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Article Citation - WoS: 32Citation - Scopus: 39Backhaul-Aware Optimization of Uav Base Station Location and Bandwidth Allocation for Profit Maximization(Ieee-inst Electrical Electronics Engineers inc, 2020) Cicek, Cihan Tugrul; Gultekin, Hakan; Tavli, Bulent; Yanikomeroglu, HalimUnmanned Aerial Vehicle Base Stations (UAV-BSs) are envisioned to be an integral component of the next generation Wireless Communications Networks (WCNs) with a potential to create opportunities for enhancing the capacity of the network by dynamically moving the supply towards the demand while facilitating the services that cannot be provided via other means efficiently. A significant drawback of the state-of-the-art have been designing a WCN in which the service-oriented performance measures (e.g., throughput) are optimized without considering different relevant decisions such as determining the location and allocating the resources, jointly. In this study, we address the UAV-BS location and bandwidth allocation problems together to optimize the total network profit. In particular, a Mixed-Integer Non-Linear Programming (MINLP) formulation is developed, in which the location of a single UAV-BS and bandwidth allocations to users are jointly determined. The objective is to maximize the total profit without exceeding the backhaul and access capacities. The profit gained from a specific user is assumed to be a piecewise-linear function of the provided data rate level, where higher data rate levels would yield higher profit. Due to high complexity of the MINLP, we propose an efficient heuristic algorithm with lower computational complexity. We show that, when the UAV-BS location is determined, the resource allocation problem can be reduced to a Multidimensional Binary Knapsack Problem (MBKP), which can be solved in pseudo-polynomial time. To exploit this structure, the optimal bandwidth allocations are determined by solving several MBKPs in a search algorithm. We test the performance of our algorithm with two heuristics and with the MINLP model solved by a commercial solver. Our numerical results show that the proposed algorithm outperforms the alternative solution approaches and would be a promising tool to improve the total network profit.Article Citation - WoS: 6Citation - Scopus: 123-D Dynamic Uav Base Station Location Problem(informs, 2021) Cicek, Cihan Tugrul; Shen, Zuo-Jun Max; Gultekin, Hakan; Tavli, BulentWe address a dynamic covering location problem of an unmanned aerial vehicle base station (UAV-BS), in which the location sequence of a single UAV-BS in a wireless communication network is determined to satisfy data demand arising from ground users. This problem is especially relevant in the context of smart grid and disaster relief. The vertical movement ability of the UAV-BS and nonconvex covering functions in wireless communication restrict utilizing classical planar covering location approaches. Therefore, we develop new formulations to this emerging problem for a finite time horizon to maximize the total coverage. In particular, we develop a mixed-integer nonlinear programming formulation that is nonconvex in nature and propose a Lagrangean decomposition algorithm (LDA) to solve this formulation. Because of the high complexity of the problem, the LDA is still unable to find good local solutions to large-scale problems. Therefore, we develop a continuum approximation (CA) model and show that CA would be a promising approach in terms of both computational time and solution accuracy. Our numerical study also shows that the CA model can be a remedy to build efficient initial solutions for exact solution algorithms. Summary of Contribution: This paper addresses a facet of mixed integer nonlinear programming formulations. Dynamic facility location problems (DFLPs) arise in a wide range of applications. However, classical DFLPs typically focus on the two-dimensional spaces. Emerging technologies in wireless communication and some other promising application areas, such as smart grids, have brought new location problems that cannot be solved with classical approaches. For practical reasons, many research attempts to solve this new problem, especially by researchers whose primary research area is not OR, have seemed far from analyzing the characteristics of the formulations. Rather, solution-oriented greedy heuristics have been proposed. This paper has two main objectives: (i) to close the gap between practical and theoretical sides of this new problem with the help of current knowledge that OR possesses to solve facility location problems and (ii) to support the findings with an exhaustive computational study to show how these findings can be applied to practice.Article Citation - WoS: 5Citation - Scopus: 6Systematic Investigation of the Effects of Unidirectional Links on the Lifetime of Wireless Sensor Networks(Elsevier, 2013) Ozyer, Sibel T.; Tavli, Bulent; Dursun, Kayhan; Koyuncu, MuratLink unidirectionality is a commonly encountered phenomenon in wireless sensor networks (WSNs), which is a natural result of various properties of wireless transceivers as well as the environment. Transmission power heterogeneity and random irregularities are important factors that create unidirectional links. Majority of the internode data transfer mechanisms are designed to work on bidirectional links (i.e., due to the lack of a direct reverse path, handshaking cannot be performed between a transmitter and receiver) which render the use of unidirectional links infeasible. Yet, there are some data transfer mechanisms designed specifically to operate on unidirectional links which employ distributed handshaking mechanisms (i.e., instead of using a direct reverse path, a multi-hop reverse path is used for the handshake). In this study, we investigate the impact of both transmission power heterogeneity and random irregularities on the lifetime of WSNs through a novel linear programming (LP) framework both for networks that utilize only bidirectional links and for those that can use bidirectional links as well as unidirectional links. (C) 2013 Elsevier B.V. All rights reserved.
