WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 24Citation - Scopus: 31On 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.Article Citation - WoS: 18Citation - Scopus: 27Analysis 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.