WoS İndeksli Yayınlar Koleksiyonu

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

Browse

Filters

2014 - 2019152020 - 202515

Settings

Author: search.filters.author.Gungor, Vehbi CagriScopus Q: search.filters.scopusQuartile.Q1

Search Results

Now showing 1 - 10 of 30
  • Article
    Citation - WoS: 11
    Citation - Scopus: 13
    Wireless Sensor Network-Based Communication for Cooperative Simultaneous Localization and Mapping
    (Pergamon-Elsevier Science Ltd, 2015-01) Tuna, Gurkan; Gungor, Vehbi Cagri; Potirakis, Stelios M.; Zeadally, Sherali
    This paper presents a novel approach of using a Wireless Sensor Network (WSN) as the communication means for Multi-Robot, Cooperative, Simultaneous Localization and Mapping (CSLAM) applications investigating the associated design challenges and suggesting corresponding solutions. Although the proposed approach brings several benefits including an increased coverage and communication range, self-organization capabilities, quick deployment, and flexible architecture, the realization is interrelated with performance in terms of energy efficiency and reliability. In this respect, the applicability of the WSNs for the presented approach is investigated. Centralized and distributed map merging methods in WSN-based CSLAM are evaluated in detail and the impacts of packet delays and losses on the performance of CSLAM algorithms are shown. Additionally, the involved network congestion and contention dynamics are presented, while the effects of observation range, speed, time intervals between observations, and odometry readings on the SLAM accuracy are shown based on an extensive set of simulation studies. (C) 2014 Elsevier Ltd. All rights reserved.
  • Article
    Citation - WoS: 11
    Citation - Scopus: 17
    The Impact of Error Control Schemes on Lifetime of Energy Harvesting Wireless Sensor Networks in Industrial Environments
    (Elsevier, 2020-06) Tekin, Nazli; Gungor, Vehbi Cagri
    Due 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: 24
    Citation - Scopus: 32
    Routing Protocol Design Guidelines for Smart Grid Environments
    (Elsevier, 2014-02) Temel, Samil; Gungor, Vehbi Cagri; Kocak, Taskin
    The 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: 63
    Citation - Scopus: 107
    Research Article Energy Consumption of On-Device Machine Learning Models for IoT Intrusion Detection
    (Elsevier, 2023-04) Tekin, Nazli; Acar, Abbas; Aris, Ahmet; Uluagac, A. Selcuk; Gungor, Vehbi Cagri
    Recently, Smart Home Systems (SHSs) have gained enormous popularity with the rapid development of the Internet of Things (IoT) technologies. Besides offering many tangible benefits, SHSs are vulnerable to attacks that lead to security and privacy concerns for SHS users. Machine learning (ML)-based Intrusion Detection Systems (IDS) are proposed to address such concerns. Conventionally, ML models are trained and tested on computationally powerful platforms such as cloud services. Nevertheless, the data shared with the cloud is vulnerable to privacy attacks and causes latency, which decreases the performance of real-time applications like intrusion detection systems. Therefore, on-device ML models, in which the user data is kept locally, have emerged as promising solutions to ensure the security and privacy of the data for real-time applications. However, performing ML tasks requires high energy consumption. To the best of our knowledge, no study has been conducted to analyze the energy consumption of ML-based IDS. Therefore, in this paper, we perform a comparative analysis of on-device ML algorithms in terms of energy consumption for IoT intrusion detection applications. For a thorough analysis, we study the training and inference phases separately. For training, we compare the cloud computing-based ML, edge computing-based ML, and IoT device-based ML approaches. For the inference, we evaluate the TinyML approach to run the ML algorithms on tiny IoT devices such as Micro Controller Units (MCUs). Comparative performance evaluations show that deploying the Decision Tree (DT) algorithm on-device gives better results in terms of training time, inference time, and power consumption.
  • Article
    Citation - WoS: 39
    Citation - Scopus: 49
    Quality-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, Gurkan
    Electrical 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: 31
    Citation - Scopus: 41
    QoSRP: A Cross-Layer QoS Channel-Aware Routing Protocol for the Internet of Underwater Acoustic Sensor Networks
    (MDPI, 2019-11-02) Faheem, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Alquhayz, Hani; Ashraf, Muhammad Waqar; Shah, Syed Bilal; Gungor, Vehbi Cagri
    Quality of service (QoS)-aware data gathering in static-channel based underwater wireless sensor networks (UWSNs) is severely limited due to location and time-dependent acoustic channel communication characteristics. This paper proposes a novel cross-layer QoS-aware multichannel routing protocol called QoSRP for the internet of UWSNs-based time-critical marine monitoring applications. The proposed QoSRP scheme considers the unique characteristics of the acoustic communication in highly dynamic network topology during gathering and relaying events data towards the sink. The proposed QoSRP scheme during the time-critical events data-gathering process employs three basic mechanisms, namely underwater channel detection (UWCD), underwater channel assignment (UWCA) and underwater packets forwarding (UWPF). The UWCD mechanism finds the vacant channels with a high probability of detection and low probability of missed detection and false alarms. The UWCA scheme assigns high data rates channels to acoustic sensor nodes (ASNs) with longer idle probability in a robust manner. Lastly, the UWPF mechanism during conveying information avoids congestion, data path loops and balances the data traffic load in UWSNs. The QoSRP scheme is validated through extensive simulations conducted by NS2 and AquaSim 2.0 in underwater environments (UWEs). The simulation results reveal that the QoSRP protocol performs better compared to existing routing schemes in UWSNs.
  • Article
    Citation - WoS: 74
    Citation - Scopus: 89
    QERP: Quality-Of (QoS) Aware Evolutionary Routing Protocol for Underwater Wireless Sensor Networks
    (IEEE-Inst Electrical Electronics Engineers Inc, 2018-09) Faheem, Muhammad; Tuna, Gurkan; Gungor, Vehbi Cagri
    Quality-of-service (QoS) aware reliable data delivery is a challenging issue in underwater wireless sensor networks (UWSNs). This is clue to impairments of the acoustic transmission caused by excessive noise, extremely long propagation delays, high bit error rate, low bandwidth capacity, multipath effects, and interference. To address these challenges, meet the commonly used UWSN performance indicators, and overcome the inefficiencies of the existing clustering-based routing schemes, a novel QoS aware evolutionary cluster based routing protocol (QERP) has been proposed for UWSN-based applications. The proposed protocol improves packet delivery ratio, and reduces average end-to-end delay and overall network energy consumption. Our comparative performance evaluations demonstrate that QERP is successful in achieving low network delay, high packet delivery ratio, and low energy consumption.
  • Article
    Citation - WoS: 21
    Citation - Scopus: 24
    Performance Evaluation of Cloud Computing Platforms Using Statistical Methods
    (Pergamon-Elsevier Science Ltd, 2014-07) Atas, Gultekin; Gungor, Vehbi Cagri
    Cloud computing is a very attractive research topic. Many studies have examined the infrastructure as a service and software as a service aspects of cloud computing; however, few studies have focused on platform as a service (PaaS). According to recent reports, demand for enterprise PaaS solutions will increase continuously. However, different sectors require different types of PaaS applications and computing resources. Therefore, an evaluation and ranking framework for PaaS solutions according to application needs is required. To address this need, this study presents the most essential aspects of PaaS solutions and provides a framework for evaluating the performance of PaaS providers. It also proposes a suitable set of benchmarking algorithms that can help determine the most appropriate PaaS provider based on different resource needs and application requirements. Performance evaluations of three well-known cloud computing PaaS providers were conducted using the analytic hierarchy process and the logic scoring of preference methods. (C) 2014 Elsevier Ltd. All rights reserved.
  • Article
    Citation - WoS: 145
    Citation - Scopus: 177
    Packet 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 Cagri
    Wireless 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: 80
    Citation - Scopus: 95
    Packet Size Optimization for Lifetime Maximization in Underwater Acoustic Sensor Networks
    (IEEE-Inst Electrical Electronics Engineers Inc, 2019-02) Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri; Tavli, Bulent
    Recently, underwater acoustic sensor networks (UASNs) have been proposed to explore underwater environments for scientific, commercial, and military purposes. However, long propagation delays, high transmission losses, packet drops, and limited bandwidth in underwater propagation environments make realization of reliable and energy-efficient communication a challenging task for UASNs. To prolong the lifetime of battery-limited UASNs, two critical factors (i.e., packet size and transmission power) play vital roles. At one hand, larger packets are vulnerable to packet errors, while smaller packets are more resilient to such errors. In general, using smaller packets to avoid bit errors might be a good option. However, when small packets are used, more frames should be transmitted due to the packet fragmentation, and hence, network overhead and energy consumption increases. On the other hand, increasing transmission power reduces frame errors, but this would result in unnecessary energy consumption in the network. To this end, the packet size and transmission power should be jointly considered to improve the network lifetime. In this study, an optimization framework via an integer linear programming (ILP) has been proposed to maximize the network lifetime by joint optimization of the transmission power and packet size. In addition, a realistic link-layer energy consumption model is designed by employing the physical layer characteristics of UASNs. Extensive numerical analysis through the optimization model has been also performed to investigate the tradeoffs caused by the transmission power and packet size quantitatively.