Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed

Optimizing the beacon exchange rate for proactive autonomic configuration in ubiquitous MANETs

Proactive self-configuration is indispensable for MANETs like ubiquitous sensor networks (USNs), as component devices of the network are usually exposed to natural or man-made disasters due to the hostile deployment and ad hoc nature of the USNs. Network state beacons (NSBs) are exchanged among the key nodes of the network for crucial and effective monitoring of the network for steady state operation. The rate of beacon exchange (F/sub E/) and its contents, define the time and nature of the proactive action. Therefore it is very important to optimize these parameters to tune the functional response of the USN. This paper presents a comprehensive model for monitoring and proactively reconfiguring the network by optimizing the F/sub E/. The results confirm the improved throughput while maintaining QoS over longer periods of network operation

Qualité de service dans l'IOT : couche de brouillard

Abstract : The Internet of Things (IoT) can be defined as a combination of push and pull from the technological side and human side respectively. This push and pull effect results in more connectivity among objects and humans in the near surrounding environments [1]. With the growth in the field of IoT, in recent times, the risk of real time failures has increased as well. The failures are often detected by certain points of vulnerability in the system. Narrowing down to the root causes we get the point of failures and that leads to the required measures to overcome them. This creates the need for IoT systems to have a proper Quality of Service (QoS) architecture. Thus, QoS is becoming a crucial issue with the democratization of IoT. QoS is the description or measurement of the overall performance of a service, such as a telephony or computer network or a cloud computing service, particularly the performance seen by the users of the network. In this study, we propose the methods of enforcement of QoS in IoT platforms. We will highlight the challenges and recurrent issues faced by all IoT platforms which in turn inspired us to build a generic tool to overcome these challenges by enforcing the QoS in all the IoT platforms with an easy to use set up. The main focus of this study is to enable QoS features in the Fog layer of the IoT architecture. Existing platforms and systems enabling QoS features in the Fog layer are also highlighted. Finally, we validate our proposed model by implementing it on our AMI-LAB platform.L'Internet des objets (IdO) (Internet of Things en anglais), peut être défini comme une combinaison d’interactions entre les Humains et le monde technologique de l’Internet. De cet effet résulte une interconnexion entre les objets physiques et les appareils technologiques dans leur environnement proche. Ces dernières années le domaine de l'IdO s’est beaucoup développé, entrainant ainsi une augmentation du risque de défaillances en temps réel. Les défaillances sont souvent détectées par certains points de vulnérabilité dans le système. En se concentrant sur les causes profondes, le point de défaillance peut être détecter, ce qui conduit aux mesures à mettre en place pour surmonter les défaillances. Les systèmes IdO ont donc besoin d'avoir une architecture de Qualité de Service (QdS) adéquate. Ainsi, la QdS devient un enjeu crucial avec la démocratisation de l'IdO. La QdS est la description ou la mesure de la performance globale d'un service, tel qu'un réseau de téléphonie ou informatique, ou un service de cloud computing, en particulier la performance perçue par les utilisateurs du réseau. Dans cette étude, nous proposons les méthodes de mise en œuvre de la QdS dans les plateformes IdO. Nous mettrons en lumière les défis et les problèmes récurrents rencontrés par toutes les plateformes IdO, qui nous ont inspirés à construire un outil générique pour surmonter ces défis en imposant la QdS dans toutes les plateformes IdO avec une configuration facile à utiliser. L'objectif principal de cette étude est de permettre les fonctionnalités de QdS dans la couche Fog de l'architecture IdO. Les plateformes et systèmes existants permettant les fonctionnalités de QdS dans la couche Fog sont également mis en évidence. Enfin, nous soulignons la validation de notre modèle en le mettant en œuvre sur notre plateforme AMI-LAB

Autonomic ubiquitous computing: a home environment management system

Tese de doutoramento em Electrónica Industrial (ramo do conhecimento Informática Industrial)The Ubiquitous Computing and Autonomic Computing reached a point of convergence in which pervasive technology in the environment meets the ability of people to interact with it, making use of all the possibilities made available by this technology. Ubiquitous computing envisions a habitat where the abundance of devices, services and applications allows the physical and virtual worlds to become seamlessly merged. The promise of ubiquitous computing environments is not feasible unless these systems can effectively "disappear". In order to achieve this goal, they need to become autonomic, by managing their own evolution and configuration with minimal user intervention. It is in this context that aspects like self-configuration and self-healing from the autonomic computing concept were adopted in this project. The context awareness and the creation of applications which use that context are the core concern of Ubiquitous Computing Systems and represent the fundamentals for autonomic actions in this type of systems. Such research raises questions on context acquisition, distribution and manipulation, as well as on artificial intelligence algorithms that decide autonomic actions in the environment, having implications in the human interaction with Autonomic Ubiquitous Systems. The research presented in this thesis concentrates on some of those issues. During this project it was developed an experimental setup for context acquisition, in an effortless way, of some activities of a small group of users. This experimental setup was installed in a real home where a young family, a couple and a small child, were actually living. This experimental setup was mainly responsible for the control of the light system of the house, by a network of several inter-connected devices scattered in the home with limited resources. This prototype installation allowed the validation of the system ability, to capture daily life behaviour patterns of the inhabitants. The system architecture was designed based on the concept of a high level and a low level autonomic management system taking from nature the model of the human reflex arc. A reflexive behaviour is managed at a local level by the small devices, with limited resources, high level management is responsible for processing and analysis of the events broadcast by the group of small devices, and run in a centralized mode in a PC. The concept of device information broadcast, to the communication medium, as events was used as an approach to: inter-connect future systems, monitor correct operation of the system devices, capture raw data for estimation of context; allow the visualization of system feedback in user interface devices. Finally, an algorithm using artificial neural networks in combination with simple statistics was developed which allowed the house to learn the routines of its inhabitants, making it truly intelligent by embedding the knowledge about patterns of activities of the users in the devices scattered in the environment, increasing their comfort and, at same time, leading to more energy efficiency. The analysis of the data captured, during two complete years, shows that the reduction of power consumption could be as high as 50%, depending on the profile of the usage of the light.A Computação Ubíqua e a Computação Autónoma atingiram um ponto de convergência no qual a tecnologia dispersa nos ambientes, juntamente com a capacidade das pessoas interagirem, permite tirar partido do seu uso para novas potencialidades. A computação ubíqua vislumbra habitats repletos de dispositivos, serviços e aplicações que permitem a união perfeita do mundo real com o mundo virtual, mas de uma forma natural. A promessa da criação de tais ambientes de computação ubíqua não se tornará possível sem que a complexidade destes sistemas “desapareçam” efectivamente da percepção dos utilizadores. Para que isso seja possível, estes necessitam de ser autónomos, gerindo a sua própria evolução e configuração com o mínimo de intervenção do utilizador. É neste contexto que a noção de Sistemas Ubíquos Autónomos envolvendo as facetas de auto-configuração e auto-reparação derivadas do conceito da computação autónoma, será usada nesta tese. A percepção do contexto e a criação de aplicações que o usam são as principais preocupações na investigação dos Sistemas de Computação Ubíqua, constituindo também a base para as acções autónomas neste tipo de sistemas. Essa investigação levanta questões sobre a forma como o contexto é capturado, distribuído e manipulado. Por outro lado, provoca impacto nos algoritmos de inteligência artificial que efectuam as decisões de acções autónomas no ambiente, afectando consequentemente a interacção humana com os Sistemas Ubíquos Autónomos. A investigação apresentada nesta dissertação concentra-se efectivamente em alguns destes aspectos. Durante a tese foi desenvolvido um sistema experimental com o objectivo de capturar o contexto, de uma forma perceptível, das actividades de um pequeno grupo de utilizadores. Este sistema experimental foi instalado numa casa real, onde vive uma jovem família constituída por uma casal e uma pequena criança. O sistema experimental era responsável por controlar toda a iluminação eléctrica da casa, através de um conjunto de dispositivos, com recursos limitados, conectados em rede e espalhados pela casa. A instalação permitiu validar a capacidade do sistema de capturar os padrões de comportamento quotidiano dos habitantes da casa. A arquitectura do sistema foi projectada baseando-se no conceito de alto-nível e baixo-nivel dos sistemas de gestão autónoma, inspirando-se no modelo dos processos que ocorrem num acto reflexo no corpo humano. As acções de reflexo ou acções básicas são geridas pelo baixo-nivel nos pequenos dispositivos e com recursos limitados, e quanto o gestão de alto-nivel é responsável pelo processamento e analise dos eventos disponíveis no barramento de dados da rede dos pequenos dispositivos. Foi também usado o conceito da difusão (broadcast) da informação, para o barramento de dados, na forma de eventos para permitir: a interligação com sistema futuros, monitorização do correcto funcionamento do sistema, captura da informação para posterior determinação do contexto; e por fim permitir a visualização do estado do sistema na interface com os utilizadores. Por último, foi desenvolvido um algoritmo usando redes neuronais artificiais e em combinação com estatística básica que permite aprender, de uma forma autónoma, as rotinas dos habitantes em casa, conferindo a esta um ambiente inteligente. Desta forma, a casa contém o conhecimento dos padrões quotidianos dos habitantes, aumentando consequentemente o seu conforto e ao mesmo tempo, permitindo melhor eficiência energética. As análises dos dados capturados, durante dois anos completos, mostram que a redução no consumo energético pode chegar os 50%, dependendo do perfil de uso da iluminação.Fundação para a Ciência e a Tecnologia (FCT)Scholarship number SFRH/BD/8290/2004

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Models and Protocols for Resource Optimization in Wireless Mesh Networks

Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

Connectivity Management for HetNets based on the Principles of Autonomicity and Context-Awareness

Στο περιβάλλον του Διαδικτύου του Μέλλοντος, η Πέμπτη γενιά (5G) δικτύων έχει ήδη αρχίσει να καθιερώνεται. Τα δίκτυα 5G αξιοποιούν υψηλότερες συχνότητες παρέχοντας μεγαλύτερο εύρος ζώνης, ενώ υποστηρίζουν εξαιρετικά μεγάλη πυκνότητα σε σταθμούς βάσης και κινητές συσκευές, σχηματίζοντας ένα περιβάλλον ετερογενών δικτύων, το οποίο στοχεύει στο να καλυφθούν οι απαιτήσεις της απόδοσης ως προς την μικρότερη δυνατή συνολική χρονοκαθυστέρηση και κατανάλωση ενέργειας. Η αποδοτική διαχείριση της συνδεσιμότητας σε ένα τόσο ετερογενές δικτυακό περιβάλλον αποτελεί ανοιχτό πρόβλημα, με σκοπό να υποστηρίζεται η κινητικότητα των χρηστών σε δίκτυα διαφορετικών τεχνολογιών και βαθμίδων, αντιμετωπίζοντας θέματα πολυπλοκότητας και διαλειτουργικότητας, υποστηρίζοντας τις απαιτήσεις των τρεχουσών εφαρμογών και των προτιμήσεων των χρηστών και διαχειρίζοντας ταυτόχρονα πολλαπλές δικτυακές διεπαφές. Η συλλογή, η μοντελοποίηση, η διεξαγωγή συμπερασμάτων και η κατανομή πληροφορίας περιεχομένου σε σχέση με δεδομένα αισθητήρων θα παίξουν κρίσιμο ρόλο σε αυτήν την πρόκληση. Με βάση τα παραπάνω, κρίνεται σκόπιμη η αξιοποίηση των αρχών της επίγνωσης περιεχομένου και της αυτονομικότητας, καθώς επιτρέπουν στις δικτυακές οντότητες να είναι ενήμερες του εαυτού τους και του περιβάλλοντός τους, καθώς και να αυτοδιαχειρίζονται τις λειτουργίες τους ώστε να πετυχαίνουν συγκεκριμένους στόχους. Επιπλέον, χρειάζεται ακριβής ποσοτική αξιολόγηση της απόδοσης λύσεων διαχείρισης της συνδεσιμότητας για ετερογενή δίκτυα, οι οποίες παρουσιάζουν διαφορετικές στρατηγικές επίγνωσης περιβάλλοντος, απαιτώντας μια μεθοδολογία που να είναι περιεκτική και γενικά εφαρμόσιμη ώστε να καλύπτει διαφορετικές προσεγγίσεις, καθώς οι υπάρχουσες μεθοδολογίες στην βιβλιογραφία είναι σχετικά περιορισμένες. Tο σύνολο της μελέτης επικεντρώνεται σε δύο θεματικούς άξονες. Στο πρώτο θεματικό μέρος της διατριβής, αναλύεται ο ρόλος της επίγνωσης περιβάλλοντος και της αυτονομικότητας, σε σχέση με την διαχείριση της συνδεσιμότητας, αναπτύσσοντας ένα πλαίσιο ταξινόμησης και κατηγοριοποίησης, επεκτείνοντας την τρέχουσα βιβλιογραφία. Με βάση το προαναφερθέν πλαίσιο, ταξινομήθηκαν και αξιολογήθηκαν λύσεις για την υποστήριξη της κινητικότητας σε ετερογενή δίκτυα, οι οποίες δύνανται να θεωρηθούν ότι παρουσιάζουν επίγνωση περιβάλλοντος και αυτο-διαχειριστικά χαρακτηριστικά. Επιπλέον, μελετήθηκε κατά πόσον οι αποφάσεις που λαμβάνονται ως προς την επιλογή του κατάλληλου δικτύου, σύμφωνα με την κάθε λύση, είναι αποτελεσματικές και προτάθηκαν τρόποι βελτιστοποίησης των υπαρχουσών αρχιτεκτονικών, καθώς και προτάσεων προς περαιτέρω ανάπτυξη σχετικών μελλοντικών λύσεων. Στο δεύτερο θεματικό μέρος της διατριβής, αναπτύχθηκε μια ευέλικτη αναλυτική μεθοδολογία, περιλαμβάνοντας όλους τους παράγοντες που μπορούν να συνεισφέρουν στην συνολική χρονοκαθυστέρηση, λαμβάνοντας υπόψιν την σηματοδοσία, την επεξεργαστική επιβάρυνση και την συμφόρηση (μελέτη ουράς), επεκτείνοντας την τρέχουσα βιβλιογραφία. Η μεθοδολογία είναι περιεκτική, ενώ ταυτόχρονα προσφέρει κλειστού τύπου λύσεις και έχει την δυνατότητα να προσαρμόζεται σε διαφορετικές προσεγγίσεις. Προς απόδειξη αυτού, εφαρμόσαμε την μεθοδολογία σε δύο λύσεις με διαφορετική στρατηγική επίγνωσης περιβάλλοντος (μια μεταδραστική και μια προδραστική). Και για τις δύο προσεγγίσεις, τα αναλυτικά αποτελέσματα επιβεβαιώθηκαν από προσομοιώσεις, επιβεβαιώνοντας την αποτελεσματικότητα και την ακρίβεια της αναλυτικής μεθοδολογίας. Επιπλέον, αποδείχθηκε ότι η προδραστική προσέγγιση εμφανίζει καλύτερη απόδοση ως προς την συνολική χρονοκαθυστέρηση, ενώ χρειάζεται σημαντικά λιγότερους επεξεργαστικούς πόρους, παρουσιάζοντας πιθανά οφέλη και στην συνολική ενεργειακή κατανάλωση και στα λειτουργικά και κεφαλαιουχικά κόστη (OPEX και CAPEX)

Engineering Self-Adaptive Applications on Software Defined Infrastructure

Cloud computing is a flexible platform that offers faster innovation, elastic resources, and economies of scale. However, it is challenging to ensure non-functional properties such as performance, cost and security of applications hosted in cloud. Applications should be adaptive to the fluctuating workload to meet the desired performance goals, in one hand, and on the other, operate in an economic manner to reduce the operational cost. Moreover, cloud applications are attractive target of security threats such as distributed denial of service attacks that target the availability of applications and increase the cost. Given such circumstances, it is vital to engineer applications that are able to self-adapt to such volatile conditions. In this thesis, we investigate techniques and mechanisms to engineer model-based application autonomic management systems that strive to meet performance, cost and security objectives of software systems running in cloud. In addition to using the elasticity feature of cloud, our proposed autonomic management systems employ run-time network adaptations using the emerging software defined networking and network function virtualization. We propose a novel approach to self-protecting applications where the application traffic is dynamically managed between public and private cloud depending on the condition of the traffic. Our management approach is able to adapt the bandwidth rates of application traffic to meet performance and cost objectives. Through run-time performance models as well as optimization, the management system maximizes the profit each time the application requires to adapt. Our autonomous management solutions are implemented and evaluated analytically as well as on multiple public and community clouds to demonstrate their applicability and effectiveness in real world environment