WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Subject: search.filters.subject.Wireless Sensor NetworksWoS Q: search.filters.wosQuartile.Q2

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Now showing 1 - 5 of 5
  • Article
    Citation - WoS: 52
    Citation - Scopus: 69
    Spectrum-Aware Bio-Inspired Routing in Cognitive Radio Sensor Networks for Smart Grid Applications
    (Elsevier Science Bv, 2017-03) Fadel, E.; Faheem, M.; Gungor, V. C.; Nassef, L.; Akkari, N.; Malik, M. G. A.; Akyildiz, I. F.
    Cognitive radio sensor networks (CRSNs) have been proposed to serve as a reliable, robust, and efficient communications infrastructure that can address both the existing and future energy management requirements of the smart grid. The existing and envisioned applications of CRSN-based smart grid include substation automation, overhead transmission line monitoring, home energy management, advanced metering infrastructure, wide-area situational awareness, demand response, outage management, distribution automation, asset management. To realize these applications, in this paper, honey bee mating optimization-based routing and cooperative channel assignment algorithms have been proposed. The developed framework significantly decreases the probability of packet loss and preserves high link quality among sensor nodes in harsh smart grid spectrum environments. The proposed approach performance has been evaluated in terms of packet delivery ratio, delay, and energy consumption demonstrating that it has successfully addressed the QoS requirements of most of the SG applications presented. (C) 2017 Elsevier B.V. All rights reserved.
  • Article
    Citation - WoS: 12
    Citation - Scopus: 13
    Collecting Smart Meter Data via Public Transportation Buses
    (Inst Engineering Technology-IET, 2016-10) Bilgin, Bilal Erman; Baktir, Selcuk; Gungor, Vehbi Cagri
    With advances in technology, wireless sensor networks (WSNs) have found new applications and their popularity has increased dramatically. In several applications, WSNs have the potential to replace wired data communication systems, e.g. in vehicular ad hoc networks (VANETs) they are the natural option for data communication. WSNs are also proposed for data communication in the emerging smart grid. In this study, the authors merge these two application domains, i.e. VANET and smart grids, and propose a novel solution for effective smart grid data communication. The authors' proposed scheme achieves the task of collecting data from smart meters by utilising VANETs. Using network simulator-2 and with different routing protocols, the authors have performed simulations and shown the efficacy of their scheme in terms of average end-to-end delay and delivery ratio.
  • Article
    Citation - WoS: 12
    Analyzing Lifetime of Energy Harvesting Wireless Multimedia Sensor Nodes in Industrial Environments
    (Elsevier Science Bv, 2018-05) Tekin, Nazli; Erdem, H. Emre; Gungor, V. Cagri
    Recently, there has been a great demand for multimedia communication using Wireless Multimedia Sensor Networks (WMSNs) in industrial environments thanks to their low cost, flexibility, and rapid deployment. However, WMSNs face a major challenge of limited lifetime due to their limited battery capacity. Compared to regular data transmission, multimedia data transmission causes higher energy consumption because of larger data sizes leading to faster depletion of sensor node's batteries. The objective of this paper is to analytically quantify the impact of different energy harvesting methods based on vibration, indoor solar, and temperature difference as well as Fast-Zonal DCT and BinDCT based image compression methods on the lifetime of Telos and Mica2 sensor nodes deployed in indoor industrial environment. Performance results show that energy harvesting and image compression techniques improve lifetime of Mica2 and Telos motes by 51.8% and 25.8%, respectively when used with proper power management methods. (C) 2017 Published by Elsevier B.V.
  • Article
    Citation - WoS: 232
    Citation - Scopus: 294
    A Survey on Wireless Sensor Networks for Smart Grid
    (Elsevier, 2015-11) Fadel, Etimad; Gungor, V. C.; Nassef, Laila; Akkari, Nadine; Maik, M. G. Abbas; Almasri, Suleiman; Akyildiz, Ian F.; Abbas Malik, M.G.
    The traditional power grid in many countries suffers from high maintenance costs and scalability issues along with the huge expense of building new power stations, and lack of efficient system monitoring that could increase the overall performance by acting proactively in preventing potential failures. To address these problems, a next-generation electric power system, called the smart grid (SG), has been proposed as an evolutionary system for power generation, transmission, and distribution. To this end, the SGs utilize renewable energy generation, smart meters and modern sensing and communication technologies for effective power system management, and hence, succeeding in addressing many of the requirements of a modern power grid system while significantly increase its performance. Recently, wireless sensor networks (WSNs) have been recognized as a promising technology to achieve seamless, energy efficient, reliable, and low-cost remote monitoring and control in SG applications. In these systems, the required information can be provided to electric utilities by wireless sensor systems to enable them to achieve high system efficiency. The real-time information gathered from these sensors can be analyzed to diagnose problems early and serve as a basis for taking remedial action. In this paper, first WSN-based SG applications have been explored along with their technical challenges. Then, design challenges and protocol objectives have been discussed for WSN-based SG applications. After exploring applications and design challenges, communication protocols for WSN-based SG applications have been explained in detail. Here, our goal is to elaborate on the role of WSNs for smart grid applications and to provide an overview of the most recent advances in MAC and routing protocols for WSNs in this timely and exciting field. (C) 2015 Elsevier B.V. All rights reserved.
  • Article
    Citation - WoS: 15
    Citation - Scopus: 16
    Stacking Ensemble Learning-Based Wireless Sensor Network Deployment Parameter Estimation
    (Springer Heidelberg, 2023) Akbas, Ayhan; Buyrukoglu, Selim
    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.