Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 12Citation - Scopus: 18The Impact of Error Control Schemes on Lifetime of Energy Harvesting Wireless Sensor Networks in Industrial Environments(Elsevier, 2020-06) Tekin, Nazli; Gungor, Vehbi CagriDue to the harsh channel conditions of the industrial environments, the data transmission over the wireless channel suffers from erroneous packets. The energy consumption of error control schemes is of great importance for battery-limited Wireless Sensor Networks (WSNs) in industrial environments. In this paper, the lifetime analysis of error control schemes, i.e., Automatic Repeat Request (ARQ), Forward Error Correction (FEC) and Hybrid ARQ (HARQ), is presented under different industrial environment channel conditions. Furthermore, the impact of energy harvesting methods on the network lifetime is investigated. A novel Mixed Integer Programming (MIP) framework is developed to maximize the network lifetime while meeting application reliability. Performance results show that utilizing HARQ-II error control scheme for Mica2 and BCH(31,21,5) for Telos improves the network lifetime while meeting the desired application reliability rate.Article Citation - WoS: 24Citation - Scopus: 30On the Lifetime of Compressive Sensing Based Energy Harvesting in Underwater Sensor Networks(IEEE-Inst Electrical Electronics Engineers Inc, 2019-06-15) Erdem, Huseyin Emre; Yildiz, Huseyin Ugur; Gungor, Vehbi CagriRecently, there has been a growing interest in academia and industry on the development of underwater acoustic sensor networks (UASNs) for scientific, commercial, and military purposes. Severe underwater channel conditions and limited battery energy of underwater nodes pose great challenges to prolong UASNs lifetime. Compressive sensing (CS), energy harvesting (EH), and transmission power control (TPC) are three promising solutions to improve UASNs lifetime. This paper aims to quantitatively investigate the joint impact of CS, EH, and TPC methods on the lifetime of UASNs. A novel Mixed Integer Programming framework is developed to maximize the network lifetime by joint consideration of CS, EH, and TPC. The performance results show that the impact of CS on the network lifetime is higher than that of EH when both methods are combined with TPC. Moreover, when all three methods are combined, the network lifetime can be extended up to three times as compared to the case when all three methods are not utilized.Article Citation - WoS: 24Citation - Scopus: 29On the Lifetime Analysis of Energy Harvesting Sensor Nodes in Smart Grid Environments(Elsevier, 2018-06) Erdem, H. E.; Gungor, V. C.Smart grids represent the future of power generation, distribution and transmission systems. Integration of renewable energy sources with fluctuating power output into the grid requires constant monitoring of grid assets. Wireless Sensor Networks (WSNs) provide an efficient monitoring infrastructure for data collection from multiple locations for extended periods. The aim of this study is to investigate the lifetime of the energy harvesting WSN nodes inside a substation, where the sensor nodes exploit the abundant electromagnetic field in the substation environment. Performance results show that the impact of harvesters on node lifetime is crucial compared to available power management systems, when realistic substation channel conditions are considered. (C) 2018 Elsevier B.V. All rights reserved.Conference Object Citation - Scopus: 12Lifetime Analysis of Energy Harvesting Underwater Wireless Sensor Nodes(Institute of Electrical and Electronics Engineers Inc., 2017-05) Erdem, Huseyin Emre; Güngör, Vehbi ÇağrıThe application of Wireless Sensor Networks (WSNs) in underwater environments poses various challenges. One of the most important problems is the limited lifetime of underwater sensor nodes. Considering how challenging and costly it is to change the batteries of sensor nodes in underwater environments, energy harvesting methods are rendered as a promising solution. In this study, the contributions of energy harvesting via turbine and hydrophone harvesters as well as schedule and trigger driven energy management methods on node lifetime have been analyzed. Performance evaluations have been conducted considering real-life conditions, e.g. flow rates, of Istanbul Bosphorus Strait. © 2017 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 55Energy Harvesting and Battery Technologies for Powering Wireless Sensor Networks(Elsevier Inc., 2016) Tuna, Gürkan; Güngör, Vehbi ÇağrıDue to the advances in wireless sensor networks (WSNs), factory and plant process automation systems are being reinvented. WSN-based industrial applications often cost much less than wired networks in both the short and long terms; automation engineers are empowering existing solutions with the new capabilities of WSNs. On the other hand, since industrial wireless sensor networks (IWSNs) consist of thousands of nodes, the problem of powering the nodes is critical. Power to the nodes is usually provided through primary batteries and this necessitates replacement when the batteries are depleted. However, the replacement may not be cost-effective or even feasible in most industrial applications.Though advancements in integrated circuit technologies help in saving more energy by leading to lower energy consumption levels, they do not eliminate the use of battery power. In this regard, energy harvesting technologies play a key role in extending the battery lifetime of the nodes. Wireless sensor nodes within industrial plants can operate from energy harvested from available energy sources such as heat, mechanical motion or vibration, indoor lighting, electromagnetic fields, and air flow. In this chapter, a review of existing energy storage technologies and various energy-harvesting techniques is given. The chapter then discusses open research issues in these topics. © 2020 Elsevier B.V., All rights reserved.Article Citation - WoS: 17Citation - Scopus: 22Analyzing Lifetime of Energy Harvesting Underwater Wireless Sensor Nodes(Wiley, 2019-11-15) Erdem, H. Emre; Gungor, V. CagriUnderwater Wireless Sensor Networks (UWSNs) are utilized to monitor underwater environments that pose many challenges to researchers. One of the key complications of UWSNs is the difficulty of changing node batteries after their energy is depleted. This study aims to diminish the issues related to battery replacement by improving node lifetime. For this goal, three energy harvesting devices (turbine harvester, piezoelectric harvester, and hydrophone harvester) are analyzed to quantitate their impacts on node lifetime. In addition, two different power management schemes (schedule-driven and event-driven power management schemes) are combined with energy harvesters for further lifetime improvement. Performance evaluations via simulations show that energy harvesting methods joined by power management schemes can improve node lifetime substantially when actual conditions of Istanbul Bosporus Strait are considered. In this respect, turbine harvester makes the biggest impact and provides lifetime beyond 2000 days for most cases, while piezoelectric harvester can perform the same only for low duty cycle or event arrival values at short transmission ranges.Article Citation - WoS: 19Citation - Scopus: 28Analysis of Compressive Sensing and Energy Harvesting for Wireless Multimedia Sensor Networks(Elsevier, 2020-06) Tekin, Nazli; Gungor, Vehbi CagriOne of the main concerns of Wireless Multimedia Sensor Networks (WMSNs) is the huge data size causing the higher energy consumption in transmission. The high energy consumption is a critical problem for lifetime of network includes sensor nodes with limited battery. The data size reduction and Energy Harvesting (EH) methods are the promising solutions to improve the network lifetime. The main objective of this paper is to evaluate the impact of the different data size reduction methods, such as image compression and Compressive s Sensing (CS), and EH methods, such as vibration, thermal and indoor solar, on WMSNs lifetime in industrial environments. In addition, a novel Mixed Integer Programming (MIP) framework is proposed to maximize the network lifetime when EH, CS, and Error Control (EC) approaches are utilized together. Comparative performance results show that utilizing Binary Compressive Sensing (BCS) and Indoor Solar Harvester (ISH) extends industrial network lifetime significantly. (C) 2020 Elsevier B.V. All rights reserved.Conference Object Citation - WoS: 7Citation - Scopus: 12Ambient Energy Harvesting for Low Powered Wireless Sensor Network Based Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2019-04) Faheem, Muhammed Yasir; Ashraf, Muhammad Waqar; Butt, Rizwan Aslam; Raza, Basit; Ngadi, M. A.; Güngör, Vehbi ÇağrıLimited battery lifetime is one of the most critical issues for wireless sensor networks (WSNs)-based smart grid (SG) applications. Recently, ambient energy harvesting (AEH) has been considered to significantly improve the network lifetime of the WSNs-based SG applications. However, extracting a significant amount of energy from the ambient energy resource due to time varying links quality affected by power grid environments is the main issue for WSNs-based applications in SG. In this paper, we propose a novel multi-source energy harvesting mechanisms for WSNs-based SG applications. The propose hybrid ambient energy harvesting framework through the designed circuitry successfully harvests massive power density by capturing the radial electric field (EF) and ambient radio frequency WiFi 2.4GHz band signals present in the vicinity of 500kV power grid station. The design energy harvesting schemes have been implemented on the recently developed routing protocol for SG applications. The experiments using EstiNet9.0, demonstrate that the designed framework is efficient in terms of energy harvesting capabilities to enable a long-lasting lifetime of the WSNs-based smart grid applications. © 2020 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 29A Hybrid Energy Harvesting Framework for Energy Efficiency in Wireless Sensor Networks Based Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2018-06) Yildiz, Huseyin Ugur; Güngör, Vehbi Çağrı; Tavli, BülentIn smart grid applications, Wireless Sensor Net-works (WSNs) which consist of battery limited sensor nodes are used on critical equipments of power distribution grids for monitoring purposes. WSN nodes have tight energy constraints hence it is important to reduce the energy consumption of sensor nodes due to harsh propagation characteristics of smart grid environment. One possible way to reduce the energy consumption is to utilize transmission power control where transmission powers are adjusted according to channel conditions. Another technique is to employ energy harvesting schemes to provide additional power for nodes by using environmental energy sources. Solar and electromagnetic energies are two possible environmental energy sources in outdoor substation environments. Solar energy can be efficiently exploited in a sunny day. On the other hand, electromagnetic energy can be used at any time. In this work, we propose a hybrid energy harvesting model that exploits both solar and electromagnetic energies and develop a Mixed Integer Programming (MIP) method to minimize the energy dissipation of sensor nodes. By using the MIP framework, we quantify the impact of the proposed hybrid energy harvesting model as well as transmission power control on the energy saving of nodes. © 2018 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 5Enerji Hasadı ve Sıkıştırmalı Algılama Yapan Gizlilik Odaklı Sualtı Kablosuz Ağlarında Ömür Analizi(Institute of Electrical and Electronics Engineers Inc., 2019-04) Uyan, Osman Gokhan; Güngör, Vehbi ÇağrıUnderwater 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.