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Smart-Cities Enabled by Heterogeneous Networks
AuthorRegis, Paulo Alexandre
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There is a growing interest in the application of new technologies to assist city management and improve the quality of life of its residents. A Smart-City is composed of several connected Internet of Things electronic devices used to manage the city's assets and resources. To harness the wide variability of coverage, bandwidth, and reliability offered by different technologies, Smart-City network providers are tending more toward the deployment of heterogeneous networks. These heterogeneous networks would be capable of providing different sets of services governed by their corresponding quality–of–service (QoS) capabilities. Different components of the network system need to be upgraded to take in the new functionalities that come with heterogeneous networks. The lower layers must diligently control the access parameters in order to maintain the network connectivity without compromising the QoS. The network layer will have to be aware of the state of the lower layers in order to enhance routing strategies based on several optimization parameters and continuously adapt itself as the system state evolves. Subsequently, the upper application layer must be aware of the conditions of the system and adequately adapt its connectivity requirements. Here, we investigate ways to optimize heterogeneous networks components from multiple points of view. We pay particular attention to routing challenges in multi-radio multi-channel ad hoc networks as well as the challenges the mobility of the network brings.In this dissertation, we propose two methods to balance the traffic load of data flows. First, we design a split-path routing method that assigns multiple paths to data streams given the network state and the flow requirements. Results show that each strategy of path assignment yield different results, and can be used in different situations depending on the network application scenario. Next, we created a distributed routing protocol that uses the past routing decisions to compute the next one by combining multiple metrics such as energy levels and link utilization.Furthermore, we explore the positioning and mobility problems in ad hoc networks. The physical position, as well as the number of nodes in the network, can drastically affect the overall performance of the network since the main medium of transmission is the air. We propose an algorithm to reduce the number of devices necessary to guarantee coverage of a given map. The algorithm runs in linear complexity, which is advantageous for large scale systems. Then, we propose new mobility models for 3D networks to account for urban areas where buildings and other obstacles are presentWe also perform a preliminary study on machine learning (ML) assisted networks. We explore the use of ML models in a cross-layer routing scenario to limit the dissemination of control packets. Finally, we developed a testbed that enables energy-aware prototyping in real IoT devices using reusable code from the simulation phase, bridging the gap between theoretical protocols to the production environment.