Browsing by Author "Uyan, Osman Gokhan"

Now showing 1 - 5 of 5

Citation - Scopus: 5
Enerji Hasadı ve Sıkıştırmalı Algılama Yapan Gizlilik Odaklı Sualtı Kablosuz Ağlarında Ömür Analizi
(Institute of Electrical and Electronics Engineers Inc., 2019) Uyan, Osman Gokhan; Güngör, Vehbi Çağrı
Underwater sensor networks (UWSN) are a division of classical wireless sensor networks (WSN), which are designed to accomplish both military and civil operations, such as invasion detection and underwater life monitoring. Underwater sensor nodes operate using the energy provided by integrated limited batteries, and it is a serious challenge to replace the battery under the water especially in harsh conditions with a high number of sensor nodes. Here, energy efficiency confronts as a very important issue. Besides energy efficiency, data privacy is another essential topic since UWSN typically generate delicate sensing data. UWSN can be vulnerable to silent positioning and listening, which is injecting similar adversary nodes into close locations to the network to sniff transmitted data. In this paper, we discuss the usage of compressive sensing (CS) and energy harvesting (EH) to improve the lifetime of the network whilst we suggest a novel encryption decision method to maintain privacy of UWSN. We also deploy a Mixed Integer Programming (MIP) model to optimize the encryption decision cases which leads to an improved network lifetime. © 2020 Elsevier B.V., All rights reserved.
Citation - Scopus: 3
LTE Ağları için Servis Kalitesi Farkında Aşağı Yönlü Çizelgeleme Algoritması: Kenar Kullanıcıları Üzerine İnceleme
(Institute of Electrical and Electronics Engineers Inc., 2017) Güngör, Vehbi Çağrı; Uyan, Osman Gokhan
4G/LTE (Long Term Evolution) is the state of the art wireless mobile broadband technology. 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, the performance of existing downlink scheduling algorithms has been investigated in two ways. First, the performance of the algorithms has been investigated in terms of throughput and fairness metrics. Second, a new quality of service-aware (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, has been proposed and evaluated. In addition, a novel QoS-aware downlink-scheduling algorithm, which increases the QoS-aware fairness and overall throughput of the edge users, has been proposed. © 2017 Elsevier B.V., All rights reserved.
Citation - WoS: 14
Citation - Scopus: 20
Machine Learning Approaches for Underwater Sensor Network Parameter Prediction
(Elsevier, 2023) 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.
Citation - WoS: 8
Citation - Scopus: 15
QoS-Aware LTE-A Downlink Scheduling Algorithm: A Case Study on Edge Users
(Wiley, 2019) Uyan, Osman Gokhan; Gungor, Vehbi Cagri
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.
Citation - WoS: 11
Citation - Scopus: 12
A Reliable and Secure Multi-Path Routing Strategy for Underwater Acoustic Sensor Networks
(Elsevier, 2022) 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.