Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/203

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Citation - WoS: 42
Citation - Scopus: 51
CBI4.0: A Cross-Layer Approach for Big Data Gathering for Active Monitoring and Maintenance in the Manufacturing Industry 4.0
(Elsevier, 2021) Faheem, Muhammad; Butt, Rizwan Aslam; Ali, Rashid; Raza, Basit; Ngadi, Md Asri; Gungor, Vehbi Cagri; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Faheem, Muhammad; Gungor, Vehbi Cagri; 01. Abdullah Gül University
Industry 4.0 (I4.0) defines a new paradigm to produce high-quality products at the low cost by reacting quickly and effectively to changing demands in the highly volatile global markets. In Industry 4.0, the adoption of Internet of Things (IoT)-enabled Wireless Sensors (WSs) in the manufacturing processes, such as equipment, machining, assembly, material handling, inspection, etc., generates a huge volume of data known as Industrial Big Data (IBD). However, the reliable and efficient gathering and transmission of this big data from the source sensors to the floor inspection system for the real-time monitoring of unexpected changes in the production and quality control processes is the biggest challenge for Industrial Wireless Sensor Networks (IWSNs). This is because of the harsh nature of the indoor industrial environment that causes high noise, signal fading, multipath effects, heat and electromagnetic interference, which reduces the transmission quality and trigger errors in the IWSNs. Therefore, this paper proposes a novel cross-layer data gathering approach called CBI4.0 for active monitoring and control of manufacturing processes in the Industry 4.0. The key aim of the proposed CBI4.0 scheme is to exploit the multi-channel and multi-radio architecture of the sensor network to guarantee quality of service (QoS) requirements, such as higher data rates, throughput, and low packet loss, corrupted packets, and latency by dynamically switching between different frequency bands in the Multichannel Wireless Sensor Networks (MWSNs). By performing several simulation experiments through EstiNet 9.0 simulator, the performance of the proposed CBI4.0 scheme is compared against existing studies in the automobile Industry 4.0. The experimental outcomes show that the proposed scheme outperforms existing schemes and is suitable for effective control and monitoring of various events in the automobile Industry 4.0.
Citation - WoS: 5
Node-Level Error Control Strategies for Prolonging the Lifetime of Wireless Sensor Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2021) Tekin, Nazli; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor, Vehbi Cagrı; 01. Abdullah Gül University
In Wireless Sensor Networks (WSNs), energy-efficiency and reliability are two critical requirements for attaining a long-term stable communication performance. Using error control (EC) methods is a promising technique to improve the reliability of WSNs. EC methods are typically utilized at the network-level, where all sensor nodes use the same EC method. However, improper selection of EC methods on some nodes in the network-level strategy can reduce the energy-efficiency, thus the lifetime of WSNs. In this study, a node-level EC strategy is proposed via mixed-integer programming (MIP) formulations. The MIP model determines the optimum EC method (i.e., automatic repeat request (ARQ), forward error correction (FEC), or hybrid ARQ (HARQ)) for each sensor node to maximize the network lifetime while guaranteeing a pre-determined reliability requirement. Five meta-heuristic approaches are developed to overcome the computational complexity of the MIP model. The performances of the MIP model and meta-heuristic approaches are evaluated for a wide range of parameters such as the number of nodes, network area, packet size, minimum desired reliability criterion, transmission power, and data rate. The results show that the node-level EC strategy provides at least 4.4% prolonged lifetimes and 4.0% better energy-efficiency than the network-level EC strategies. Furthermore, one of the developed meta-heuristic approaches (i.e., extended golden section search) provides lifetimes within a 3.9% neighborhood of the optimal solutions, reducing the solution time of the MIP model by 89.6%.
Operator User Management System Based on the TMF615 Standard
(Springer, 2016) Yigit, Melike; Macit, Muhammed; Gungor, V. Cagri; Kocak, Taskin; Ozhan, Oguz; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor, V. Cagri; 01. Abdullah Gül University
Multi-vendor telecommunications networks in a typical service provider environment are managed using multiple proprietary user management systems (UMS), supplied by the operational support system (OSS) vendors. The management of a typical service provider includes communications solutions put into place between the global UMS and the local UMS. Nowadays, in service provider environments OSSs exist that use multi-vendor communications' protocols. In the telecommunications sector, the centralized management of all these different OSSs can cause serious problems for the network operation. In this respect, there is an urgent need for a standardized and centralized provisioning and auditing mechanism for the operators and their entitlements that work on these management systems. To address this need and to provide efficient operations among different service provider network components, this paper outlines the design and development of a TMF615 (Tele Management Forum) standard-based, common communication platform. In this respect, the proposed approach includes a common interface to address communication problems in multi-vendor, service provider environments. The interface and performance evaluations developed are some of the first solutions in this field, and the resulting solutions are converted into a commercial product with a high added value. In this regard, our proposed approach makes an important contribution to scientific literature and commercial applications. The realization of the proposed TMF615 standard-based interface enables the efficient and easy integration of existing and new OSSs of the service providers. In this way, a standardized interface is offered, along with a common communications platform adequate for all different systems. The vendors are thereby only responsible for application development based on specifications, and a standardized communications process is introduced for all related systems. This significantly facilitates the management of service providers, system performance is improved, and a massive cost reduction is provided at the same time. Consequently, the efficient management of network components is provided using a common standardized interface. In this respect, we aim to explain the TMF615 specifications; the evolution of UMS, OSSs and TMF615 with centralized UMS, as well as the implementation and performance evaluation of the TMF615 protocol are all explained in this paper.
Citation - WoS: 15
Citation - Scopus: 16
Stacking Ensemble Learning-Based Wireless Sensor Network Deployment Parameter Estimation
(Springer Heidelberg, 2023) Akbas, Ayhan; Buyrukoglu, Selim; 0000-0002-6425-104X; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Akbas, Ayhan; 01. Abdullah Gül University
In wireless sensor network projects, it is generally desired to cover the area to be monitored at a given cost and to achieve the maximum useful network lifetime. In the deployment of the wireless sensors, it is necessary to know in advance how many sensor nodes will be required, how much the distance between the nodes should be, etc., or what the transmit power level should be, etc. depending on the channel parameters of the area. This necessitates accurate calculation of variables such as maximum network lifetime, communication channel parameters, number of nodes to be used, and distance between nodes. As numbers reach to the order of hundreds, calculation tends to a NP hard problem to solve. At this point, we employed both single-based and stacked ensemble-based machine learning models to speed up the parameter estimations with highly accurate outcomes. Adaboost was superior over other models (Elastic Net, SVR) in single-based models. Stacked ensemble models achieved best results for the WSN parameter prediction compared to single-based models.

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