Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

A Multichannel Medium Access Control and its Performance Estimation for Multihop Wireless Sensor Networks

The thesis proposes a three-tier architecture wireless sensor network to monitor the environment of wide rural area. To enhance the network throughput, a multichannel MAC, 2HCR, is developed. The performance of 2HCR is examined for both single and bidirectional traffics. For the bidirectional traffic, a simple priority support scheme is proposed to give a priority for command traffic. Also, a procedure to estimate the throughput of multihop networks is developed to be used in network design

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)

Review of data fusion methods for real-time and multi-sensor traffic flow analysis

Recently, development in intelligent transportation systems (ITS) requires the input of various kinds of data in real-time and from multiple sources, which imposes additional research and application challenges. Ongoing studies on Data Fusion (DF) have produced significant improvement in ITS and manifested an enormous impact on its growth. This paper reviews the implementation of DF methods in ITS to facilitate traffic flow analysis (TFA) and solutions that entail the prediction of various traffic variables such as driving behavior, travel time, speed, density, incident, and traffic flow. It attempts to identify and discuss real-time and multi-sensor data sources that are used for various traffic domains, including road/highway management, traffic states estimation, and traffic controller optimization. Moreover, it attempts to associate abstractions of data level fusion, feature level fusion, and decision level fusion on DF methods to better understand the role of DF in TFA and ITS. Consequently, the main objective of this paper is to review DF methods used for real-time and multi-sensor (heterogeneous) TFA studies. The review outcomes are (i) a guideline of constructing DF methods which involve preprocessing, filtering, decision, and evaluation as core steps, (ii) a description of the recent DF algorithms or methods that adopt real-time and multi-sensor sources data and the impact of these data sources on the improvement of TFA, (iii) an examination of the testing and evaluation methodologies and the popular datasets and (iv) an identification of several research gaps, some current challenges, and new research trends

Internet of Things From Hype to Reality

The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions

Uncertainty Management of Intelligent Feature Selection in Wireless Sensor Networks

Wireless sensor networks (WSN) are envisioned to revolutionize the paradigm of monitoring complex real-world systems at a very high resolution. However, the deployment of a large number of unattended sensor nodes in hostile environments, frequent changes of environment dynamics, and severe resource constraints pose uncertainties and limit the potential use of WSN in complex real-world applications. Although uncertainty management in Artificial Intelligence (AI) is well developed and well investigated, its implications in wireless sensor environments are inadequately addressed. This dissertation addresses uncertainty management issues of spatio-temporal patterns generated from sensor data. It provides a framework for characterizing spatio-temporal pattern in WSN. Using rough set theory and temporal reasoning a novel formalism has been developed to characterize and quantify the uncertainties in predicting spatio-temporal patterns from sensor data. This research also uncovers the trade-off among the uncertainty measures, which can be used to develop a multi-objective optimization model for real-time decision making in sensor data aggregation and samplin

Reliable, Context-Aware and Energy-Efficient Architecture for Wireless Body Area Networks in Sports Applications

RÉSUMÉ Un Réseau Corporel Sans Fil (RCSF, Wireless Body Area Network en anglais ou WBAN) permet de collecter de l'information à partir de capteurs corporels. Cette information est envoyée à un hub qui la transforme et qui peut aussi effectuer d'autres fonctions comme gérer des événements corporels, fusionner les données à partir des capteurs, percevoir d’autres paramètres, exécuter les fonctions d’une interface d’utilisateur, et faire un lien vers des infrastructures de plus haut niveau et d’autres parties prenantes. La réduction de la consommation d'énergie d’un RCSF est un des aspects les plus importants qui doit être amélioré lors de sa conception. Cet aspect peut impliquer le développement de protocoles de Contrôles d'Accès au Support (CAS, Media Access Control en anglais ou MAC), protocoles de transport et de routage plus efficients. Le contrôle de la congestion est un autre des facteurs les plus importants dans la conception d’un RCSF, parce que la congestion influe directement sur la Qualité De Service (QDS, Quality of Service en anglais ou QoS) et l’efficience en énergie du réseau. La congestion dans un RCSF peut produire une grande perte de paquets et une haute consommation d’énergie. La QDS est directement impactée par la perte de paquets. L’implémentation de mesures additionnelles est nécessaire pour atténuer l’impact sur la communication des RCSF. Les protocoles de CAS pour RCSF devraient permettre aux capteurs corporels d’accéder rapidement au canal de communication et d’envoyer les données au hub, surtout pour les événements urgents tout en réduisant la consommation d’énergie. Les protocoles de transport pour RCSF doivent fournir de la fiabilité bout-à-bout et de la QDS pour tout le réseau. Cette tâche peut être accomplie par la réduction du ratio de perte de paquets (Packet Loss Ratio en anglais ou PLR) et de la latence tout en gardant l'équité et la faible consommation d'énergie entre les noeuds. Le standard IEEE 802.15.6 suggère un protocole de CAS qui est destiné à être applicable à tous les types de RCSF; toutefois, ce protocole peut être amélioré pour les RCSF utilisés dans le domaine du sport, où la gestion du trafic pourrait être différente d’autres réseaux. Le standard IEEE 802.15.6 comprend la QDS, mais cela ne suggère aucun protocole de transport ou système de contrôle du débit. Le but principal de ce projet de recherche est de concevoir une architecture pour RCSF en trois phases : (i) Conception d’un mécanisme sensible au contexte et efficient en énergie pour fournir une QDS aux RCSF; (ii) Conception d’un mécanisme fiable et efficient en énergie pour fournir une récupération des paquets perdus et de l’équité dans les RCSF; et (iii) Conception d’un système de contrôle du débit sensible au contexte pour fournir un contrôle de congestion aux RCSF. Finalement, ce projet de recherche propose une architecture fiable, sensible au contexte et efficiente en énergie pour RCSF utilisés dans le domaine du sport. Cette architecture fait face à quatre défis : l'efficacité de l'énergie, la sensibilité au contexte, la qualité de service et la fiabilité. La mise en place de cette solution aidera à l’amélioration des compétences, de la performance, de l’endurance et des protocoles d’entraînement des athlètes, ainsi qu’à la détection des points faibles. Cette solution pourrait être prolongée à l’amélioration de la qualité de vie des enfants, des personnes malades ou âgées, ou encore aux domaines militaires, de la sécurité et du divertissement. L’évaluation des protocoles et schémas proposés a été faite par simulations programmées avec le simulateur OMNeT++ et le système Castalia. Premièrement, le protocole de CAS proposé a été comparé avec les protocoles de CAS suivants : IEEE 802.15.6, IEEE 802.15.4 et T-MAC (Timeout MAC). Deuxièmement, le protocole de CAS proposé a été comparé avec le standard IEEE 802.15.6 avec et sans l’utilisation du protocole de transport proposé. Finalement, le protocole de CAS proposé et le standard IEEE 802.15.6 ont été comparés avec et sans l’utilisation du système de contrôle du débit proposé. Le protocole de CAS proposé surpasse les protocoles de CAS IEEE 802.15.6, IEEE 802.15.4 et T-MAC dans le pourcentage de pertes de paquets d’urgence et normaux, l’efficacité en énergie, et la latence du trafic d’urgence et du trafic normal. Le protocole de CAS proposé utilisé avec le protocole du transport proposé surpasse la performance du standard IEEE 802.15.6 dans le pourcentage de perte de paquets avec ou sans trafic d’urgence, l’efficacité en énergie, et la latence du trafic normal. Le système de contrôle du débit proposé a amélioré la performance du protocole de CAS proposé et du standard IEEE 802.15.6 dans le pourcentage de perte de paquets avec ou sans trafic d’urgence, l’efficacité en énergie, et la latence du trafic d’urgence.----------ABSTRACT Information collected from body sensors in a Wireless Body Area Network (WBAN) is sent to a hub or coordinator which processes the information and can also perform other functions such as managing body events, merging data from sensors, sensing other parameters, performing the functions of a user interface and bridging the WBAN to higher-level infrastructure and other stakeholders. The reduction of the power consumption of a WBAN is one of the most important aspects to be improved when designing a WBAN. This challenge might imply the development of more efficient Medium Access Control (MAC), transport and routing protocols. Congestion control is another of the most important factors when a WBAN is designed, due to its direct impact in the Quality of Service (QoS) and the energy efficiency of the network. The presence of congestion in a WBAN can produce a big packet loss and high energy consumption. The QoS is also impacted directly by the packet loss. The implementation of additional measures is necessary to mitigate the impact on WBAN communications. The MAC protocols for WBANs should allow body sensors to get quick access to the channel and send data to the hub, especially in emergency events while reducing the power consumption. The transport protocols for WBANs must provide end-to-end reliability and QoS for the whole network. This task can be accomplished through the reduction of both the Packet Loss Ratio (PLR) and the latency while keeping fairness and low power consumption between nodes. The IEEE 802.15.6 standard suggests a MAC protocol which is intended to be applicable for all kinds of WBANs. Nonetheless, it could be improved for sports WBANs where the traffic-types handling could be different from other networks. The IEEE 802.15.6 standard supports QoS, but it does not suggest any transport protocol or rate control scheme. The main objective of this research project is to design an architecture for WBANs in three phases: (i) Designing a context-aware and energy-efficient mechanism for providing QoS in WBANs; (ii) Designing a reliable and energy-efficient mechanism to provide packet loss recovery and fairness in WBANs; and (iii) Designing a context-aware rate control scheme to provide congestion control in WBANs. Finally, this research project proposes a reliable, context-aware and energy-efficient architecture for WBANs used in sports applications, facing four challenges: energy efficiency, context awareness, quality of service and reliability. The benefits of this solution will help to improve skills, performance, endurance and training protocols of athletes, and deficiency detection. Also, it could be extended to enhance the quality of life of children, ill and elderly people, and to security, military and entertainment fields. The evaluation of the proposed protocols and schemes was made through simulations programed in the OMNeT++ simulator and the Castalia framework. First, the proposed MAC protocol was compared against the IEEE 802.15.6 MAC protocol, the IEEE 802.15.4 MAC protocol and the T-MAC (Timeout MAC) protocol. Second, the proposed MAC protocol was compared with the IEEE 802.15.6 standard with and without the use of the proposed transport protocol. Finally, both the proposed MAC protocol and the IEEE 802.15.6 standard were compared with and without the use of the proposed rate control scheme. The proposed MAC protocol outperforms the IEEE 802.15.6 MAC protocol, the IEEE 802.15.4 MAC protocol and the T-MAC protocol in the percentage of emergency and normal packet loss, the energy effectiveness, and the latency of emergency and normal traffic. The proposed MAC protocol working along with the proposed transport protocol outperforms the IEEE 802.15.6 standard in the percentage of the packet loss with or without emergency traffic, the energy effectiveness, and the latency of normal traffic. The proposed rate control scheme improved the performance of both the proposed MAC protocol and the IEEE 802.15.6 standard in the percentage of the packet loss with or without emergency traffic, the energy effectiveness and the latency of emergency traffic