communications, as well as the collaboration of mutual-interest between mobile network operators (network layer) and service providers (application layer), presenting the high potential from such approaches for all involved stakeholders

    Mechanisms for service-oriented resource allocation in IoT

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    Albeit several IoT applications have been recently deployed in several fields, including environment and industry monitoring, Smart Home, Smart Hospital and Smart Agriculture, current deployments are mostly host-oriented, which is undoubtedly limiting the attained benefits brought up by IoT. Indeed, future IoT applications shall benefit from service-oriented communications, where the communication establishment between end-points is not dependent on prior knowledge of the host devices in charge of providing the service execution. Rather, an end-user service execution request is mapped into the most suitable resources able to provide the requested service. Furthermore, this model is a key enabler for the design of future services in Smart Cities, e-Health, Intelligent Transportation Systems, among other smart scenarios. Recognized the benefits of this model in future applications, considerable research effort must be devoted for addressing several challenges yet unsolved, such as the ones brought up by the high dynamicity and heterogeneity inherent to these scenarios. In fact, service-oriented communication requires an updated view of available resources, mapping service requests into the most suitable resources taking several constraints and requirements into account, resilience provisioning, QoS-aware service allocation, just to name a few. This thesis aims at proposing and evaluating mechanisms for efficient resource allocation in service-oriented IoT scenarios through the employment of two distinct baseline technologies. In the first approach, the so-called Path Computation Element (PCE), designed to decouple the host-oriented routing function from GMPLS switches in a centralized element, is extended to the service-oriented PCE (S-PCE) architecture, where a service identifier (SID) is used to identify the service required by an end-user. In this approach, the service request is mapped to one or a set of resources by a 2-steps mapping scheme that enables both selection of suitable resources according to request and resources characteristics, and avoidance of service disruption due to possible changes on resources¿ location. In the meantime, the inception of fog computing, as an extension of the cloud computing concept, leveraging idle computing resources at the edge of the network through their organization as highly virtualized micro data centers (MDC) enabled the reduction on the network latency observed by services launched at edge devices, further reducing the traffic at the core network and the energy consumption by network and cloud data center equipment, besides other benefits. Envisioning the benefits of the distributed and coordinated employment of both fog and cloud resources, the Fog-to-Cloud (F2C) architecture has been recently proposed, further empowering the distributed allocation of services into the most suitable resources, be it in cloud, fog or both. Since future IoT applications shall present strict demands that may be satisfied through a combined fog-cloud solution, aligned to the F2C architecture, the second approach for the service-oriented resource allocation, considered in this thesis, aims at providing QoS-aware resource allocation through the deployment of a hierarchical F2C topology, where resource are logically distributed into layers providing distinct characteristics in terms of network latency, disruption probability, IT power, etc. Therefore, distinct strategies for service distribution in F2C architectures, taking into consideration features such as service transmission delay, energy consumption and network load. Concerning the need for failure recovery mechanisms, distinct demands of heterogeneous services are considered in order to assess distinct strategies for allocation of protection resources in the F2C hierarchy. In addition, the impact of the layered control topology on the efficient allocation of resources in F2C is further evaluated. Finally, avenues for future work are presented.Aunque son ya varias las aplicaciones que se han desarrollado en el área de IoT, especialmente en el campo ambiental, Smart Home o Smart Health, las implementaciones actuales son en su mayoría ¿host-oriented¿, lo que sin duda limita sus potenciales beneficios. Una posible estrategia para reducir esos efectos negativos se centra en que las futuras aplicaciones se beneficien de las comunicaciones orientadas a servicios, ¿service-oriented¿, donde el establecimiento de comunicación entre puntos finales no depende del conocimiento previo de los hosts a cargo de proporcionar la ejecución del servicio. En este escenario, una solicitud de ejecución de servicio se asigna a los recursos más adecuados capaces de proporcionar el servicio solicitado. Este modelo se considera clave para el despliegue de futuros servicios en Smart Cities, e-Health, Intelligent Transportation Systems, etc. Reconocidos los beneficios de este modelo en las aplicaciones futuras, un substancial esfuerzo de investigación es necesario para abordar varios desafíos aún no resueltos, como los surgidos por la alta dinámica y heterogeneidad inherente a estos escenarios. De hecho, la comunicación service-oriented requiere una vista actualizada de los recursos disponibles, así como la asignación de solicitudes de servicio en los recursos más adecuados teniendo en cuenta varias restricciones y requisitos. Esta tesis tiene como objetivo proponer y evaluar mecanismos para la asignación eficiente de recursos en escenarios IoT orientados a servicios a través del empleo de dos tecnologías básicas distintas. En el primer enfoque, el llamado Path Computation Element (PCE), diseñado para desacoplar la función de enrutamiento de los conmutadores GMPLS hacia un elemento centralizado, se extiende generando la arquitectura service-oriented PCE (S-PCE). En S-PCE se utiliza un identificador de servicio (SID) para identificar el servicio requerido por un usuario final, y la solicitud se asigna, bien a uno o bien a un conjunto de recursos, mediante un esquema de asignación de 2 pasos que permite la selección de los recursos adecuados, evitando la interrupción del servicio debido a posibles cambios en la ubicación de los recursos. Mientras tanto, el inicio de Fog computing, como una extensión de Cloud computing, basado conceptualmente en aprovechar la infraestructura y los recursos inactivos en el extremo de la red a través de su organización como micro data centers (MDC), ha supuesto la reducción de la latencia de la red para los servicios lanzados por dispositivos localizados en el extremo de la red, reduciendo el tráfico en el centro de la red (backbone) así como el consumo de energía, además de otros beneficios. Asumiendo las ventajas de la utilización distribuida y coordinada de los recursos fog y cloud, la arquitectura Fog-to-Cloud (F2C) ha sido recientemente propuesta, destinada a potenciar la asignación distribuida de servicios en los recursos más adecuados, sea en cloud, fog o ambos. Dado que las futuras aplicaciones IoT deben presentar demandas que podrían ser satisfechas a través de una solución alineada con la arquitectura F2C, el segundo enfoque para la asignación de recurso orientado a servicio, considerado en esta tesis, tiene como objetivo proporcionar una asignación de recursos mediante el despliegue de una topología F2C, donde los recursos se distribuyen lógicamente en capas que proporcionan características distintas en términos de latencia de red, probabilidad de interrupción, etc. Así, se proponen distintas estrategias para la distribución de servicios, teniendo en cuenta características tales como QoS y consumo de energía. Con respecto a la necesidad de mecanismos de recuperación de fallos, se evalúan distintas estrategias para la asignación de recursos de protección en la jerarquía F2C. Además, se evalúa el impacto de la topología de control en capas sobre la asignación eficiente de recursos en F2C. Finalmente, las sugerencias para trabajos futuros son presentadas
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