Future and next-generation wireless networks are driven by the rapidly growing wireless traffic stemming from diverse services and applications, such as the Internet-of-Things (IoT), virtual reality, autonomous vehicles, and smart intersections. Many of these applications require massive connectivity between IoT devices as well as wireless access links with ultra-high bandwidth (Gbps or above) and ultra-low latency (10ms or less). Therefore, realizing the vision of future wireless networks requires significant research efforts across all layers of the network stack. In this thesis, we use a cross-layer approach and focus on several critical components of future wireless networks including IoT systems and full-duplex (FD) wireless, and on experimentation with advanced wireless technologies in the NSF PAWR COSMOS testbed. First, we study tracking and monitoring applications in the IoT and focus on ultra-low-power energy harvesting networks. Based on realistic hardware characteristics, we design and optimize Panda, a centralized probabilistic protocol for maximizing the neighbor discovery rate between energy harvesting nodes under a power budget. Via testbed evaluation using commercial off-the-shelf energy harvesting nodes, we show that Panda outperforms existing protocols by up to 3x in terms of the neighbor discovery rate. We further explore this problem and consider a general throughput maximization problem among a set of heterogeneous energy-constrained ultra-low-power nodes. We analytically identify the theoretical fundamental limits of the rate at which data can be exchanged between these nodes, and design the distributed probabilistic protocol, EconCast, which approaches the maximum throughput in the limiting sense. Performance evaluations of EconCast using both simulations and real-world experiments show that it achieves up to an order of magnitude higher throughput than Panda and other known protocols. We then study FD wireless - simultaneous transmission and reception at the same frequency - a key technology that can significantly improve the data rate and reduce communication latency by employing self-interference cancellation (SIC). In particular, we focus on enabling FD on small-form-factor devices leveraging the technique of frequency-domain equalization (FDE). We design, model, and optimize the FDE-based RF canceller, which can achieve >50dB RF SIC across 20MHz bandwidth, and experimentally show that our prototyped FD radios can achieve a link-level throughput gain of 1.85-1.91x. We also focus on combining FD with phased arrays, employing optimized transmit and receive beamforming, where the spatial degrees of freedom in multi-antenna systems are repurposed to achieve wideband RF SIC. Moving up in the network stack, we study heterogeneous networks with half-duplex and FD users, and develop the novel Hybrid-Greedy Maximum Scheduling (H-GMS) algorithm, which achieves throughput optimality in a distributed manner. Analytical and simulation results show that H-GMS achieves 5-10x better delay performance and improved fairness compared with state-of-the-art approaches. Finally, we described experimentation and measurements in the city-scale COSMOS testbed being deployed in West Harlem, New York City. COSMOS' key building blocks include software-defined radios, millimeter-wave radios, a programmable optical network, and edge cloud, and their convergence will enable researchers to remotely explore emerging technologies in a real world environment. We provide a brief overview of the testbed and focus on experimentation with advanced technologies, including the integrating of open-access FD radios in the testbed and a pilot study on converged optical-wireless x-haul networking for cloud radio access networks (C-RANs). We also present an extensive 28GHz channel measurements in the testbed area, which is a representative dense urban canyon environment, and study the corresponding signal-to-noise ratio (SNR) coverage and achievable data rates. The results of this part helped drive and validate the design of the COSMOS testbed, and can inform further deployment and experimentation in the testbed. In this thesis, we make several theoretical and experimental contributions to ultra-low-power energy harvesting networks and the IoT, and FD wireless. We also contribute to the experimentation and measurements in the COSMOS advanced wireless testbed. We believe that these contributions are essential to connect fundamental theory to practical systems, and ultimately to real-world applications, in future wireless networks.

Le routage dans les réseaux de capteurs, est un service essentiel qui transmet les lectures des capteurs à certains points de collecte de données dans le réseau sur la base des relais multi-saut. Cette tâche est particulièrement difficile car elle doit être réalisé d'une manière efficace au niveau de consommation de ressources et avec une quantité limitée d'informations disponible. La facilité de mise à l'échelle et l'utilisation d'information local pour fonctionner ont permis au routage géographique être considéré comme une approche prometteuse. Cependant, lors de son implémentation, certains problèmes subsistent en raison des difficultés pratiques. Dans ce travail de recherche, deux problématiques inhérentes aux protocoles de routages géographique ont été étudiés: i) Le coût associé: aux évanouissements liés aux obstacles et aux multi-trajets suivis par un signal transmis sur un canal radio, aux changements rapides des conditions physiques du canal de transmission and ii) l'administration de resources affectés à chaque noeud appartenant au réseau. Afin de résoudre ce problème, deux protocoles ont été présentés: un protocole de routage géographique avec communications coopératives, Beaconless Cooperative Geographic cross-layer protocol for ad hoc and sensor networks (CoopGeo) et un protocole de routage basé sur le principe d'extension de couverture: Relay-Aware Cooperative Routing (RACR). / In Wireless Sensor Networks, the routing task is an essential service that forwards the sensor readings to some data collection points in the network on the basis of the multi-hop relaying. The routing task is particularly challenging as it should be realized in an energy efficiency manner with limited amount of information. Geographic routing is a promising approach because of its good scalability and local information use, but when deploying such approach, some problems still remain because of some practical difficulties. In this thesis, some techniques have been explored to address two issues in geographic routing protocols: i) Cost associated to: the wireless channel impairments due to fading, mobility patterns or high dynamic environment and ii) the management of constrained resources of the nodes. To tackle these issues, two protocols were presented: a beaconless Cooperative Geographic cross-layer protocol for ad hoc and sensor networks (CoopGeo) and a Relay-Aware Cooperative Routing protocol (RACR). CoopGeo deals the wireless impairments by means of a cross-layer framework where a beaconless geographic routing approach was used to build the route not only in a local manner, but also on the y worked with a relay selection mechanism to exploit the broadcast nature of the wireless communications. The RACR protocol exploits the coverage extension as a result from node cooperation to improve the non-cooperative geographic routing. It is an alternative to scenarios where network resources like energy should be preserved while respecting a Symbol Error Rate constraint (SER).

A wireless sensor network is a network of distributed nodes each equipped with its own sensors, computational resources and transceivers. These sensors are designed to be able to sense specific phenomenon over a large geographic area and communicate this information to the user. Most sensor networks are designed to be stand-alone systems that can operate without user intervention for long periods of time. While the use of wireless sensor networks have been demonstrated in various military and commercial applications, their full potential has not been realized primarily due to the lack of efficient methods to self organize and cover the entire area of interest. Techniques currently available focus solely on homogeneous wireless sensor networks either in terms of static networks or mobile networks and suffers from device specific inadequacies such as lack of coverage, power and fault tolerance. Failing nodes result in coverage loss and breakage in communication connectivity and hence there is a pressing need for a fault tolerant system to allow replacing of the failed nodes. In this dissertation, a unique hybrid sensor network is demonstrated that includes a host of mobile sensor platforms. It is shown that the coverage area of the static sensor network can be improved by self-organizing the mobile sensor platforms to allow interaction with the static sensor nodes and thereby increase the coverage area. The performance of the hybrid sensor network is analyzed for a set of N mobile sensors to determine and optimize parameters such as the position of the mobile nodes for maximum coverage of the sensing area without loss of signal between the mobile sensors, static nodes and the central control station. A novel approach to tracking dynamic targets is also presented. Unlike other tracking methods that are based on computationally complex methods, the strategy adopted in this work is based on a computationally simple but effective technique of received signal strength indicator measurements. The algorithms developed in this dissertation are based on a number of reasonable assumptions that are easily verified in a densely distributed sensor network and require simple computations that efficiently tracks the target in the sensor field. False alarm rate, probability of detection and latency are computed and compared with other published techniques. The performance analysis of the tracking system is done on an experimental testbed and also through simulation and the improvement in accuracy over other methods is demonstrated.

Applications for Wireless Sensor Networks can be updated dynamically by means of wireless upgrade mechanisms. Current research efforts in wireless upgrade mechanisms for WSN have focused on transmitting application packets for upgrades via wireless medium. However, these schemes require significant overhead involved in sending and receiving application packets that affect the sensor operation, in addition to bringing the nodes down to reprogram and restart them. By designing applications in a way that allows dynamic functionality changes during operation, the overhead and sensor delays can be eliminated. Dynamically Controllable Application (DCA) is a novel scheme for designing WSN applications whose behavior can be rapidly and dynamically changed during operation. The results indicate that a veritable functionality change is achieved in a span of a few milliseconds.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.