WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Conference Object Citation - WoS: 30Citation - Scopus: 38Software Defined Communication Framework for Smart Grid to Meet Energy Demands in Smart Cities(IEEE, 2019-04) Faheem, Muhammad; Umar, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Ngadi, Md. Asri; Gungor, Vehbi CagriIn smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG.Article Citation - WoS: 52Citation - Scopus: 62MGRP: Mobile Sinks-Based QoS-Aware Data Gathering Protocol for Wireless Sensor Networks-Based Smart Grid Applications in the Context of Industry 4.0-Based on Internet of Things(Elsevier Science Bv, 2018-05) Faheem, Muhammad; Gungor, V. C.The recent advances in internet of things (IoT) and industrial wireless sensor networks (IWSNs) paradigm provide a promising opportunity for upgrading todays elderly electricity industrial systems and even allow the fourth stage of the industrial revolution, referred to as smart grid industry (SGI) 4.0. In SGI 4.0 paradigm, the WSNs are considered as promising solutions due to their advantages, such as cable replacement, ease of deployment, flexibility, and cost reduction. However, harsh and complex smart grid (SG) environments pose great challenges to guarantee reliable communication for WSNs-based SG applications due to equipment noise, electromagnetic interference, multipath effects and fading in SG environments. This results in deteriorating the quality-of-service (QoS) requirements as well as the network lifetime of multi-hop communication-based WSNs for SG applications. Thus, for SGI 4.0 paradigm to come true, a WSN-based highly reliable communication infrastructure is crucial that will wirelessly connect and integrate power system components for more efficient, reliable, and intelligent operations of the next-generation electricity power grids. To address these challenges, in this paper a novel multi-mobile sinks-based QoS-aware data gathering protocol (called MQRP) for WSNs-based SG applications has been proposed to empower SGI 4.0. The extensive simulations study is carried through a network simulation tool called EstiNet9.0. The obtained experimental facts show that the proposed scheme has not only improved the QoS performance metrics, such as packet delivery ratio, memory utilization, control message overhead, residual energy, network lifetime, and throughput, but also reduced packet error rate and end-to-end delay compared to existing data collection schemes. (C) 2017 Elsevier B.V. All rights reserved.Article Citation - WoS: 28Citation - Scopus: 31Capacity and Spectrum-Aware Communication Framework for Wireless Sensor Network-Based Smart Grid Applications(Elsevier Science Bv, 2017-08) Faheem, Muhammad; Gungor, Vehbi Cagri; Cagri Gungor, VehbiRecently, wireless sensor networks (WSNs) have been widely recognized as a promising technology for enhancing various aspects of smart grid and realizing the vision of next-generation electric power system in a cost-effective and efficient manner. However, recent field tests show that wireless links in smart grid environments have higher packet error rates and variable link capacity because of dynamic topology changes, obstructions, electromagnetic interference, equipment noise, multipath effects, and fading. To overcome these communication challenges, in this paper, we propose a data capacity-aware channel assignment (DCA) and fish bone routing (FBR) algorithm for WSN-based smart grid applications. The proposed DCA framework deals with the channel scarcities by dynamically switching between different spectrum bands and employs a network for organizing WSN into a highly stable connected hierarchy. In addition, the proposed FBR mechanism provides robust loop free data paths and avoids high transmission cost, excessive end-to-end delay and restricts unnecessary multi-hop data transmission from the source to destination in the network. Thus, it significantly reduces the probability of data packet loss and preserves stable link qualities among sensor nodes for load balancing and prolonging the lifetime of wireless sensor networks in harsh smart grid environments. Comparative performance evaluations show that our proposed schemes outperform the existing communication architectures in terms of data packet delivery, communication delay and energy consumption.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.