Browsing by Author "Uyan, Osman Gokhan"

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Machine learning approaches for underwater sensor network parameter prediction
(ELSEVIER, 2023) Uyan, Osman Gokhan; Akbas, Ayhan; Gungor, Vehbi Cagri; 0000-0003-3922-1647; 0000-0002-6425-104X; 0000-0003-0803-8372; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Uyan, Osman Gokhan; Akbas, Ayhan; Gungor, Vehbi Cagri
Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low communication reliability provoked by the constrained battery supply of sensors and harsh channel conditions in the underwater environments. To meet communication reliability requirements, packet-duplication and multi -path routing algorithms have been recommended in the literature. Furthermore, underwater sensors may convey sensitive data, which must be masked to avoid eavesdropping attempts. To improve network security, cryptographic encryption is the most widely used method. Nevertheless, data encryption needs computations to cipher the data, which consumes extra energy, resulting in a cutback in the life span of the network. To address these challenges, an optimization model has been proposed to evaluate the impacts of multi-path routing, packet duplication, encryption, and data fragmentation on the lifetime of the UASNs. However, the solution time of the proposed optimization model is quite high, and sometimes it cannot come up with feasible solutions. To this end, in this study, different regression and neural network methods have been proposed to predict network param-eters and energy consumptions of underwater nodes as supplementary methods to optimization models. Per-formance evaluations show that the proposed methods yield remarkably accurate predictions and can be used for energy consumption prediction in UASNs.
QoS-aware LTE-A downlink scheduling algorithm: A case study on edge users
(WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2019) Uyan, Osman Gokhan; Gungor, Vehbi Cagri; 0000-0003-3922-1647; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü
4G/LTE-A (Long-Term Evolution-Advanced) is the state of the art wireless mobile broadband technology. It allows users to take advantage of high Internet speeds. It makes use of the OFDM technology to offer high speed and provides the system resources both in time and frequency domain. A scheduling algorithm running on the base station holds the allocation of these resources. In this paper, we investigate the performance of existing downlink scheduling algorithms in two ways. First, we look at the performance of the algorithms in terms of throughput and fairness metrics. Second, we suggest a new QoS-aware fairness criterion, which accepts that the system is fair if it can provide the users with the network traffic speeds that they demand and evaluate the performance of the algorithms according to this metric. We also propose a new QoS-aware downlink scheduling algorithm (QuAS) according to these two metrics, which increases the QoS-fairness and overall throughput of the edge users without causing a significant degradation in overall system throughput when compared with other schedulers in the literature.
A reliable and secure multi-path routing strategy for underwater acoustic sensor networks
(ELSEVIER, 2022) Uyan, Osman Gokhan; Akbas, Ayhan; Gungor, Vehbi Cagri; 0000-0003-3922-1647; 0000-0002-6425-104X; 0000-0003-0803-8372; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Uyan, Osman Gokhan; Akbas, Ayhan; Gungor, Vehbi Cagri
Underwater Acoustic Sensor Networks (UASNs) have nowadays become an attractive topic in scientific studies and commercial applications. An important challenge in UASN’s design is the limited network lifetime and low reliability caused by the limited battery energy of sensor nodes and harsh channel conditions in underwater environments. In addition, sensor nodes may generate sensitive data, which needs to be concealed. To this end, cryptographic encryption is a commonly used method to cipher a data before transmission to maintain security. However, encryption methods require additional computation and extra energy, which causes a decrease in the network lifetime. To this end, transmitting fragmented data through multiple paths can be used as a security countermeasure, in conjunction with encryption against silent listening attacks. To address these challenges, in this study, an optimization framework has been developed to analyze the effects of multi-path routing, packet duplication, encryption and data fragmentation on network lifetime. In addition to an optimal solution, Simulated Annealing, Golden Section Search and Genetic Algorithm-based heuristic methods have been developed. Performance results show that the proposed approach jointly solves the problem of UASN lifetime maximization, while providing network reliability and security