Person: CİCİOĞLU, MURTAZA
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CİCİOĞLU
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MURTAZA
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Publication Ehealth monitoring testb e d with fuzzy based early warning score system(Elsevier, 2021-02-25) Calhan, Ali; Cicioğlu, Murtaza; Ceylan, Arif; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020Background and objective: EHealth monitoring systems are able to save the persons' lives and track some vital physiological signs of patients, sportsmen, and soldiers for some purposes. Instant data tracking enables appropriate clinical interventions. The early warning score concept defines that specific vital human body signs that are considered together and gives the persons' health score. The patient's vital signs are periodically recorded with the Early Warning Score (EWS) system and the illness severity score of the patient is decided manually. The aim of the study is to monitor a person's health data continuously and calculate the EWS score thanks to the fuzzy logic. Therefore, the simulation as a testbed is constructed for real-time applications with ISO/IEEE 11073 Health informatics -Medical/health device communication standard.Methods: In our paper, a fuzzy-based early warning score system in the EHealth monitoring testbed is proposed. Real-time data are obtained from Riverbed Modeler simulation software with socket programming and stored in the InfluxDB using Node-Red and monitored on the remote desktop with Grafana.Results: Heart rate, body temperature, systolic blood pressure, respiratory rate, and SPO2 are taken into consideration in the fuzzy-based evaluation system for EWS. The data produced in the Riverbed has been provided in a realistic manner because the real human vital sign values are considered during generating vital signs.Conclusions: Using real-time Riverbed Modeler health data with fuzzy-based EWS, a more realistic testbed platform is constructed in this study.Publication Multi-criteria handover management using entropy-based saw method for sdn-based 5g small cells(Springer, 2021-04-28) Cicioglu, Murtaza; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020The high data traffic requirements of the new generation 5G networks will be satisfied with effective and efficient mobility and handover management. However, dense or ultra-dense small cell (eNB) placements in 5G networks may lead to some problems, such as latency, handover failures, frequent handover, ping-pong effect, etc. In this study, we proposed an Entropy-based simple additive weighting decision-making method for multi-criteria handover in software-defined networking (SDN) based 5G small cells for the solution of the aforementioned problems. This method provides the connection of the mobile node to the most suitable eNB using bandwidth, user density and SINR parameters. The proposed handover method is compared with conventional LTE handover and distributed approach in terms of delay, block ratio, handover failure and throughput according to the varying number of mobile users. The scalability of handovers for both approaches according to the user number are also analysed. According to the simulation results, the proposed approach achieved 15%, 48% and 22% improvement in handover delay, blocking probability and throughput, respectively, compared to the conventional LTE handover.Publication Fuzzy logic based handover management in small cell networks(IEEE, 2021) Cicioğlu, Murtaza; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020In order to meet high data traffic demands in fifth generation (5G) networks, many small cells (eNBs) are needed. This approach is used in next-generation wireless communication to increase network capacity and coverage in dense networks. However, this approach can cause handover delays and unnecessary handover (ping-pong effect). In order to overcome these problems, fuzzy logic-based handover management has been proposed in small cell networks. In fuzzy logic-based handover management, mobile nodes select the most suitable small cells with RSSI, SNR, and Jitter parameters. Thanks to this approach, mobile nodes determine the most suitable small cells with fuzzy logic decision mechanism in next generation 5G small cell networks. Fuzzy logic-based handover management and traditional handover algorithm have been compared using delay and handover numbers. According to the results, it has been observed that the proposed approach gives more successful results than the traditional handover algorithm.Publication Iot-based gps assisted surveillance system with inter-wban geographic routing for pandemic situations(Elsevier, 2021-03-18) Sen, Seda Savascı; Cicioğlu, Murtaza; Çalhan, Ali; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020Background: Worldwide pandemic situations drive countries into high healthcare costs and dangerous conditions. Hospital occupancy rates and medical expenses increase dramatically. Real-time remote health monitoring and surveillance systems with IoT assisted eHealth equipment play important roles in such pandemic situations. To prevent the spread of a pandemic is as crucial as treating the infected patients. The COVID-19 pandemic is the ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Methods: We propose a surveillance system especially for coronavirus pandemic with IoT applications and an inter-WBAN geographic routing algorithm. In this study, coronavirus symptoms such as respiration rate, body temperature, blood pressure, oxygen saturation, heart rate can be monitored and the social distance with ?maskwearing status? of persons can be displayed with proposed IoT software (Node-RED, InfluxDB, and Grafana).Results: The geographic routing algorithm is compared with AODV in outdoor areas according to delivery ratio, delay for priority node, packet loss ratio and bit error rate. The results obtained showed that the geographic routing algorithm is more successful for the proposed architecture.Conclusion: The results show that the use of WBAN technology, geographic routing algorithm, and IoT applications helps to achieve a realistic and meaningful surveillance system with better statistical data.Publication Energy efficiency solutions for IEEE 802.15.6 based wireless body sensor networks(Springer, 2021-02-26) Cicioglu, Murtaza; Calhan, Ali; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020IEEE 802.15.6 standard has been designed for wireless body sensor networks (WBSNs) that consist of several sensors and a coordinator node in, on or around the human body. In WBSNs, the body sensors continuously send their data to the coordinator node for remote healthcare applications. Continuously sensing body signals is a requirement for vital signs but continuously sending these signals to a destination over coordinator node is not necessary. Measured signs may be in a normal range for a healthy person, so these measurements may not be transmitted to a destination. In this study, the event-driven approach in an IEEE 802.15.6 based WBSN architecture are examined. If a vital sign exceeds the normal range in the proposed architecture, the corresponding sensor must send the sign to the coordinator node. In addition, a WBSN architecture is designed with the energy harvesting capabilities for purposing energy efficiency in a different way. Comparative performance analysis of three WBSN; traditional WBSN, event-driven WBSN, and energy harvesting aware WBSN is given in this study to show the impacts of energy efficiency methods to WBSNs. The event-driven scheme outperforms traditional WBSN, with a delay of 21% and energy consumption of 67% and the proposed energy harvesting aware scheme provides 5% additional energy to the traditional WBSN. Simulation results show that our proposed methods yield much better performance than the traditional approach.Publication Handover management in software-defined 5G small cell networks via long short-term memory(Wiley, 2022-01-19) Cicioğlu, Murtaza; Calhan, Ali; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-20205G and beyond communication technologies have started to spread around the world. Higher frequencies lead 5G base stations to have small coverage areas. Besides, the wireless network users have mobility and may move fast among the base stations. Software-defined networking (SDN) is a promising network solution for dynamic and dense networks such as 5G networks. The handover process defines the transfer of mobile users' connections among the base stations and the handover has to happen frequently in ultra-dense networks. In this study, we aim to construct a more robust handover based on long short-term memory (LSTM) with SDN in terms of the number of handover and handover failures. LSTM, linear regression, support vector machine, and tree algorithms performances have been investigated for handover. According to the R-2 values of LSTM, SVM, tree, linear regression results are obtained as 0.998, 0.980, 0.980, and 0.75, respectively. Root mean square error, coefficient of determination (R), mean squared error, and mean absolute deviation statistics prove the improvement of the handover mechanism. In the proposed approach, approximately 30% reduction in the HO failure ratio and 22.22% reduction number of handover have been observed.Publication Drone-assisted smart data gathering for pandemic situations(Pergamon-Elsevier Science Ltd, 2022-01-25) Çalhan, Ali; Cicioğlu, Murtaza; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü.; AAL-5004-2020In this study, a new approach is proposed based on drone-assisted smart data gathering for pandemic situations. Drones can play important roles in highly dynamic and dense disaster areas for the data gathering process. Under these conditions, if big data gathering is necessary, the network traffic can be lightened and balanced with smart techniques. For these reasons, the drones construct the aerial network and scan the frequency bands in their coverage area. Then the collected data on the related drone is processed in terms of importance and priority levels. The drones take on fog computing capabilities for the specific duties. So, the unnecessary data will not be transmitted to the related destinations and the most priority data will be transferred immediately to the related units. The proposed mechanism is developed and examined with various scenarios. The throughput, delay and energy consumption performance metrics are considered for performance evaluation.Publication Performance analysis of cross-layer design for internet of underwater things(IEEE, 2022-08-01) Cicioğlu, Murtaza; Calhan, Ali; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020Underwater communication is a diverse and complex environment and has many problems. There are many problems in modeling and operating underwater networks. Physical and data link layer specifications for underwater networking should be taken into account in terms of quality of service metrics. In this study, we construct an underwater simulation environment as a cross-layer design consisting of physical and data link layers for the Internet of Underwater Things (IoUT) Network. The IoUT network has sensors with various priorities, a central node as a hub and a gateway as a buoy. The underwater sensors communicate with CSMA/ CA-based IEEE 802.15.6 protocol on low frequencies. For a more realistic communication channel, all the features of the acoustic channel are designed and performance analyzes are discussed. In addition, the proposed IoUT is compared with terrestrial network results in terms of bit error rate, signal-to-noise ratio, packet loss ratio, end-to-end delay, radio receiver utilization, and throughput. We claim that we have made a realistic IoUT network, especially for divers, autonomous underwater vehicles with specific sensors, or for similar purposes.Publication A multiprotocol controller deployment in SDN-based ioMT architecture(IEEE, 2022-11-01) Cicioğlu, Murtaza; Çalhan, Ali; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü; 0000-0002-5657-7402; AAL-5004-2020Internet of Medical Things (IoMT) as a next-generation network requires heterogeneous services, technologies, and equipment infrastructure management resulting in more complex systems. The software-defined networking (SDN) approach has emerged as a promising solution to reduce this complexity by proposing a vendor-independent structure that disaggregates the control and data planes. In this study, an architecture based on the SDN is proposed for such heterogeneous and complex IoMT networks. A new controller that supports different wireless communication protocols has been developed for the control plane. We propose machine learning (ML)-based load balancing and time-sensitive prioritization (MLA) algorithms for dense and dynamic networks. An SDN-based IoMT network that consists of IEEE 802.15.6, TDMA, and IEEE 802.11 protocols is analyzed in a simulation program simultaneously using various scenarios in terms of throughput, delay, packet loss ratio, bit error rate, and user density parameters. In addition, in this study, a new data set is created for load balancing. The performances of support vector machine (SVM), ensemble of decision trees, k-NN, and Naive Bayes ML algorithms are compared, and SVM gives the best result with 95.1% accuracy.Publication Cnn-based automatic modulation recognition for index modulation systems(Pergamon-elsevier Science Ltd, 2023-11-21) Leblebici, Merih; Çalhan, Ali; Cicioğlu, Murtaza; CİCİOĞLU, MURTAZA; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Bilgisayar Mühendisliği Bölümü.; 0000-0002-5657-7402; AAL-5004-2020Automatic modulation recognition (AMR) has garnered significant attention in both civilian and military domains, with applications ranging from spectrum sensing and cognitive radio (CR) to the deterrence of adversary communication. Index modulation (IM) represents an innovative digital modulation technique that exploits the indices of parameters of communication systems to transmit extra information bits. This paper aims to examine the performance of a convolutional neural network (CNN)-based AMR across various IM systems, including spatial modulation (SM), quadrature spatial modulation (QSM), and generalized spatial modulation (GSM) with eight digital modulation schemes. In this study, we leverage confusion matrices, receiver operating characteristic (ROC) curves, and F1 scores to illustrate the recognition model's outputs.