Department of Computer Engineering and Computational Sciences

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http://hdl.handle.net/20.500.12519/624

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Browsing Department of Computer Engineering and Computational Sciences by Title

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    A 3G/WiFi-enabled 6LoWPAN-based U-healthcare system for ubiquitous real-time monitoring and data logging
    (IEEE Computer Society, 2014) Tabish, Rohan ; Ghaleb, Abdulaziz M. ; Hussein, Rima ; Touati, Farid ; Mnaouer, Adel Ben ; Khriji, Lazhar ; Rasid, Mohd Fadlee A.
    Ubiquitous healthcare (U-healthcare) systems are expected to offer flexible and resilient high-end technological solutions enabling remote monitoring of patients health status in real-time and provisioning of feedback and remote actions by healthcare providers. In this paper, we present a 6LowPAN based U-healthcare platform that contributes to the realization of the above expectation. The proposed system comprises two sensor nodes sending temperature data and ECG signals to a remote processing unit. These sensors are being assigned an IPv6 address to enable the Internet-of-Things (IoT) functionality. A 6LowPAN-enabled edge router, connected to a PC, is serving as a base station through a serial interface, to collect data from the sensor nodes. Furthermore, a program interfacing through a Serial-Line-Internet-Protocol (SLIP) and running on the PC provides a network interface that receives IPv6 packets from the edge router. The above system is enhanced by having the application save readings from the sensors into a file that can be downloaded by a remote server using a free Cloud service such as UbuntuOne. This enhancement makes the system robust against data loss especially for outdoor healthcare services, where the 3G/4G connectivity may get lost because of signal quality fluctuations. The system provided a proof of concept of successful remote U-healthcare monitoring illustrating the IoT functionality and involving 3G/4G connectivity while being enhanced by a cloud-based backup. © 2014 IEEE.
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    A survey of blockchain-based solutions for IoTs, VANETs, and FANETs
    (IGI Global, 2021-06-11) Abdelhafidh, Maroua ; Charef, Nadia ; Mnaouer, Adel Ben ; Chaari, Lamia
    Recently, the internet of things (IoT) has gained popularity as an enabling technology for wireless connectivity of mobile and/or stationary devices providing useful services for the general public in a collaborative manner. Mobile ad-hoc networks (MANETs) are regarded as a legacy enabling technology for various IoT applications. Vehicular ad-hoc networks (VANETs) and flying ad-hoc networks (FANETs) are specific extensions of MANETs that are drivers of IoT applications. However, IoT is prone to diverse attacks, being branded as the weakest link in the networking chain requiring effective solutions for achieving an acceptable level of security. Blockchain (BC) technology has been identified as an efficient method to remedy IoT security concerns. Therefore, this chapter classifies the attacks targeting IoT, VANETs, and FANETs systems based on their vulnerabilities. This chapter explores a selection of blockchain-based solutions for securing IoT, VANETs, and FANETs and presents open research directions compiled out of the presented solutions as useful guidelines for the readers. © 2021, IGI Global.
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    AI-based Energy Model for Adaptive Duty Cycle Scheduling in Wireless Networks
    (Institute of Electrical and Electronics Engineers Inc., 2021) Charef, Nadia ; Mnaouer, Adel Ben ; Bouachir, Ouns
    The vast distribution of low-power devices in IoT applications requires robust communication technologies that ensure high-performance level in terms of QoS, light-weight computation, and security. Advanced wireless technologies (i.e. 5G and 6G) are playing an increasing role in facilitating the deployment of IoT applications. To prolong the network lifetime, energy harvesting is an essential technology in wireless networks. Nevertheless, maintaining energy sustainability is difficult when considering high QoS requirements in IoT. Therefore, an energy management technique that ensures energy efficiency and meets QoS is needed. Energy efficiency in duty cycling solutions needs novel energy management techniques to address these challenges and achieve a trade-off between energy efficiency and delay. Predictive models (i.e., based on AI and ML techniques) represent useful tools that encapsulate the stochastic nature of harvested energy in duty cycle scheduling. The conventional predictive model relies on environmental parameters to estimate the harvested energy. Instead, Artificial Intelligence (AI) allows for recursive prediction models that rely on past behavior of harvested and consumed energy. This is useful to achieve better precision in energy estimation and extend the limit beyond predictive models directed solely for energy sources that exhibit periodic behavior. In this paper, we explore the usage of a ML model to enhance the performance of duty cycle scheduling. The aim is to improve the QoS performance of the proposed solution. To assess the performance of the proposed model, it was simulated using the INET framework of the OMNet++ simulation environment. The results are compared to an enhanced IEEE 802.15.4 MAC protocol from the literature. The results of the comparative study show clear superiority of the proposed AI-based protocol that testified to better use of energy estimation for better management of the duty cycling at the MAC sublayer. © 2021 IEEE.
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    An Autonomous Multi-Variable Outdoor Air Quality Mapping Wireless Sensors IoT Node for Qatar
    (Institute of Electrical and Electronics Engineers Inc., 2020-06) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Mnaouer, Adel Ben
    In all outdoor long haul air quality monitoring and mapping applications, sensing accuracy, the sustainability of telemetry, and resilience in node systems and operation are major challenges. The severity of these challenges varies depending on the moderateness and harshness of the climate of observation. In this work, an autonomous environmentally powered, sensors self-diagnostic/calibration, and context-aware IoT-based telemetry for multi-variable sensing node is being proposed. In this node, photo-voltaic and piezoelectric energy harvesters contributed to self-calibration and sustainable measurement of temperature (in °C), humidity (in %), pressure (in bar), geo-position (in NMEA format), volatile organic compounds-VOC (in ppm), particulate matter PM (in ppm), ozone (in Dobson Unit), Carbon mono-oxide (in ppm), Nitrogen dioxide (in ppm), and Sulphur dioxide (in ppm). Results have shown that the proposed system worked autonomously for days and optimized the real-time air quality mapping for the chosen geo-spatial cluster, i.e. Qatar University. © 2020 IEEE.
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    An autoregressive time delay neural network for speech steganalysis
    (Institute of Electrical and Electronics Engineers Inc., 2012) Rekik, Siwar ; Selouani, Sid-Ahmed ; Guerchi, Driss ; Hamam, Habib
    Hiding a secret message in speech signal, called steganography, is used to provide secure communication. The detection of hidden information in the transmitted message called steganalysis. The purpose of steganalysis is to identify the presence of embedded information, and does not actually attempt to extract or decode the hidden data. An automated method is required for detecting the existence of hidden message, since the huge amount of channeled information. However, the development and evaluation of steganalysis algorithms is a challenging task. In this paper we advocate a new steganalysis technique to classify a speech as having hidden information or not, using a powerful and sophisticated classifier called Autoregressive Time Delay Neural Network (AR-TDNN). The originality of this AR-TDNN is its quite ability to detect secret messages hidden with different steganographic algorithms, although the variation of detection rate depends on the particular hiding techniques and amount of hidden information. © 2012 IEEE.
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    Cognitive internet of things for smart water pipeline monitoring system
    (Institute of Electrical and Electronics Engineers Inc., 2019) Abdelhafidh, Maroua ; Mohamed, Fourati ; Fourati, Lamia Chaari ; Mnaouer, Adel Ben ; Mokhtar, Zid ; Permission to reuse the abstract has been secured from the Publisher.
    Water Pipeline Monitoring System (WPMS) is extremely important considering the several pipeline damages and the various hydraulic failures that cause a critical water loss. In this context, Cognitive Water Distribution System integrates Internet of Things (IoT) technology, based on smart sensors, actuators and connected objects, with a reliable Big Data processing for smart and robust Structural Health Monitoring (SHM) of pipelines. In this paper, we propose a cognitive IoT-based architecture where we used Apache Spark framework to maintain a real time processing of the large amount of collected data. This efficient processing of measured data and its correspondent calculated values simplify the transient simulations and leak detection and make it faster and easier. © 2018 IEEE.
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    A comparative analysis of BLE and 6LoWPAN for U-HealthCare applications
    (Institute of Electrical and Electronics Engineers Inc., 2013) Tabish, Rohan ; Mnaouer, Adel Ben ; Touati, Farid ; Ghaleb, Abdulaziz M.
    For decades, there exist a variety of low-power wireless technologies deployed for healthcare applications such as Zigbee/IEEE802.15.4, Bluetooth, ANT, NFC, IrDA. However, the recently announced Bluetooth Low Energy (BLE) technology claims to offer many new compelling features and is expected to get wide adoption by many mobile manufacturers around the world and hence be included in daily life mobile devices. Therefore, it is important to provide future adopters with a thorough yet insightful evaluation of this technology as contrasted to competing ones in the market today. In this paper, we present such evaluation from an experimental point of view as well as referring to technical specifications from manufacturers. The discussion is geared toward assessing the extent to which theses technologies can meet the stringent requirements for u-healthcare applicability. BLE and 6LoWPAN showed greater potentials for such applicability in terms of power demand, bit rate and latency. Nevertheless, BLE was found to be most robust to obstacles and was operable using single coin cell. © 2013 IEEE.
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    A Data-based Guiding Framework for Digital Transformation
    (CEUR-WS, 2021) Maamar, Zakaria ; Cheikhrouhou, Saoussen ; Elnaffar, Said
    This paper presents a framework for guiding organizations initiate and sustain digital transformation initiatives. Digital transformation is a long-term journey that an organization embarks on when it decides to question its practices in light of management, operation, and technology challenges. The guiding framework stresses out the importance of data in any digital transformation initiative by suggesting 4 stages referred to as collection, processing, storage, and dissemination. Because digital transformation could impact different areas of an organization for instance, business processes and business models, each stage suggests techniques to expose data. 2 case studies are adopted in the paper to illustrate how the guiding framework is put into action. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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    Design and Implementation of Cadastral Geo-spatial IoT Network Gateway Analyzer for Urban Scale Infrastructure Health Monitoring
    (Institute of Electrical and Electronics Engineers Inc., 2020-01) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Mnaouer, Adel Ben
    Urban and global scale health monitoring systems have gained significance in digital ecosystems. Every stakeholder is striving for efficiency through performance analysis of digital infrastructure health monitoring (IHM) solutions. In this work, a geospatial network analyzer (GNA) is designed and implemented in python using the synergic strengths of Plotly, NetworkX, Scipy, Numpy, MatplotLib, Network2tikz, Pysocks, and PyPing. The GNA uses as a case study a utility computing model (UCM) to make structural health monitoring (SHM) that is based on analysis of geographical area network (GAN). A geo-distributed SHM deployment is assessed from a network performance perspective and verified from geo-spatial packet processing in GNA. The results have shown that this work can lead to standardizing the future of global-scale IoT networks analytics. © 2020 IEEE.
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    Design and implementation of information centered protocol for long haul SHM monitoring
    (Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel Ben
    In structural health monitoring systems (SHM), robust data transmission is the fundamental constraint. In this work, an information centered protocol is being proposed for multi-sensor and multi-variable communication channels in (SHM). The core objective is communication traffic optimization, data streams compression, bottleneck compensation for seamless information system. A novel SHM hierarchical information model has been designed and implemented using addressing taxonomy and domain definitions accumulated with data segments, beacons and flags-handshaking. On both ends of an SHM channel, a SQLite based encoding and decoding preprocessor is implemented, which requires the use of serial protocols such as CANopen, UART, 12C and SPI. Results have shown that the proposed system optimizes traffic monitoring in handling critical situations of dynamic baud rate switching. © 2019 IEEE.
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    Design and Implementation of Multi-Protocol Data Networks Interface Detector in Heterogeneous IoTs
    (Institute of Electrical and Electronics Engineers Inc., 2020-02) Tariq, Hasan ; Abdaoui, Abderrazak ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E ; Crescini, Damiano ; Manouer, Adel Ben
    In Internet of Everything (IoE) or heterogeneous IoTs, there exist a plethora of protocols and inter-connected Internet of Things. For every network protocol, the complexity of communication and wiring at the physical interface becomes more and more challenging. In this work, an automated interface detector (or gateway) is proposed using a novel port, that scans the physical layer parameters, interpolates with Electronic Industry Association/Telecommunication Industry Association (EIA/TIA) standards specification parameters and compares packet format initiates communication. In this approach, line impedance, voltage, current, SNR, power, and network capacity are used as the coefficients of merit for physical layer detection by interpolation and averaging methods. Standard packet architectures are the key parameters for communication initiation and network fastening at both ends of the data line. The serial protocols such as CANopen, Ethernet, UART, I2C, and SPI are tested and verified. Results have shown that the proposed system can detect any physical layer interface and initiate a data network regardless of connector pinouts and interface wiring complexities. The implementation results exhibit a fertile resource for redundancy handling in-line parameters of data networks. © 2020 IEEE.
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    Design and implementation of programmable multi-parametric 4-degrees of freedom seismic waves ground motion simulation IoT platform
    (Institute of Electrical and Electronics Engineers Inc., 2019) Tariq, Hasan ; Touati, Farid ; Al-Hitmi, Mohammed Abdulla E. ; Crescini, Damiano ; Mnaouer, Adel Ben
    The early warning and disaster management agencies spend billions of dollars to counter and cater earthquakes but it has always been unique accident. In this work, a programmable four degrees of freedom electromechanical seismic wave events simulation platform design is being proposed to study and experiment seismic waves and earthquakes realization in form of ground motions. The platform can be programmed and interfaced through an IoT cloud-based Web application. The rig has been tested in the range of frequencies of extreme seismic waves from 0.1Hz to 178Hz and terrestrial inclinations from -5.000° to 5.000°, which is key contribution of this work. This would be an enabler for a variety of applications such as training self-balancing and calibrating seismic resistant designs and structures in addition to studying and testing seismic detection devices. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems. © 2019 IEEE.
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    Design and simulation of a green bi-variable mono-parametric SHM node and early seismic warning algorithm for wave identification and scattering
    (Institute of Electrical and Electronics Engineers Inc., 2018) Touati, Farid ; Tariq, Hasan ; Crescini, Damiano ; Mnaouer, Adel Ben
    Early seismic warning systems are key for safe future scalable infrastructures. In this work, a dual variable i.e. vibration and line of sight (LOS) based structure health monitoring (SHM) node is designed to sense tilt angle for early seismic warning and wave scattering detection. The SHM node, consisting of high-precision five bi-axis tiltmeters and five Blue-Violet laser diodes transmitter/receiver/reflector(LDTRR) assembly, has been designed and simulated in Proteus 7ISIS, MATLAB 7 and drafted in AutoCAD. In AutoCAD, a four LDTRR assembly is oriented at the bottom of building and its four co-planer reflectors have been orthogonally placed at effective radii with respect to the characteristic wavelengths of P, S, and Rayleigh whilst Love seismic waves, and one reflector is placed at the bottom of building. PV umbrella with a Li-ion battery has been used for green ergonomic shape. The time plots from real tiltmeter sensor nodes and data acquired from the proposed SHM node show similar behavior and results. The derived parameters of wavelength S, i.e. seismic parameter F,varied linearly from safe to hazardous seismic conditions. The variation from safe seismic to hazardous seismic transition of randomly simulated environment, also varied network traffic in GPS module as per defined threshold of sensor variables in Proteus ISIS Electronics Design Automation (EDA) engine. As per early warning evaluation functions (EWEF), the proposed design for early seismic warning algorithm (ESWA) can be a cost-effective analytics resource for any scalable SHM solution for observation range within 5km+ radius at low cost and 20km at moderate/high cost. © 2018 IEEE.
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    Design of intelligent real-time safety supervision system for pension institutions based on LBS
    (Sciendo, 2021) Song, Caili ; Kateb, Faris ; Aouad, Marwan
    With the gradual ageing of China's population and the single-child family system becoming the backbone of society, the traditional pension way of relying on children at home not only does not guarantee the quality of life of the elderly, but also brings great pressure to the work and life of young people. The way of relying on pension institutions to provide for the aged is becoming gradually accepted by society. In elderly care institutions, safety supervision systems provide an important link to protect the safety of the elderly, thereby ensuring accurate analysis and supervision of the elderly persons' activity routes and activity rules, and thus allowing an early warning to be given in a dangerous situation. The system realises the real-time positioning and monitoring of the elderly activity track, and can give early warning and timely rescue to the elderly who enter into any dangerous area. The system includes a server monitoring program and mobile APP; ASP.NET Technology to develop the monitoring program; SQL Server 2012 for data storage; and model view controller (MVC) architecture for the APP to improve the efficiency of program development. The supervision program comprises the functions of personnel information management, fence management, positioning service, activity track record, danger warning and rapid rescue. The APP deploys the location-based service (LBS) technology of Android, uses Baidu map API to obtain location information and draw activity track, and stores the information in the mobile phone SQLite database. The APP is installed on mobile phones, bracelets and other devices carried by the elderly and staff, which can record the current position of the person in real-time and simultaneously transmit it to the computer. When the elderly enter into a dangerous area, the system can quickly select the nearest staff and inform them for rescue, so as to ensure the safety of the elderly. After simulation test, the system has now reached the preset function. © 2021 Caili Song et al., published by Sciendo 2021.
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    Development of prototype for IoT and IoE scalable infrastructures, architectures and platforms
    (Springer Verlag, 2018) Touati, Farid ; Tariq, Hasan ; Crescini, Damiano ; Mnaouer, Adel Ben
    IoT is the third wave of economy after the first and second being agriculture and industry, respectively, paving the way for the fourth industrial revolution (4IR). IoT is a combination of all the revolutionary technologies in the last two decades. More than a billion of smart devices have been developed across the world by more than 10 vendors to satisfy billions of needs that are trusted by 98% of economic actors. This study describes design and implementation of IoT architectures stressing on scalability, integration, and interoperability of heterogeneous IoT systems. It gives answers to (i) how systems can be designed to become easily configurable and customizable for a specific IoT infrastructure? And (ii) how Investors, producers and consumers can be integrated on the same page of an IoT platform? We have developed a master database and directories from top chart IoT nomenclature, frameworks, vendors, devices, platforms and architectures and integrated data from 27 big online resources commonly used by Forbes, Businessweek and CNBC. Also, datasheets of IoT equipment by vendors (e.g. Intel, IBM, ARM, Microchip, Schneider, and CISCO), used tools (e.g. Labcenter Proteus, AutoCAD and Excel), and platforms (e.g. Visual Studio, Eclipse) are combined to build directories of plethora of data. The main outcome of this work culminates in providing a seamless solution and recommendations for various infrastructures (hardware and software) for effective and integrated resource utilization and management in a new IoT paradigm. © Springer Nature Switzerland AG 2018.
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    Diagnosing COVID-19 on Limited Data: A Comparative Study of Machine Learning Methods
    (Springer Science and Business Media Deutschland GmbH, 2021) Zgheib, Rita ; Kamalov, Firuz ; Chahbandarian, Ghazar ; El Labban, Osman
    Given the enormous impact of COVID-19, effective and early detection of the virus is a crucial research question. In this paper, we compare the effectiveness of several machine learning algorithms in detecting COVID-19 virus based on patient’s age, gender, and nationality. The results of the experiments show that neural networks, support vector machines, and gradient boosting decision tree models achieve an 89% accuracy, and the random forest model produces an 87% accuracy in the identification of the COVID-19 cases. © 2021, Springer Nature Switzerland AG.
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    Digital image steganography : an FFT Approach
    (Springer Nature Switzerland AG, 2012) Rabie, Tamer
    This work describes a framework for image hiding that exploits spatial domain color properties of natural images combined with spectral properties of the Fourier magnitude and phase of these images. The theory is that as long as the Fourier phase of an image is maintained intact, the overall appearance of an image remains specious if the Fourier magnitude of the image is slightly modified. This hypothesis leads to a data hiding technique that promises high fidelity, double the capacity of previous methods, higher security, and robustness to tampering. Experimental results are presented throughout the paper which demonstrate the effectiveness of this novel approach. © Springer-Verlag Berlin Heidelberg 2012.
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    Dynamic energy based text-in-speech spectrum hiding using speech masking properties
    (Institute of Electrical and Electronics Engineers Inc., 2010) Djebbar, Fatiha ; Abed-Meraim, Karim ; Guerchi, Driss ; Hamam, Habib
    In this paper we present a new method for text-in-speech Fast Fourier Transform (FFT) based steganography. Our method exploits high energetic magnitude frequency components of speech spectrum to hide the secret text. The energy level of each magnitude component is evaluated, and considered only if it is high enough to embed secret data. A frequency maskmg threshold is then calculated for each energetic frequency magnitude component to decide where to embed the secret text. As a result, the initial energy of the cover speech spectrum is slightly modified and the dIstortion error is always kept under the mask. The objective and subjective evaluations show that introducing the energy-based frequency masking 0l?ens new frontiers in text-in-speech steganography since hIgher bit rate text embedding was achieved while obtaining a stego-speech with unnoticeable distortion. © 2010 IEEE.
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    EAMP-AIDC - energy-aware mac protocol with adaptive individual duty cycle for EH-WSN
    (Institute of Electrical and Electronics Engineers Inc., 2017) Bouachir, Ons ; Mnaouer, Adel Ben ; Touati, Farid ; Crescini, Damiano
    Network lifetime is the main issue of wireless sensor networks and IoT solutions in real world application. Sensors cannot have an infinite lifetime without battery recharge or replacement. Energy harvesting, from environmental energy sources, is a promising technology to provide sustainable powering for WSN. However, based on harvesting opportunities, nodes power may alternate between two states: a state with sufficient residual power and another with shortage in power. Hence, it is paramount to develop robust networking platforms that are energy-harvesting-aware and that support low-energy consumption and data integrity in a noisy, variable environment. In this paper, we present the EAMP-AIDC protocol, an energy aware MAC protocol for EH-WSN based on individual duty cycle optimization. It takes into consideration nodes' residual energy and application and data requirements in order to define individual dynamic duty cycles (Active and sleep periods) that allow to create a balanced load in term of cooperative data relaying tasks and in terms of energy consumption between the different participating nodes so as to ensure continuous network operation. The proposed protocol was evaluated using the network simulator OMNET++ and was compared to the standard IEEE 802.15.4 MAC. The results showed that EAMP-AIDC protocol outperformed the IEEE 802.15.4 standard in term of better energy consumption, increased survivability in energy savings and in guaranteeing continuous operations. © 2017 IEEE.
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    Effect of Power Saving Techniques on the Quality of VoIP
    (Springer Science and Business Media B.V., 2017) Alakhras, Mohammad Adnan
    Power saving techniques in wireless networks have an effect on the quality of VoIP applications. These techniques are used to reduce the consumption of power when mobile terminals are used for VoIP. This paper will introduce a study on the effect of different techniques (used to reduce power consumption at various layers of the wireless network) on voice quality of service (QoS). The study will concentrate on jitter and delay of voice packets. Current standards for power saving techniques, at each network layers, will be discussed, and their effectiveness will be analyzed. WLAN is used in this study to fully analyze the effect of these power saving techniques on the voice packets jitter and delay. Simulation results are presented to demonstrate the analysis. © 2017, Springer International Publishing Switzerland.