WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 4Citation - Scopus: 6Traffic Aware Cyclic Sleep-Based Power Consumption Model for a Passive Optical Network(Wiley, 2022-02-28) Butt, Rizwan Aslam; Faheem, Muhammad; Anwar, Muhammad; Mohammadani, Khalid H.; Idrus, Sevia M.For a network, a power consumption model is an important tool to test the performance of a network process for different traffic loads. In a Passive optical network (PON), the optical network unit (ONU) is responsible for the major power consumption of PON. Both IEEE and ITU have standardized a cyclic sleep process (CSP) for ONU energy conservation. In next-generation PON; TWDM and XGS PON, the ONU power contribution has increased further due to higher number of ONUs and ONU being tunable. Therefore, an accurate power consumption model of the CSP process for energy efficiency studies under different traffic conditions is of prime importance. The existing CSP power consumption models do not depict the CSP process accurately especially the inactivity of the ONU in the asleep and sleep aware states are not taken into account which reduce the accuracy of the model. The proposed inactivity aware model (IAM) overcomes these gaps and very accurately models the CSP process, as evident from the results, which are better than earlier model results and quite close to earlier published simulation results. The model is also validated through a simulation-based study and the simulation results are observed to be very close to the model results with only a 5% deviation.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: 74Citation - Scopus: 89QERP: 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 CagriQuality-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: 37Citation - Scopus: 35Performance Prediction and Adaptation for Database Management System Workload Using Case-Based Reasoning Approach(Pergamon-Elsevier Science Ltd, 2018-07) Raza, Basit; Kumar, Yogan Jaya; Malik, Ahmad Kamran; Anjum, Adeel; Faheem, MuhammadWorkload management in a Database Management System (DBMS) has become difficult and challenging because of workload complexity and heterogeneity. During and after execution of the workload, it is hard to control and handle the workload. Before executing the workload, predicting its performance can help us in workload management. By knowing the type of workload in advance, we can predict its performance in an adaptive way that will enable us to monitor and control the workload, which ultimately leads to performance tuning of the DBMS. This study proposes a predictive and adaptive framework named as the Autonomic Workload Performance Prediction (AWPP) framework. The proposed AWPP framework predicts and adapts the DBMS workload performance on the basis of information available in advance before executing the workload. The Case-Based Reasoning (CBR) approach is used to solve the workload management problem. The proposed CBR approach is compared with other machine learning techniques. To validate the AWPP framework, a number of benchmark workloads of the Decision Support System (DSS) and the Online Transaction Processing (OLTP) are executed on the MySQL DBMS. For preparation of training and testing data, we executed more than 1000 TPC-H and TPC-C like workloads on a standard data set. The results show that our proposed AWPP framework through CBR modeling performs better in predicting and adapting the DBMS workload. DBMSs algorithms can be optimized for this prediction and workload can be controlled and managed in a better way. In the end, the results are validated by performing post-hoc tests. (C) 2018 Elsevier Ltd. All rights reserved.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: 34Citation - Scopus: 44LRP: Link Quality-Aware Queue-Based Spectral Clustering Routing Protocol for Underwater Acoustic Sensor Networks(Wiley, 2016-12-20) Faheem, Muhammad; Tuna, Gurkan; Gungor, Vehbi CagriRecently, underwater acoustic sensor networks (UASNs) have been considered as a promising approach for monitoring and exploring the oceans in lieu of traditional underwater wireline instruments. As a result, a broad range of applications exists ranging from oil industry to aquaculture and includes oceanographic data collection, disaster prevention, offshore exploration, assisted navigation, tactical surveillance, and pollution monitoring. However, the unique characteristics of underwater acoustic communication channels, such as high bit error rate, limited bandwidth, and variable delay, lead to a large number of packet drops, low throughput, and significant waste of energy because of packets retransmission in these applications. Hence, designing an efficient and reliable data communication protocol between sensor nodes and the sink is crucial for successful data transmission in underwater applications. Accordingly, this paper is intended to introduce a novel nature-inspired evolutionary link quality-aware queue-based spectral clustering routing protocol for UASN-based underwater applications. Because of its distributed nature, link quality-aware queue-based spectral clustering routing protocol successfully distributes network data traffic load evenly in harsh underwater environments and avoids hotspot problems that occur near the sink. In addition, because of its double check mechanism for signal to noise ratio and Euclidean distance, it adopts opportunistically and provides reliable dynamic cluster-based routing architecture in the entire network. To sum up, the proposed approach successfully finds the best forwarding relay node for data transmission and avoids path loops and packet losses in both sparse and densely deployed UASNs. Our experimental results obtained in a set of extensive simulation studies verify that the proposed protocol performs better than the existing routing protocols in terms of data delivery ratio, overall network throughput, end-to-end delay, and energy efficiency.Article Handling Incomplete Data Classification Using Imputed Feature Selected Bagging (IFBAG) Method(Ios Press, 2021-07-09) Khan, Ahmad Jaffar; Raza, Basit; Shahid, Ahmad Raza; Kumar, Yogan Jaya; Faheem, Muhammad; Alquhayz, HaniAlmost all real-world datasets contain missing values. Classification of data with missing values can adversely affect the performance of a classifier if not handled correctly. A common approach used for classification with incomplete data is imputation. Imputation transforms incomplete data with missing values to complete data. Single imputation methods are mostly less accurate than multiple imputation methods which are often computationally much more expensive. This study proposes an imputed feature selected bagging (IFBag) method which uses multiple imputation, feature selection and bagging ensemble learning approach to construct a number of base classifiers to classify new incomplete instances without any need for imputation in testing phase. In bagging ensemble learning approach, data is resampled multiple times with substitution, which can lead to diversity in data thus resulting in more accurate classifiers. The experimental results show the proposed IFBag method is considerably fast and gives 97.26% accuracy for classification with incomplete data as compared to common methods used.Article Citation - WoS: 45Citation - Scopus: 57Energy Efficient Multi-Objective Evolutionary Routing Scheme for Reliable Data Gathering in Internet of Underwater Acoustic Sensor Networks(Elsevier, 2019-10) Faheem, Muhammad; Ngadi, Asri; Gungor, Vehbi Cagri; Ngadi, Md AsriEarth's surface is covered with two-thirds of water. The marine world covers the lakes, rivers and sea and is rich in natural resources largely unexplored by human beings. Recently, underwater wireless sensor network (UWSN) with the advancement in the Internet of underwater smart things has emerged as promising networking techniques to explore the mysteries of vastly unexplored ocean environments for several underwater applications. These applications include offshore exploration, pollution monitoring, disaster prevention, oceanographic data collection, offshore oil fields monitoring, tactical surveillance applications and several others. However, the underwater channel impairments caused by multipath effects, fading, bit errors, variable and high latency and low bandwidth severely limits the data transmission reliability for UWSNs-based applications. This results in poor quality-aware data gathering in UWSNs. Therefore, designing a quality of service (QoS)-aware data gathering protocol to monitor and explore oceans is challenging in the underwater environments. In this paper, we propose a bio-inspired multi-objective evolutionary routing protocol (called MERP) for UWSNs-based applications. The designed routing protocol exploits the features of the natural evolution of the multi-objective genetic algorithm in order to provide reliable and energy-aware information gathering in UWSNs. The extensive simulation results show that the developed protocol attains its defined goals compared to existing UWSNs-based routing protocols during monitoring and exploring underwater environments. (C) 2019 Elsevier B.V. All rights reserved.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: 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.