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New network architectures and communication technologies continue to emerge to meet rapidly increasing and changing user demands requiring continuous connectivity and high data rate transmissions. These ubiquitous infrastructures result in a paradigm shift in mobile communications with the advent of mobile robots equipped with sensors, unmanned aerial vehicles, and mobile small-cells, which makes the future networks highly dynamic. This dynamism poses unpredictable variations in the network density causing many run-time problems such as disrupted coverage, undesirable quality of service, and inefficient resource usage. Pre-configurations are no longer suitable because of the network topology variations, which prompts us to develop density-adaptive protocols and self-configured system designs. Therefore, the most crucial objective of this thesis is to make future wireless networks density-aware and -adaptive. We propose novel network density estimators using received signal strength and density-aware networking applications. We introduce a distance matrix-based density estimator, multi-access edge cloud-based density estimator, and interference-based density estimator for wireless networks. We also develop density-aware network outage, transmit power adaptation, and channel utilization approaches by considering the effective network density as an optimization parameter for clustered ad hoc networks, mobile cellular networks, and flying ad hoc networks. We validate the results by implementing Monte-Carlo simulations on MATLAB. Outputs of this thesis may help network operators enhance service quality, create the best deployment strategies, reduce operational expenditures, and meet increasing user expectations without wasting network resources. Density-aware and -adaptive applications make wireless networks self-organized and run-time adaptable.-Ph.D. - Doctoral Progra

Geniş ölçekli algılayıcı ağlarında yoğunluk tahmini.

Density estimation is a significant problem in large-scale wireless ad-hoc networks since the density drastically impacts the network performance. It is crucial to make the network adaptive in the run-time to the density changes that may not be predictable in advance. Local density estimators are required while taking run-time control decisions to improve the network performance. A wireless node may estimate the density locally by measuring the received signal strength (RSS) of packets sent by its neighbours. In this thesis, RSS-based individual and cooperative density estimators are validated by controlled field experiments conducted in the FIT IoT-LAB test-bed, in France. According to the experiments these methods cannot be used as accurate density estimators in practice. The success of the individual density is significantly affected by the position of the estimating node and the number of its neighbours. Also, the cooperative density estimator is affected negatively by correlated data. Hence, a new fusion approach is proposed as a new density estimator. New method is more accurate than the two other density estimators. However, it should be considered that the RSS is prone to large- and small-scale fading, and this phenomenon negatively affects the accuracy of density estimators.M.S. - Master of Scienc

Control and Motion Planning for Mobile Robots with Microsoft Kinect-Based Real-Time Hand Gestures

An experimental setup consisting of a hand gesture recognition system based on a Microsoft Kinect XBOX 360 device, a wireless communication system, and a tele-operable robotic system with autonomous shuttling capabilities will be introduced, and the results of a few independent and geographically distributed social experiments aiming to figure out whether such a setup might yield more natural ways of interactions between an inexperienced human operator and a mobile robotic platform will be presented

ECOLOGICAL AND VISUAL CHARACTERISTICS OF NATIVE PLANT COMPOSITIONS IN MOUNTAIN FORESTS

WOS: 000430372900024Plants are important components of native landscape should be handled in accordance with their features, enabling them to be recognized, defined and utilized in natural and cultural environments. Road corridors are the best places to observe changes related to succession and fragmentation in native vegetation in the mountainside. In the present study, carried out in the road corridors in the mountainside within the boundaries of Trabzon province in Turkey. It was aimed to define the vegetation visually and ecologically based on the native landscape features. While native plant compositions were ecologically defined, they were approached as an ecological corridor. Patch Analyses based on landscape metrics in the vegetation around this ecological corridor were carried out via GIS. As for visual studies, photographing, visualization and surveys were used to define the design elements and design principles of plant composition and the visual effects they had. Thus, come up in planting design, it was determined according to which design principle design elements came together and what kind of a visual effect appeared. In the final phase, the relationships between the values produced by ecological and visual parameters were stated. Consequently, some significant relationships were found out between patch analysis metrics and visual parameters, area metrics and potential effect of seasonal change of native compositions, habitat features and fragmentation values etc

Density-aware cell zooming

Ultra-dense deployments and mobile cells significantly change cellular networking paradigm. Infrastructure and topology of cellular networks become dynamic as opposed to legacy systems where the infrastructure is assumed to be stationary. As topology morphs, base station or user density of networks also change impacting the performance in terms of resource utilization and quality of service. To increase network capacity, preserve coverage and conserve energy, network density should be considered in communication stacks to make the network density-aware and -adaptive. In this work, we analyze the impact of density on network outage in cellular networks. We propose a novel cell zooming technique at run-time considering network outage and density jointly with a three-dimensional base station density estimator

Density-aware outage in clustered Ad Hoc networks

Density of ad hoc networks may vary in time and space because of mobile stations, sleep scheduling or failure of nodes. Resources such as spectrum will be wasted if the network is not density-aware and -adaptive. Towards this aim, distributed and robust network density estimators are required. In this paper, we propose a novel cluster density estimator in random ad hoc networks by employing distance matrix. Monte-Carlo simulation results validate the proposed estimator. The accuracy of the estimator is impressive even under a high amount of distance measurement errors. We also propose a network outage model and a transmit power adaption technique that are density-aware. The results indicate the necessity of the density-aware solutions for making network performance better from capacity, coverage and energy conservation viewpoints