Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Task Allocation among Connected Devices: Requirements, Approaches and Challenges

Task allocation (TA) is essential when deploying application tasks to systems of connected devices with dissimilar and time-varying characteristics. The challenge of an efficient TA is to assign the tasks to the best devices, according to the context and task requirements. The main purpose of this paper is to study the different connotations of the concept of TA efficiency, and the key factors that most impact on it, so that relevant design guidelines can be defined. The paper first analyzes the domains of connected devices where TA has an important role, which brings to this classification: Internet of Things (IoT), Sensor and Actuator Networks (SAN), Multi-Robot Systems (MRS), Mobile Crowdsensing (MCS), and Unmanned Aerial Vehicles (UAV). The paper then demonstrates that the impact of the key factors on the domains actually affects the design choices of the state-of-the-art TA solutions. It results that resource management has most significantly driven the design of TA algorithms in all domains, especially IoT and SAN. The fulfillment of coverage requirements is important for the definition of TA solutions in MCS and UAV. Quality of Information requirements are mostly included in MCS TA strategies, similar to the design of appropriate incentives. The paper also discusses the issues that need to be addressed by future research activities, i.e.: allowing interoperability of platforms in the implementation of TA functionalities; introducing appropriate trust evaluation algorithms; extending the list of tasks performed by objects; designing TA strategies where network service providers have a role in TA functionalities’ provisioning

From serendipity to sustainable Green IoT: technical, industrial and political perspective

Recently, Internet of Things (IoT) has become one of the largest electronics market for hardware production due to its fast evolving application space. However, one of the key challenges for IoT hardware is the energy efficiency as most of IoT devices/objects are expected to run on batteries for months/years without a battery replacement or on harvested energy sources. Widespread use of IoT has also led to a largescale rise in the carbon footprint. In this regard, academia, industry and policy-makers are constantly working towards new energy-efficient hardware and software solutions paving the way for an emerging area referred to as green-IoT. With the direct integration and the evolution of smart communication between physical world and computer-based systems, IoT devices are also expected to reduce the total amount of energy consumption for the Information and Communication Technologies (ICT) sector. However, in order to increase its chance of success and to help at reducing the overall energy consumption and carbon emissions a comprehensive investigation into how to achieve green-IoT is required. In this context, this paper surveys the green perspective of the IoT paradigm and aims to contribute at establishing a global approach for green-IoT environments. A comprehensive approach is presented that focuses not only on the specific solutions but also on the interaction among them, and highlights the precautions/decisions the policy makers need to take. On one side, the ongoing European projects and standardization efforts as well as industry and academia based solutions are presented and on the other side, the challenges, open issues, lessons learned and the role of policymakers towards green-IoT are discussed. The survey shows that due to many existing open issues (e.g., technical considerations, lack of standardization, security and privacy, governance and legislation, etc.) that still need to be addressed, a realistic implementation of a sustainable green-IoT environment that could be universally accepted and deployed, is still missing

Task allocation in the Internet of Things

The last few years have been involved by the technological revolution represented by the Internet of Things (IoT). The IoT vision aims to interconnect devices with different capabilities such as sensors, actuators, Radio Frequency Identification (RFID) tags, smart objects (e.g. smartphones), and servers, within the same heterogeneous network. The aim is to enable the network objects to dynamically cooperate and make their resources available, in order to reach a goal, i.e. the execution of one or more applications assigned to the network. As known since its invention, the Internet interconnects nodes with dissimilar characteristics without central authorities by introducing some simple yet effective protocols that allow for nodes' interoperability so that information is successfully exchanged and services are provided by servers to clients and among peers. Fortunately, the same happens among objects in the IoT so that interoperability is assured and the data sensed by objects distributed and connected to the physical world is now available for the benefit of the human users. The realization of the IoT paradigm relies on the implementation of systems of cooperative intelligent objects with key interoperability capabilities. However, to reach this goal, it's important to consider some key features that characterize many IoT objects: i) available nodes' resources (electrical energy, memory, processing, node capability to perform a given task) are often limited. This is the case, for example, of battery powered nodes, which have limited energy amounts. ii) sensors may provide information that is not unique but can be generated by set of different objects which for example are capable to sense the same physical measure of the same geographical. iii) the number of nodes in the IoT is quickly overcoming the number of hosts in the 'traditional' Internet and most of these have a low reliability due mostly to the mobility and energy. This entails for a new paradigm of communication according to which objects coordinate with the other objects in groups and provide a unified service to the external world (the application that requires the service), with the intent to distribute the load of the requested services according to specific community defined rules, which could be: lifetime extension, QoS (Quality of Service) maximization, reward maximization, or others. It is evident that an appropriate coordination of objects' resources utilization would consistently improve their performance. This foreword is necessary to introduce this thesis, which is defined as follows. Task allocation in the IoT: given the IoT paradigm and the requirements of IoT applications, the nodes involved in the execution of the same application should cooperate to reach the optimal allocation of tasks among them. They should execute tasks to reach the global application target and to satisfy the relevant requirements while optimizing the network performance in terms of resources used. This issue should be continuously addressed to dynamically adapt the system to changes in terms of application requirements and network topolog

Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-iot integrated deployment environments

Traditionally, hybrid optical-wireless networks (Fiber-Wireless - FiWi domain) and last-mile Internet of Things edge networks (Edge IoT domain) have been considered independently, with no synergic management solutions. On the one hand, FiWi has primarily focused on high-bandwidth and low-latency access to cellular-equipped nodes. On the other hand, Edge IoT has mainly aimed at effective dispatching of sensor/actuator data among (possibly opportunistic) nodes, by using direct peer-to-peer and base station (BS)-assisted Internet communications. The paper originally proposes a model and an architecture that loosely federate FiWi and Edge IoT domains based on the interaction of FiWi and Edge IoT software defined networking controllers: The primary idea is that our federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of end-to-end quality-aware packet management. To show the applicability and the effectiveness of the approach, our original proposal is applied to the notable example of multimedia stream provisioning from surveillance cameras deployed in the Edge IoT domain to both an infrastructure-side server and spontaneously interconnected mobile smartphones; our solution is able to tune the BS behavior of the FiWi domain and to reroute/prioritize traffic in the Edge IoT domain, with the final goal to reduce latency. In addition, the reported application case shows the capability of our solution of joint and coordinated exploitation of resources in FiWi and Edge IoT domains, with performance results that highlight its benefits in terms of efficiency and responsiveness

Cooperative mobility maintenance techniques for information extraction from mobile wireless sensor networks

Recent advances in the development of microprocessors, microsensors, ad-hoc wireless networking and information fusion algorithms led to increasingly capable Wireless Sensor Networks (WSNs). Besides severe resource constraints, sensor nodes mobility is considered a fundamental characteristic of WSNs. Information Extraction (IE) is a key research area within WSNs that has been characterised in a variety of ways, ranging from a description of its purposes to reasonably abstract models of its processes and components. The problem of IE is a challenging task in mobile WSNs for several reasons including: the topology changes rapidly; calculation of trajectories and velocities is not a trivial task; increased data loss and data delivery delays; and other context and application specific challenges. These challenges offer fundamentally new research problems. There is a wide body of literature about IE from static WSNs. These approaches are proved to be effective and efficient. However, there are few attempts to address the problem of IE from mobile WSNs. These attempts dealt with mobility as the need arises and do not deal with the fundamental challenges and variations introduced by mobility on the WSNs. The aim of this thesis is to develop a solution for IE from mobile WSNs. This aim is achieved through the development of a middle-layer solution, which enables IE approaches that were designed for the static WSNs to operate in the presence of multiple mobile nodes. This thesis contributes toward the design of a new self-stabilisation algorithm that provides autonomous adaptability against nodes mobility in a transparent manner to both upper network layers and user applications. In addition, this thesis proposes a dynamic network partitioning protocol to achieve high quality of information, scalability and load balancing. The proposed solution is flexible, may be applied to different application domains, and less complex than many existing approaches. The simplicity of the solutions neither demands great computational efforts nor large amounts of energy conservation. Intensive simulation experiments with real-life parameters provide evidence of the efficiency of the proposed solution. Performance experimentations demonstrate that the integrated DNP/SS protocol outperforms its rival in the literature in terms of timeliness (by up to 22%), packet delivery ratio (by up to 13%), network scalability (by up to 25%), network lifetime (by up to 40.6%), and energy consumption (by up to 39.5%). Furthermore, it proves that DNP/SS successfully allows the deployment of static-oriented IE approaches in hybrid networks without any modifications or adaptations

The Virtual Object as a Major Element of the Internet of Things: a Survey

The Internet of Things (IoT) paradigm has been evolving toward the creation of a cyber-physical world where everything can be found, activated, probed, interconnected, and updated, so that any possible interaction, both virtual and/or physical, can take place. A Crucial concept of this paradigm is that of the virtual object, which is the digital counterpart of any real (human or lifeless, static or mobile, solid or intangible) entity in the IoT. It has now become a major component of the current IoT platforms, supporting the discovery and mash up of services, fostering the creation of complex applications, improving the objects energy management efficiency, as well as addressing heterogeneity and scalability issues. This paper aims at providing the reader with a survey of the virtual object in the IoT world. Virtualness is addressed from several perspectives: historical evolution of its definitions, current functionalities assigned to the virtual object and how they tackle the main IoT challenges, and major IoT platforms, which implement these functionalities. Finally, we illustrate the lessons learned after having acquired a comprehensive view of the topic

QOS-Aware and Status-Aware Adaptive Resource Allocation Framework in SDN-Based IOT Middleware

«L’Internet des objets (IdO) est une infrastructure mondiale pour la société de l’information, qui permet de disposer de services évolués en interconnectant des objets (physiques ou virtuels) grâce aux technologies de l’information et de la communication interopérables existantes ou en évolution. »[1] La vision de l’Internet des Objets est d’étendre l’Internet dans nos vies quotidiennes afin d’améliorer la qualité de vie des personnes, de sorte que le nombre d’appareils connectés et d’applications innovantes augmente très rapidement pour amener l’intelligence dans différents secteurs comme la ville, le transport ou la santé. En 2020, les études affirment que les appareils connectés à Internet devraient compter entre 26 milliards et 50 milliards d’unités. [2, 3] La qualité de service d’application IoT dépend non seulement du réseau Internet et de l’infrastructure de communication, mais aussi du fonctionnement et des performances des appareils IoT. Par conséquent, les nouveaux paramètres de QoS tels que la précision des données et la disponibilité des appareils deviennent importants pour les applications IoT par rapport aux applications Internet. Le grand nombre de dispositifs et d’applications IoT connectés à Internet, et le flux de trafic spontané entre eux rendent la gestion de la qualité de service complexe à travers l’infrastructure Internet. D’un autre côté, les dispositifs non-IP et leurs capacités limitées en termes d’énergie et de transmission créent l’environnement dynamique et contraint. De plus, l’interconnexion de bout en bout entre les dispositifs et les applications n’est pas possible. Aussi, les applications sont intéressées par les données collectées, pas à la source spécifique qui les produit. Le Software Defined Networking (SDN) est un nouveau paradigme pour les réseaux informatiques apparu récemment pour cacher la complexité de l’architecture de réseau traditionnelle (par exemple de l’Internet) et briser la fermeture des systèmes de réseau dans les fonctions de contrôle et de données. Il permet aux propriétaires et aux administrateurs de réseau de contrôler et de gérer le comportement du réseau par programme, en découplant le plan de contrôle du plan de données. SDN a le potentiel de révolutionner les réseaux informatiques classiques existants, en offrant plusieurs avantages tels que la gestion centralisée, la programmabilité du réseau, l’efficacité des coûts d’exploitation, et les innovations. Dans cette thèse, nous étudions la gestion de ressources sur l’infrastructure IoT, y compris les réseaux de transport/Internet et de détection. Nous profitons de la technologie SDN comme le futur d’Internet pour offrir un système de support QoS flexible et adaptatif pour les services IoT. Nous présentons un intergiciel basé sur SDN pour définir un cadre de gestion de QoS pour gérer les besoins spécifiques de chaque application à travers l’infrastructure IoT. De plus, nous proposons un nouveau modèle QoS qui prend en compte les préférences de QoS des applications et l’état des éléments de réseau pour allouer efficacement les ressources sur le réseau transport/Internet basé sur SDN tout en maximisant les performances du réseau.----------ABSTRACT: The Internet of Things (IoT) is an integration of various kinds of technologies, wherein heterogeneous objects with capabilities of sensing, actuation, communication, computation, networking, and storage are rapidly developed to collect the data for the users and applications. The IoT vision is to extend the Internet into our everyday lives, so the number of connected devices and innovative applications are growing very fast to bring intelligence into as many domains as possible. The QoS for IoT application not only depends on the Internet network and communication infrastructure, it is also impacted by the operation and performance of IoT sensing infrastructure. Therefore, the new QoS parameters such as data accuracy, sampling rate, and device availability become important for the IoT applications compared to the Internet applications. The huge number of the Internet-connected IoT devices and application, and the spontaneous traffic flow among them make the management of the quality of service complex across the Internet infrastructure. On the other hand, the non-IP devices and their limited capabilities in terms of energy and transmission create the dynamic environment and hinder the direct interaction between devices and applications. The quality of service is becoming one of the critical non-functional IoT element which needs research and studies. A flexible and scalable QoS management mechanism must be implemented in IoT system to keep up with the growth rate of the Internet-connected IoT devices and applications as well as their heterogeneity and diversity. The solution should address the IoT application requirements and user satisfaction while considering the system dynamism, limitations, and characteristics. Software-Defined Networking (SDN) is an emerging paradigm in computer networking which separates the control plane and the data plane of the network elements. It makes the network elements programmable via the centralized control plane. This approach enables more agile management and control over the network behavior. In this thesis, we take advantage of SDN technology as the future of the Internet to offer a flexible and adaptive QoS support scheme for the IoT services. We present an SDN-based middleware to define a QoS management framework to manage the application specific QoS needs across the IoT infrastructure including transport and sensing network. Also, we propose a new QoS model that takes into account the application QoS preferences and the network elements status to allocate effectively the resources for the applications across SDN network while maximizing network performance

Evaluation of Trust in the Internet Of Things: Models, Mechanisms And Applications

In the blooming era of the Internet of Things (IoT), trust has become a vital factor for provisioning reliable smart services without human intervention by reducing risk in autonomous decision making. However, the merging of physical objects, cyber components and humans in the IoT infrastructure has introduced new concerns for the evaluation of trust. Consequently, a large number of trust-related challenges have been unsolved yet due to the ambiguity of the concept of trust and the variety of divergent trust models and management mechanisms in different IoT scenarios. In this PhD thesis, my ultimate goal is to propose an efficient and practical trust evaluation mechanisms for any two entities in the IoT. To achieve this goal, the first important objective is to augment the generic trust concept and provide a conceptual model of trust in order to come up with a comprehensive understanding of trust, influencing factors and possible Trust Indicators (TI) in the context of IoT. Following the catalyst, as the second objective, a trust model called REK comprised of the triad Reputation, Experience and Knowledge TIs is proposed which covers multi-dimensional aspects of trust by incorporating heterogeneous information from direct observation, personal experiences to global opinions. The mathematical models and evaluation mechanisms for the three TIs in the REK trust model are proposed. Knowledge TI is as “direct trust” rendering a trustor’s understanding of a trustee in respective scenarios that can be obtained based on limited available information about characteristics of the trustee, environment and the trustor’s perspective using a variety of techniques. Experience and Reputation TIs are originated from social features and extracted based on previous interactions among entities in IoT. The mathematical models and calculation mechanisms for the Experience and Reputation TIs also proposed leveraging sociological behaviours of humans in the real-world; and being inspired by the Google PageRank in the web-ranking area, respectively. The REK Trust Model is also applied in variety of IoT scenarios such as Mobile Crowd-Sensing (MCS), Car Sharing service, Data Sharing and Exchange platform in Smart Cities and in Vehicular Networks; and for empowering Blockchain-based systems. The feasibility and effectiveness of the REK model and associated evaluation mechanisms are proved not only by the theoretical analysis but also by real-world applications deployed in our ongoing TII and Wise-IoT projects