Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 24Citation - Scopus: 32Routing Protocol Design Guidelines for Smart Grid Environments(Elsevier, 2014-02) Temel, Samil; Gungor, Vehbi Cagri; Kocak, TaskinThe evaluation of the current electric power grid with novel communication facilities is one of the most challenging and exciting issues of the 21st century. The modern grid technology is called the smart grid in the sense that it utilizes digital communication technologies to monitor and control the grid environments, which ultimately require novel communication techniques to be adapted to the system. Wireless sensor networks (WSN) have. recently been considered as a cost-effective technology for the realization of reliable remote monitoring systems for smart grid. However, problems such as noise, interference and fading in smart grid environments, make reliable and energy-efficient multi-hop routing a difficult task for WSNs in smart grid. Our main goal is to describe advantages and applications of WSNs for smart grid and motivate the research community to further investigate this promising research area. In this study we have investigated and experimented some of the well-known on-demand, table-driven and QoS-aware routing protocols, in terms of packet delivery ratio, end-to-end delay, and energy consumption to show the advantages and disadvantages of each routing protocol type in different smart grid spectrum environments. The environmental characteristics which are based on real-world field tests are injected into ns-2 Network Simulator and the performance of four different multi-hop routing protocols is investigated. Also, we have shown that traditional multi-hop routing protocols cannot deliver adequate performance on smart grid environments. Hence, based on our simulation results, we present some guidelines on how to design routing protocols specifically for smart grid environments. (C) 2013 Elsevier B.V. All rights reserved.Article Citation - WoS: 39Citation - Scopus: 49Quality-of Differentiation in Single-Path and Multi-Path Routing for Wireless Sensor Network-Based Smart Grid Applications(Elsevier, 2014-11) Sahin, Dilan; Gungor, Vehbi Cagri; Kocak, Taskin; Tuna, GurkanElectrical grid is one of the most important infrastructure of the modern nation. However, power grid has been aged over 100 years and prone to major failures. The imbalance between power demand and supply, the equipment failures and the lack of comprehensive monitoring and control capabilities are other important signs to take incremental steps for switching to a smarter power grid with effective communication, automation and monitoring skills. This new concept is named as smart grid, which is a modern power grid system with advanced communication, monitoring, sensing and control capabilities. Wireless sensor network (WSN) concept places an important role in this modernization process of the power grid with its efficient and low-cost deployment characteristics. However, harsh and complex smart grid environmental conditions, dynamic topology changes, connectivity problems, interference and fading may pose some challenges for the communication performance of WSN technology. For this objective, in this paper, the use of multi-path and single-path QoS-aware routing algorithms under harsh SG environmental conditions is investigated in order to evaluate their service differentiation capabilities in reliability and timeliness domains. In this regard, this study is an important step towards developing novel routing protocols specifically designed for smart grid environments. (C) 2014 Elsevier B.V. All rights reserved.Article Citation - WoS: 145Citation - Scopus: 177Packet Size Optimization in Wireless Sensor Networks for Smart Grid Applications(IEEE-Inst Electrical Electronics Engineers Inc, 2017-03) Kurt, Sinan; Yildiz, Huseyin Ugur; Yigit, Melike; Tavli, Bulent; Gungor, Vehbi CagriWireless sensor networks (WSNs) are envi-sioned to be an important enabling technology for smart grid (SG) due to the low cost, ease of deployment, and versatility of WSNs. Limited battery energy is the tightest resource constraint on WSNs. Transmission power control and data packet size optimization are powerful mechanisms for prolonging network lifetime and improving energy effi-ciency. Increasing transmission power will reduce the bit error rate (BER) on some links, however, utilizing the high-est power level will lead to inefficient use of battery energy because on links with low path loss achieving low BER is possible without the need to use the highest power level. Utilizing a large packet size is beneficial for increasing the payload-to-overhead ratio, yet, lower packet sizes have the advantage of lower packet error rate. Furthermore, trans-mission power level assignment and packet size selection are interrelated. Therefore, joint optimization of transmission power level and packet size is of utmost importance in WSN lifetime maximization. In this study, we construct a de-tailed link layer model by employing the characteristics of Tmote Sky WSN nodes and channel characteristics based on actual measurements of SG path loss for various envi-ronments. A novel mixed integer programming framework is created by using the aforementioned link layer model for WSN lifetime maximization by joint optimization of trans-mission power level and data packet size. We analyzed the WSN performance by systematic exploration of the parameter space for various SG environments through the numer-ical solutions of the optimization model.Article Citation - WoS: 18Citation - Scopus: 21Lifetime Analysis of Wireless Sensor Nodes in Different Smart Grid Environments(Springer, 2014-05-03) Eris, Cigdem; Saimler, Merve; Gungor, Vehbi Cagri; Fadel, Etimad; Akyildiz, Ian F.Wireless sensor networks (WSNs) can help the realization of low-cost power grid automation systems where multi-functional sensor nodes can be used to monitor the critical parameters of smart grid components. The WSN-based smart grid applications include but not limited to load control, power system monitoring and control, fault diagnostics, power fraud detection, demand response, and distribution automation. However, the design and implementation of WSNs are constrained by energy resources. Sensor nodes have limited battery energy supply and accordingly, power aware communication protocols have been developed in order to address the energy consumption and prolong their lifetime. In this paper, the lifetime of wireless sensor nodes has been analyzed under different smart grid radio propagation environments, such as 500 kV substation, main power control room, and underground network transformer vaults. In particular, the effects of smart grid channel characteristics and radio parameters, such as path loss, shadowing, frame length and distance, on a wireless sensor node lifetime have been evaluated. Overall, the main objective of this paper is to help network designers quantifying the impact of the smart grid propagation environment and sensor radio characteristics on node lifetime in harsh smart grid environments.Article Citation - WoS: 64Citation - Scopus: 76EDHRP: Energy Efficient Event Driven Hybrid Routing Protocol for Densely Deployed Wireless Sensor Networks(Academic Press Ltd- Elsevier Science Ltd, 2015-12) Faheem, Muhammad; Abbas, Muhammad Zahid; Tuna, Gurkan; Gungor, Vehbi CagriEfficient management of energy resources is a challenging research area in Wireless Sensor Networks (WSNs). Recent studies have revealed that clustering is an efficient topology control approach for organizing a network into a connected hierarchy which balances the traffic load of the sensor nodes and improves the overall scalability and the lifetime of WSNs. Inspired by the advantages of clustering techniques, we have three main contributions in this paper. First, we propose an energy efficient cluster formation algorithm called Active Node Cluster Formation (ANCF). The core aim to propose ANCF algorithm is to distribute heavy data traffic and high energy consumption load evenly in the network by offering unequal size of clusters in the network. The developed scheme appoints each cluster head (CH) near to the sink and sensing event while the remaining set of the cluster heads (CHs) are appointed in the middle of each cluster to achieve the highest level of energy efficiency in dense deployment. Second, we propose a lightweight sensing mechanism called Active Node Sensing Algorithm (ANSA). The key aim to propose the ANSA algorithm is to avoid high sensing overlapping data redundancy by appointing a set of active nodes in each cluster with satisfy coverage near to the event. Third, we propose an Active Node Routing Algorithm (ANRA) to address complex inter and intra cluster routing issues in highly dense deployment based on the node dominating values. Extensive experimental studies conducted through network simulator NCTUNs 6.0 reveal that our proposed scheme outperforms existing routing techniques in terms of energy efficiency, end-to-end delay and data redundancy, congestion management and setup robustness. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 12Citation - Scopus: 13Collecting Smart Meter Data via Public Transportation Buses(Inst Engineering Technology-IET, 2016-10) Bilgin, Bilal Erman; Baktir, Selcuk; Gungor, Vehbi CagriWith 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.Data Paper Citation - WoS: 34Citation - Scopus: 41Big Data Acquired by Internet of Things-Enabled Industrial Multichannel Wireless Sensors Networks for Active Monitoring and Control in the Smart Grid Industry 4.0(Elsevier, 2021-04) Faheem, Muhammad; Fizza, Ghulam; Ashraf, Muhammad Waqar; Butt, Rizwan Aslam; Ngadi, Md. Asri; Gungor, Vehbi CagriSmart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in SGI4.0, the reliable and efficient gathering and transmission of the observed information from the Internet of Things (IoT)-enabled Cyberphysical systems, such as sensors located in remote places to the control center is the biggest challenge for the Industrial Multichannel Wireless Sensors Networks (IMWSNs). This is due to the harsh nature of the smart grid environment that causes high noise, signal fading, multipath effects, heat, and electromagnetic interference, which reduces the transmission quality and trigger errors in the IMWSNs. Thus, an efficient monitoring and real-time control of unexpected changes in the power generation and distribution processes is essential to guarantee the quality of service (QoS) re-quirements in the smart grid. In this context, this paper de-scribes the dataset contains measurements acquired by the IMWSNs during events monitoring and control in the smart grid. This work provides an updated detail comparison of our proposed work, including channel detection, channel assign-ment, and packets forwarding algorithms, collectively called CARP [1] with existing G-RPL [2] and EQSHC [3] schemes in the smart grid. The experimental outcomes show that the dataset and is useful for the design, development, testing, and validation of algorithms for real-time events monitoring and control applications in the smart grid. (C) 2021 The Authors. Published by Elsevier Inc.