Despite the extensive deployment of digital instruments in modern times, their stability is challenging to maintain in adverse environmental conditions such as extreme temperatures, pressure, or powerful electromagnetic radiation. Analog meters, owing to their mechanical resilience and electromagnetic impedance, persistently find usage across nuclear power plants, petroleum, and chemical industries. However, under these harsh conditions, manual reading of the instruments may prove to be difficult and dangerous while failing to meet the requirements of real-time monitoring. In recent years, several machine vision-based meter reading systems have been proposed, however, achieving high accuracy through camera-based methods under varying angles and lighting conditions poses significant challenges. Cloud deployment may compromise plant privacy, while edge computing faces limitations in real-time meter reading due to limited computing power. To address these issues, we propose a real-time reading system based on the YolactEdge instance segmentation framework for single-point analog meters. Our system is more accurate than previous studies and is implemented and deployed on the Jetson Xavier NX edge computing device. Our performance evaluation shows that our model outperforms other baselines, with low reference values and relative errors of 0.0237% and 0.0300%, respectively, and an average inference speed of 10.26 FPS with INIT 8 linear acceleration on Nvidia Jetson NX.

Software-Defined Networking (SDN) architecture was developed to address the shortcomings of traditional network architectures. It allows system administrators to easily manage and configure the network by separating and abstracting the control plane from the data plane. All the knowledge and intelligence of SDN is concentrated in a software entity called the SDN controller, making the network programmable. However, a large-scale SDN architecture, particularly in the IoT domain, requires the implementation of a physically distributed control mechanism. Such a mechanism, based on the East/West interface raises many challenges in terms of scalability, reliability, security, consistency, and traceability. The development of the Blockchain allows addressing some of these challenges. In this paper, we present a design using Blockchain technology to improve SDNs in terms of trackability and discuss the adaptations required for large-scale deployment. Experimental results clearly show that the use of a proof-of-authority consensus algorithm in combination with a Merkle tree approach reduces the impact in terms of latency as well as in terms of Gas consumption.

Towards the next generation networks, low earth orbit (LEO) satellites have been considered as a promising component for beyond 5G networks. In this paper, we study downlink LEO-5G communication systems in a practical scenario, where the integrated LEO-terrestrial system is over-loaded by serving a number of terminals with high-volume traffic requests. Our goal is to optimize resource scheduling such that the amount of undelivered data and the number of unserved terminals can be minimized. Due to the inherent hardness of the formulated quadratic integer programming problem, the optimal algorithm requires unaffordable complexity. To solve the problem, we propose a near-optimal algorithm based on alternating direction method of multipliers (ADMM-HEU), which saves computational time by taking advantage of the distributed ADMM structure, and a low-complexity heuristic algorithm (LC-HEU), which is based on estimation and greedy methods. The results demonstrate the near-optimality of ADMM-HEU and the computational efficiency of LC-HEU compared to the benchmarks.

In a backbone-assisted industrial wireless network (BAIWN), the technology of successive interference cancellation (SIC) based non-orthogonal multiple access (NOMA) provides potential solutions for improving the delay performance. Previous work emphasizes minimizing the transmission delay by user scheduling without considering power control. However, power control is beneficial for SIC-based NOMA to exploit the power domain and manage co-channel interference to simultaneously serve multiple user nodes with the high spectral and time resource utilization characteristics. In this paper, we consider joint power control and user scheduling to study the scheduling time minimization problem (STMP) with given traffic demands in BAIWNs. Specifically, STMP is formulated as an integer programming problem, which is NP-hard. To tackle the NP-hard problem, we propose a conflict graph-based greedy algorithm, to obtain a sub-optimal solution with low complexity. As a good feature, the decisions of power control and user scheduling can be made by the proposed algorithm only according to the channel state information and traffic demands. The experimental results show that compared with the other methods, the proposed method effectively improves the delay performance regardless of the channel states or the network scales.

Software-Defined Networking (SDN) brought a groundbreaking idea to facilitate network system management by decoupling and abstracting the Control plane and Data plane of traditional networks. The centralised control offers network administrators many benefits such as a global view of the network, programmability, dynamic updating of forwarding rules, and software-based traffic analysis. The SDN architecture has been applied a lot in practice, and especially in Internet of Things (IoT) platforms. With the superiority of SDN, IoT devices can be managed and configured much more easily when combined. However, SDN also raises many challenges in terms of scalability, reliability, and security. Blockchain is another promising solution for secure information storage and transmission technology that operates without a centralised authority. Applying Blockchain technology into SDN can address some of the current issues of SDN by providing decentralised methods to authenticate exchanged network information. This study provides a comprehensive survey on Blockchain technologies applied to SDN in both security and non-security fields. First, related studies and an overview of SDN and the background of Blockchain technology are presented. Then, the authors review how Blockchain technologies are applied in SDN from two perspectives: non-security and security-aware approaches. Finally, challenges and broader perspectives are discussed.

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless power communication networks (WPCN-s), where the UAV provides energy for mobile user nodes (M-UNs) and receives information from M-UNs. The movement of M-UN complies with a Gauss-Markov random model. To ensure acceptable quality-of-service (QoS), we consider dynamically planning the flight path of the UAV according to the movements of M-UNs. Since the flight time of UAV is restricted by limited energy, nonorthogonal multiple access (NOMA) is adopted to access a large number of M-UNs for simultaneous information transmission. Based on the above considerations, we aim to maximize the throughput via path planning of the UAV, subject to the QoS requirements of M-UNs and the UAV's energy constraint. To handle the challenges brought by dynamically changing channels to solving the problem, we propose a QoS-based double deep Q-learning network (DDQN). Numerical simulation results show that, compared with the conventional algorithms, the proposed framework achieves higher throughput.

In this paper, we investigate a low-altitude unmanned aerial vehicle (UAV)-assisted wireless power- ed device-to-device (D2D) network with the "harvest-transmit-store" model, where a UAV broadcasts energy to all D2D transmitters and the transmitters then store or use the energy for transmission information. In the proposed model, the UAV does not transmit energy in the transmission information time, resulting in a limited charging time. In addition, the interference may be caused by communicating information of an arbitrary number of D2D pairs simultaneously. In this paper, we propose a hybrid time division duplex/frequency division duplex communication scheme, which performs the power transfer and information transmission simultaneously in the transmission information time. The scheme cancels the cochannel interference by using the time division duplex scheme and guarantees the charging time by using the frequency division duplex. We consider optimizing the throughput based on the scheme via joint power control, spectrum allocation, and scheduling time. We propose a two-step algorithm to solve the formulated nonconvex problem. The simulation results show that the proposed algorithm improves the average throughput compared to the other schemes.

In this mymargin letter, we investigate a backbone-assisted wireless powered communication network (WPCN) under the protocol of "harvest-then-transmit" protocol, where user nodes (UNs) harvest energy from the sinks in the downlink (DL), then they use the energy to transmit signals to the sinks by a non-orthogonal multiple access in the uplink (UL). We consider joint successive interference cancellation and backbone-assisted sink cooperation to reduce the impact of co-channel interference on the throughput performance. We maximize the system throughput by jointly optimizing user scheduling and the time allocation for DL energy harvesting and UL transmission. For solving the maximum throughput problem efficiently, we propose a column generation method based on a greedy algorithm. Numerical results show that our proposed energy and information transfer design is superior to other reference methods in WPCNs.

Wireless devices have been used to investigate the environment and to understand our physical world. In this work, we undertake the challenging problem of identifying location of obstacles and objects by WiFi signals. Gathering wireless sensory data to form an image is difficult since wireless signals are susceptible to multipath. Moreover, reconstructing an image of unknown objects based on the measurements of sparse signals is an ill-posed problem. To tackle these problems, we first present a linear model using received signal strength indicator (RSSI) measurements. We define the sparse beamforming problem as an l(0)-norm optimization problem, then use the iterative reweighted l(1) heuristic algorithm to obtain an optimal solution as a multipath. Finally, the multipath fading is removed by using Machine Learning. More specifically, we use Support Vector Regression (SVR) to identify a clear image of the unknown object. Our results show that the proposed method can reconstruct signals as a 3D image with a satisfactory visual appearance, i.e. the generated data mesh is well defined and smooth compared to previous work.

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Use of wireless signal for identification of unknown object, or technology to see-through a wall to form an image, is gaining growing interest from various fields including law enforcement and military sectors, disaster management, or even in civilian sectors such as construction sites. The great challenge in the implementation of such technology is the stochastic disturbances on wireless signal which will result in a signal with missing samples. Compressive Sensing (CS) is a powerful tool for estimating the missing samples since it can find accurate solution to largely underdetermined linear wireless signals. However, sparse models like CS can also suffer from information loss dues to stochastic lossy nature of wireless, making CS not to have accurate information for reconstruction of a signal. In this paper, we developed a theoretical and experimental framework for the mapping of obstacles by reconstructing the wireless signal based on a sparse signal. We apply tensor format to perform the computations along each mode by relaxing the tensor constraints to obtain accurate results. The proposed framework demonstrates how to take 2D signals, formulate estimate signals and produce a 3D image location in a completely unknown area inside of the obstacle (wall).

To meet the needs of high throughput, low delay and high resolution video services, the free space optical network (FSO) has recently received increasing attention due to its large bandwidth and high transmission rate. However, atmospheric turbulence is a major challenge, which can lead to severe BER performance degradation or even make the link ineffective. To mitigate the significant degradation of the video streaming quality on FSO networks, in this paper, an unequal error protection (UEP) scheme for scalable video coding is designed to minimize the video distortion. By adaptively choosing the number of video layers and the redundancy rate of the channel coding, unequal error protection of Scalable video coding is achieved. In addition, to solve the optimization model, a heuristic-based fast algorithm is proposed. A large number of simulation experiments in an NS3 network simulator show that the proposed scheme offers significantly higher quality in the reconstructed video sequences.

In this paper, we developed a theoretical and experimental framework for the mapping of obstacles using WiFi, based on a small number of wireless channel samples. This is very challenging due to the numerous channel coefficients to be estimated over the time-varying channel and the channel estimation of a wireless signal transmission to be considered for compressive sampling. In a typical communication system, the signal is sampled at least twice at the highest frequency contained in the signal. However, this limits efficient ways to compress the signal, as it places a huge burden on sampling the entire signal while only a small number of the transform coefficients are needed to represent the signal. To tackle this problem, we will focused on a mathematical optimization problem for the most efficient compressed sensing method called $\ell_1$-norm, known as Basis Pursuit. Before optimizing the problem, the noise was removed from the signal, namely, multipath fading. Our experimental results show the improved performance in the number of iterations for obtaining a framework for the mapping of obstacles.

We address an energy-efficient scheduling problem for practical multiple-input single-output (MISO) systems with stringent execution-time requirements. Optimal user-group scheduling is adopted to enable timely and energy-efficient data transmission, such that all the users' demand can be delivered within a limited time. The high computational complexity in optimal iterative algorithms limits their applications in real-time network operations. In this paper, we rethink the conventional optimization algorithms, and embed machine-learning based predictions in the optimization process, aiming at improving the computational efficiency and meeting the stringent execution-time limits in practice, while retaining competitive energy-saving performance for the MISO system. Numerical results demonstrate that the proposed method, i.e., optimization with machine- learning predictions (OMLP), is able to provide a time-efficient and high-quality solution for the considered scheduling problem. Towards online scheduling in real-time communications, OMLP is of high computational efficiency compared to conventional optimal iterative algorithms. OMLP guarantees the optimality as long as the machine- learning based predictions are accurate.

Traffic calming measures, such as speed bumps and elevated crossing points, are used to reduce speed, to prevent overtaking and generally contribute to a safer traffic situation. However, they might also cause increased response times for rescue vehicles (e.g. ambulances or fire trucks). An alternative to the conventional traffic calming measures is so-called smart traffic calming measures. These can determine when a vehicle approaches, whose journey should not be hindered, and adjust to allow for free passage for this vehicle.

This report gives an overview of the problem, and some examples of smart  traffic calming measures are discussed. Special focus is put on the wireless communication necessary to detect emergency vehicles. Furthermore, existing challenges and possible solutions for traffic calming measures and the communication needed to make them smart are discussed.

Current wireless networks face unprecedented challenges because of the exponentially increasing demand for mobile data and the rapid growth in infrastructure and power consumption. This study investigates the optimal energy efficiency of millimeter wave (mmWave) cellular networks, given that these networks are some of the most promising 5G-enabling technologies. Based on the stochastic geometry, a mathematical framework of coverage probability is proposed and the optimal energy efficiency is obtained with coverage performance constraints. Numerical results show that increasing the base station density damages coverage performance exceeding the threshold. This work demonstrates an essential understanding of the deployment and dynamic control of energy-efficient mmWave cellular networks.

The combination of forward error correction (FEC) and interleaving can be used to improve free-space optical communication systems. Recent research has optimised the codeword length and interleaving depth under the assumption of a fixed buffering size; however, how the buffering size influences the system performance remains unsolved. This study models the system performance as a function of buffering size and FEC recovery threshold, which allows system designers to determine optimum parameters in consideration of the overhead. The modelling is based on statistics of temporal features of correct data reception and burst error length through the measurement of the channel good time and outage time. The experimental results show good coherence with the theoretical values. This method can also be applied in other channels if a continuous-time-Markov-chain model of the channel can be derived.

It is a critical requirement of the future 5G communication networks to provide high speed and significantly reduce the network energy consumption. Energy efficient networks along with an energy saving strategy in mobile devices play a vital role in the mobile revolution. The new strategies should not only focus on wireless base stations, which consumes most of the power, but also considers the other power consumption elements for future mobile communication networks, including User Equipment (UE). In this paper, we have proposed a method that calculates the power consumption of a 5G network by considering its main elements based on current vision of 5G network infrastructure. Our proposed model uses the component based methodology that simplifies the process by taking into account the different high power consuming elements. The proposed method is evaluated by considering the three UEs DRX models and Virtual Base Station (VBS) with respect to different DRX timer in terms of Power Saving (PS) and delay as performance parameters.

The data de-duplication system not only pursues the high de-duplication rate, which refers to the aggregate reduction in storage requirements gained from de-duplication, but also the de-duplication speed. To solve the problem of random parameter-setting brought by Content Defined Chunking (CDC), a self-adaptive data chunking algorithm is proposed. The algorithm improves the de-duplication rate by conducting pre-processing de-duplication to the samples of the classified files and then selecting the appropriate algorithm parameters. Meanwhile, FastCDC, a kind of content-based fast data chunking algorithm, is adopted to solve the problem of low de-duplication speed of CDC. By introducing de-duplication factor and acceleration factor, FastCDC can significantly boost de-duplication speed while not sacrificing the de -duplication rate through adjusting these two parameters. The experimental results demonstrate that our proposed method can improve the de -duplication rate by about 5 %, while FastCDC can obtain the increase of de -duplication speed by 50 % to 200 % only at the expense of less than 3 % de duplication rate loss.

Wireless radio-frequency (RF) technologies has had universal wide-scale deployment. Despite this, the practical limitations of the RF spectrum being unable to meet the challenges (e.g. lack of security, high interference, limited bandwidth, scalability) of RF based communication networks have become increasingly apparent over the past decade. With the evergrowing of data heavy wireless communications, especially on the last mile (e.g. wireless mesh network) and the backbone, methods are required to help addresses the problem RF have been facing for the next generation network. Faced with such daunting obstacles in RF-only networks, the use of Free Space Optical (FSO) for wireless communications was proposed. FSO is a promising solution to security, limited spectrum bandwidth, the scalability problem of wireless mesh networks, but also the advantage of large transmission distance, free license, interference immunity, and high-bandwidth. Despite the major advantages of FSO technology, its widespread use has been hampered by atmospheric turbulence-induced fading. However, FSO is still consider to be a practical solution to RF challenges. To maximize the potential of FSO networks, we study the problem of maximum path resource flow for a route and minimum linear delay while the FSO topology under atmospheric turbulence. Such methods can be easy adopted to SDN to manage the data flow at the linkor network-layer.

The 4G standard Long Term Evolution-Advanced(LTE-A) has been deployed in many countries. Now, technologyis evolving towards the 5G standard since it is expecting tostart its service in 2020. The 5G cellular networks will mainlycontain in cloud computing and primarily Quality of Service(QoS) parameters (e.g. delay, loss rate, etc.) influence thecloud network performance. The impact of user perceivedQuality of Experience (QoE) using multimedia services, andapplication significantly relies on the QoS parameters. The keychallenge of 5G technology is to reduce the delay less thanone millisecond. In this paper, we have described a methodthat minimizes the overall network delay for multimediaservices; which are constant bit rate (VoIP) and variablebit rate (video) traffic model. We also proposed a methodthat measures the user’s QoE for video streaming trafficusing the network QoS parameters, i.e. delay and packet lossrate. The performance of proposed QoE method is comparedwith QoV method, and our proposed QoE method performsbest by carefully handle the impact of QoS parameters. Theresults show that our described method successfully reduces theoverall network delays, which result to maximize the user’s QoE.

The fastest growing of multimedia services overfuture wireless communication system demand more networkresources, efficient delivery of multimedia service with highusers satisfaction, and power optimization of User Equipments(UEs). The resources and power optimization are significant infuture mobile computing systems, because emerging multimediaservices consume more resources and power. The 4G standard ofLTE-A wireless system has adopted the Discontinuous Reception(DRX) method to extend and optimize the UE battery life,while there is no standard scheduling method to distribute theradio resources among the UE. This paper presents a downlinkscheduler, i.e. Quality of Experience (QoE) Power EfficientMethod (QEPEM) for LTE-A, which efficiently allocates theradio resources and optimizes the use of UE power using theDRX mechanism. We investigates how the different durationof DRX Light and Deep Sleep cycle influences the QoS andQoE of end users, using VoIP over the LTE-A. The QEPEMis evaluated with the traditional methods, in terms of SystemThroughput, Fairness Index, Packet Loss Rate, and PacketDelay. The QEPEM measures the user’s QoE, and feedback toeNodeB for scheduling decisions along with other importantparameters. Our proposed method reduces the packet delay,packet loss, and increases the fairness and UE’s power savingwith high users satisfaction.

Abstract LTE and LTE-Advanced mobile technologies have integrated discontinuous reception (DRX) power saving method to optimize the power consumption at the user equipment (UE). The DRX method was proposed by the 3rd Generation Partnership Project (3GPP), and since then, the traffic behavior has been analyzed in several studies with a standard 3-state DRX model to describe the trade-off between power saving and delay. In this paper, we presented a novel 4-state and 5-state 3GPP LTE DRX mechanisms. The proposed mechanisms were developed by augmenting (an) active state(s) to deep and/or light sleep cycle of standard 3-state DRX for handling a small burst of packets, thereby bypassing the process of returning to the timer-dependent active mode. We have generated analytical models using a semi-Markov process for bursty packet data traffic and evaluated these augmented DRX mechanisms against a standard 3-state DRX method. Overall, the analytical results from varying timing parameters showed that our augmented DRX (both 4-state and 5-state) improved power saving factor (ranging between 1% and 8%) and reduced delay (ranging between 20% and 60%) compared to the standard 3-state DRX. Furthermore, the magnitude of improvement for both delay and power-saving was somewhat greater in 5-state than 4-state.

The 3rd Generation Partnership Project (3GPP) introduced the new radio access technology, LTE (Long Term Evolution) and LTE-Advanced, which has the capability to provide larger bandwidth and low latencies on a wireless network in order to fulfill the demand of Users' Equipment (UEs) with acceptable Quality of Service (QoS). One of the data-heavy applications that has exploded on the market is Video. This calls for accurate modeling of video traffic. To ensure the quality and correctness of complex systems with Video traffic, it is important to evaluate the behavior of the traffic in the heterogeneous environment. This paper presents measurements on LTE Video traffic which were performed in a real environment. We derived a semi-Markov model which accurately reproduces the statistics of composite Video measurements over LTE network.

Vehicular ad hoc networks (VANETs) are witnessing in recent years a rapid development for road transmissions and are considered as one of the most important types of next generation networks, in which drivers can have access anywhere and anytime to information. However, vehicles have to deal with many challenges such as the links failures due to their frequent mobility as well as limited degrees of freedom in their mobility patterns. In this paper, we propose a new quality of service multicast and multipath routing protocol for VANETs, based on the paradigm of bees communication, called multicast quality of service swarm bee routing for VANETs (MQBV). The MQBV finds and maintains robust routes between the source node and all multicast group members. Therefore, the average end-to-end delay and the normalized overhead load should be reduced, while at the same time increasing the average bandwidth and the packet delivery ratio. Extensive simulation results were obtained using ns-2 simulator in a realistic VANET settings and demonstrated the efficiency of the proposed protocol. Copyright (c) 2013 John Wiley and Sons, Ltd.

The 4G standard Long Term Evolution-Advanced(LTE-A) has been deployed in many countries. Now, technologyis evolving towards the 5G standard since it is expecting tostart its services in 2020. The 5G cellular networks will mainlycontain in cloud computing and primarily Quality of Service(QoS) parameters (e.g. delay, loss rate, etc.) influence the cloudnetwork performance. The impact of user perceived Quality ofExperience (QoE) significantly relies on the QoS parameters. Thekey challenge of 5G technology is to reduce the delay less thanone millisecond. In this paper, we have described a method thatminimizes the overall network delay for constant bit rate (VoIP)and variable bit rate (video) traffic model. We also proposed amethod that measures the user’s QoE for video streaming trafficusing the network QoS parameters, i.e. delay and packet lossrate. The performance of proposed QoE method is comparedwith QoV method, and our proposed QoE method performsbest by carefully handle the impact of QoS parameters. Theresults show that our described method successfully reduces theoverall network delays, which result to maximize the user’s QoE.

The emerging and fastest growing multimedia services such as Skype, GTalk and interactive video gaming have created new challenges for wireless communication technologies, especially in terms of resource allocation and power optimization of User Equipments (UEs). The efficient resources and the power optimization are very important in the next communication systems because new multimedia services are more resource and power hungry. Having more traffic flow in the downlink as compared to the uplink, the resource allocation schemes in the downlink are more important than those in the uplink. In this paper, we have proposed a new downlink scheduling scheme, known as Quality-aware DRX (Q-DRX) Scheme, for Long Term Evaluation (LTE) wireless networks that not only improves the Quality of Service (QoS) to satisfy the users experience of multimedia services but also saves the UEs power by using the Discontinuous Reception (DRX). This paper investigates how the different durations of DRX Light and Deep Sleep cycles affect the QoS and influence the Quality of Experience (QoE) of end users, in the context of Voice over IP (VoIP) traffic delivery over the LTE wireless network. The performance of the Q-DRX scheme is evaluated with traditional scheduling schemes, in the perception of the following important parameters, System Throughput, Throughput Fairness Index, Packet Loss Rate and Packet Delay. Our proposed Q-DRX Scheme successfully minimized the packets delay and packets loss by considering the key parameters of QoS with fair resources distribution among the UEs to achieve a high satisfaction level. (C) 2014 Elsevier Ltd. All rights reserved.

Smart Environments are environments where heterogeneous wireless networks are implemented and connected together both in terms of networking and in terms of functionalities, thus providing an abstraction layer to higher level applications that can exploit the interplay of such technologies to obtain killer features. In order to obtain real advantages from the integration of heterogeneous components the scenarios shall be clearly understood and analysed;therefore this paper classifies the different scenarios and network architectures that can be employed in creating a Smart Environment. Moreover, real life experimenting is needed, through testbeds and trial installations; our testbed is therefore described, as well as some results on the effects achieved by interconnecting different technologies.

The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today's data-heavy applications, consequently, a better experience for the end user. Since cellular communication is ready available, LTE communication has been designed to work at high speeds for vehicular communication. The challenge is that the protocols in LTE/LTE-Advanced should not only provide good packet delivery but also adapt to changes in the network topology due to vehicle volume and vehicular mobility. It is a critical requirement to ensure a seamless quality of experience ranging from safety to relieving congestion as deployment of LTE/LTE-Advanced become common. This requires learning how to improve the LTE/LTE-Advanced model to better appeal to a wider base and move toward additional solutions. In this paper we present a feasibility analysis for performing vehicular communication via a queueing theory approach based on a multi-server queue using real LTE traffic. A M/M/m model is employed to evaluate the probability that a vehicle finds all channels busy, as well as to derive the expected waiting times and the expected number of channel switches. Also, when a base station (eNB) becomes overloaded with a single-hop, a multi-hop rerouting optimization approach is presented.

The LTE standard has been developed for high-bandwidth mobile access for today’s data-heavy applications. With broadband cellular available already from the UMTS system, users are expecting the LTE network to provide high quality communication. To ensure the quality and correctness of complex systems of LTE, it is important to evaluate the behavior of traffic on a LTE network in relation to UMTS. In this paper, LTE and UMTS measurements on video traffic were performed in a real environment, allowing for greater development, and understanding of network traffic performance.

In real-time video transmission, the distortion of video content may be caused by video compression in source coding and packets loss in transmission. Meanwhile the source coding distortion and transmission distortion are often mutually affected. There is a fundamental tradeoff between them for achieving the best video transmission quality. In order to make wise use of network resources, this paper proposes a video transmission scheme in which the source coding distortion and transmission distortion to the video quality are formulated and fountain code is used as the channel coding for unequal protection in scalable video transmission. The network packet loss and the characteristic of scalable video are quantitated in our proposed rate distortion model, which formulates the real-time video transmission system in a bandwidth limited network. We introduce a computerized algorithm. The computerized algorithm will determine the optimal source rate of the video coding and the optimal redundancy amount assigned to each scalable video layer. Our proposed algorithm can guarantee that the optimal quality of real-time video transmission will be achieved and the total real-time video transmission distortion will be reduced dramatically.

The 4G standard Long Term Evolution (LTE) utilizes discontinuous reception (DRX) to extend the user equipments battery lifetime. DRX permits an idle UE to power off the radio receiver for two predefined sleep period and then wake up to receive the next paging message. Two major basic power saving models proposed to data are the 3GPP ETSI model and industrial DRX model proposed by Nokia. While previous studies have investigated power saving with the 3GPP ETSI models, the industrial DRX model has not been considered for analytical studies to date. Thus, there is a need to optimize the DRX parameters in the industrial model so as to maximize power saving without incurring network reentry and packet delays. In this paper, we take an overview of various static DRX cycles of the LTE/LTE-Advanced power saving mechanisms by modelling the system with bursty packet data traffic using a semi-Markov process. Using this analytical model, we will show the tradeoff relationship between the power saving and wake-up delay performance in the industrial model.

The tremendous popularity of smart phones and electronic tablets has spurred the explosive growth of high-rate multimedia wireless services. To alleviate the huge infrastructure investment in the exponential growth of mobile traffic and improve local service flexibility, device-to-device (D2D) communications have been considered for the next generation mobile telecommunications. This has triggered investigation of fifth gernation (5G) to utilizes D2D communications for hetergenous networks. D2D communications enable users to transmit signals directly without going through the base station. However, many technical challenges need to be addressed for D2D communications to harvest the potential benefits. This requires learning how to improve the the model to better appeal to a wider base and move toward additional solutions. In this paper we provided a simple overview of D2D communications 5G hetergenous network by means of various Integer Linear programming. Finally, we present experiments on how Fractional knapsack using greedy algorithm can be used for power efficiency and improve throughput, thus allowing of future optimization problems.

The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today’s data-heavy applications. However, these data-heavy applications require lots of battery power on the user equipment. To extend the user equipment battery lifetime, plus further support various services and large amount of data transmissions, the 3GPP standards for LTE/LTE-Advanced has adopted discontinuous reception (DRX). In this paper, we take an overview of various static/fixed DRX cycles of the LTE/LTE-Advanced power saving mechanisms, by modelling the system with bursty packet data traffic using a semi-Markov process. Based on the analytical model, we will show the trade-off relationship between the power saving and wake-up delay performance. This work will help to select the best parameters when LTE/LTE-Advanced DRX is implemented depending on the protocols and desired outcome of the traffic.

Fourth-generation (4G) or long-term evolution (LTE) technology offers the promise of even smarter computing and multimedia applications which will be available anywhere, at any time. This comprehensive text/reference presents a detailed review of the pioneering research underpinning this emerging technological revolution. The book also examines the various challenges to secure, efficient and cost-effective next-generation wireless networking. Opening with a selection of chapters devoted to the exciting trends in wireless network technology, followed by a section focusing on advanced applications, the text then concludes with an investigation into the future internet systems that will pave the way towards true ubiquitous computing. Topics and features: Presents the latest advances, standards and technical challenges in a broad range of emerging wireless technologies Discusses cooperative and mesh networks, delay tolerant networks, and other next-generation networks such as LTE Examines real-world applications of vehicular communications, broadband wireless technologies, RFID technology, and energy-efficient wireless communications Introduces developments towards the ‘Internet of Things’ from both a communications and a service perspective Discusses the machine-to-machine communication model, important applications of wireless technologies in healthcare, and security issues in state-of-the-art networks This wide-ranging, cutting-edge volume is a ‘must-read’ for all researchers and practitioners involved in wireless communications. Dr. Naveen Chilamkurti is a Senior Lecturer in the Department of Computer Science and Engineering at La Trobe University, Melbourne, Australia.

Cellular positioning has been a very active research area for the last decade. Large improvement in accuracy has been made to support, for example, e-call and other location-based services. Traditionally, cellular positioning has been limited to cellular operators equipped with expensive synchronization hardware in order to achieve good accuracy. Lately, third parties have employed fingerprinting methods to enable positioning systems independent from the cellular operators. With improved available processing power, denser cellular networks, cheaper data collection and efficient pattern matching algorithms, the fingerprinting positioning methods have also gained popularity. In this paper, we analyzed the potential of using System Frame Number (SFN) - SFN observed time differences, which are traditionally used in Time Difference of Arrival (TDOA) positioning, for fingerprinting-based positioning. A field test was performed using measurements from TEMS (Telecommunication Management System) Investigation. By combining SFN-SFN observed time differences with Received Signal Code Power (RSCP) measurements, we demonstrated an improved accuracy of the fingerprinting method by 20% compared to only using RSCP measurements. The results are promising and show good potential in using SFN-SFN observed time differences for positioning based on fingerprinting.

Single carrier frequency division multiple access (SC-FDMA) has been adopted as the standard multiple access scheme for 3GPP LTE uplink. In comparison to orthogonal frequency division multiple access (OFDMA), the subcarriers assigned to each user are required to be consecutive in SC-FDMA localized scheme, which imposes more difficulties on resource allocation problem. Subject to this constraint, various optimization objectives, such as utility maximization and power minimization, have been studied for SC-FDMA resource allocation. In this paper, we focus on developing a general algorithm framework with near-optimal performance and polynomial-time complexity to maximize the total utility for SC-FDMA systems. The proposed algorithm is based on low-complexity estimation for the partial solution space. Compared with existing algorithms, simulation results show that our algorithm improves the system utility significantly and has less deviation to global optimum. In addition, the proposed algorithm framework allows a flexible trade-off between computational effort and solution performance by varying the complexity of estimation approaches.

The recent explosive growth of voice over IP (VoIP) solutions calls for accurate modelling of VoIP traffic. This study presents measurements of ON and OFF periods of VoIP activity from a significantly large database of VoIP call recordings consisting of native speakers speaking in some of the worlds most widely spoken languages. The impact of the languages and the varying dynamics of caller interaction on the ON and OFF period statistics are assessed. It is observed that speaker interactions dominate over language dependence which makes monologue-based data unreliable for traffic modelling. The authors derive a semi-Markov model which accurately reproduces the statistics of composite dialogue measurements.

As smartphone clients are restricted in computational power and bandwidth, it is important to minimise the overhead of transmitted messages.  This paper identifies and studies methods that reduce the amount of data being transferred via wireless links between a web service client and a web service. Measurements were performed in a real environment based on a web service prototype providing public transport information for the city of Hamburg in Germany, using actual wireless links with a mobile smartphone device.  REST based web services using the data exchange formats JSON, XML and Fast Infoset were evaluated against the existing SOAP based web service.

The 4G standard Long Term Evolution (LTE) has been developed for high-bandwidth mobile access for today's data-heavy applications, consequently, a better experience for the end user. To extend the user equipment battery lifetime, plus further support various services and large amount of data transmissions, the 3GPP standards for LTE/LTE-Advanced has adopted discontinuous reception (DRX). However, there is a need to optimize the DRX parameters, so as to maximize power saving without incurring network re-entry and packet delays. In this paper, we take an overview of the fixed frame DRX cycle and compare it against an adjustable DRX cycle of the LTE/LTE-Advanced power saving mechanism, by modelling the system with bursty packet data traffic using a semi-Markov process. Based on the analytical model, we will show the trade-off relationship between the power saving and wake-up delay performance.

In this paper a novel unequal packet loss protection scheme R2NC based on low-triangular global coding matrix with ladder-shaped partition is presented, which combines redundant and random network coding for robust H.264/SVC video transmission. Firstly, the error-correcting capabilities of redundant network coding make our scheme resilient to loss. Secondly, the implementation of random network coding at the intermediate nodes with multiple input links can reduce the cost of network bandwidth, thus reducing the end-to-end delay for video transmission. Thirdly, the low-triangular global coding matrix with ladder-shaped partition is maintained throughout the R2NC processes to reduce the impact of global coding matrixs rank deficiency on video transmission and provide unequal erasure protection for H.264/SVC priority layers. The redundant network coding avoids the retransmission of lost packets and improves error-correcting capabilities of lost packets. Based only on the knowledge of the packet loss rates on the output links, the source node and intermediate nodes can make decisions for redundant network coding and random network coding (i.e., how much redundancy to add at this node). However, the redundancy caused by redundant network coding makes the network load increases. In order to improve network throughput, we performed random network coding at the intermediate nodes. Our approach is grounded on the overall distortion of reconstructed video minimization by optimizing the amount of redundancy assigned to each layer. The convex optimization model is constructed under the constraint of network coding and scalable video coding. Experimental results are shown to demonstrate the significant improvement of H.264/SVC video reconstruction quality with R2NC over packet lossy networks.

The addition of emerging multimedia services such as Skype, GTalk, multi-user interactive gaming in cellular communication systems has created new challenges for resource allocation and power optimization. The requirement of efficient resource allocation is more important in downlink than uplink due to high traffic flows. These multimedia applications require more power, therefore power optimization has gained a key role in future communication systems. In this paper, a downlink scheduling technique in Long Term Evolution (LTE) is proposed that improves the Quality of Service (QoS) for multimedia services in relation with use of the power saving scheme at the User Equipment (UE) i.e. Discontinuous Reception (DRX). The DRX effectively improves power consumption at the cost of QoS degradation due to higher packet delays and packet losses. The proposed scheme considers key QoS parameters during scheduling with fair resource allocation while minimizing packet delay and packet loss even in a power saving environment.

The WiMAX, also known as IEEE 802.16, provides a mechanism for deploying high-speed wireless mesh network, (an ubiquitous wireless network) in metropolitan areas.  WiMAX technology can be used as ``last mile ubiquitous" broadband connections to deliver streaming audio or video to clients. Thus, Quality of Service (QoS) is very important for WiMAX networks. Providing QoS in multi-hop WiMAX networks such as WiMAX mesh networks is challenging since the WiMAX mesh networks MAC is connectionless based and does not have proper support guarantees for QoS over multiple hops.  As a result, multiple links can interfere with each other when they are scheduled at the same time. The scheduling function plays a crucial role in QoS support, and various algorithms have been proposed and analyzed. These analysis basically assume a backlogged situation evenly in all queues.  However, multimedia traffic is bursty in nature, and the fairness of bursty traffic relative to continuous traffic has not been fully studied yet. Therefore, in this paper, we will discuss the potential unfairness that bursty traffic may be subjected to and propose a new frame-based packet scheduling algorithm. The scheduling is evaluated with multiple channels on WiMAX mesh nodes, which are operated in a distributed coordinated scheduling mode. Each wireless node has a single radio interface which is able to switch between multiple channels.  We evaluated the performance of the proposed dynamic changing scheduling method by extensive simulations, and it was shown to provide fair bandwidth allocation while increasing the traffic performance by means of throughput.

The ubiquitous access to wired and wireless networks is making information access possible from anywhere, anytime, and any device. Today, end-users are also highly mobile, often equipped with a range of portable devices, and they expect service availability when they require it. In addition, they do not want to be burdened by complex configurations before they can discover and use services. The Zero Configuration (Zeroconf) Networking technology promises to alleviate this configuration burden by allowing users to discover services and devices with little end-user intervention. We compare two popular implementations of Zeroconf namely, Avahi and Mono.Zeroconf running on Linux and Windows XP operating systems, respectively. We evaluate their performance using service discovery time as the performance metric. Our empirical results show that Linux Avahi yields almost 99% improvements in service discovery time over Windows Mono.Zeroconf. We also discuss security solutions that can be deployed to enhance the security of Zeroconf networks. We further investigate the performance of the IP Security (IPSec) protocol when used by our Mono.Zeroconf implementation running on the Windows XP platform. With IPSec, service discovery time increases by almost 45% with our prototype implementation.

Wireless Mesh Networks (WMNs) have emerged as a key technology for the next generation ofwireless networking.  Instead of being another type of ad-hoc networking, WMNs diversify the capabilities of ad-hoc networks.  Several protocols that work over WMNs include IEEE802.11a/b/g, 802.15, 802.16 and LTE-Advanced. To bring about a high throughput under varying conditions, these protocols have to adapt their transmission rate. In this paper, we have proposed a scheme to improve channel conditions by performing rate adaptation along with multiple packet transmission using packet loss and physical layer condition.  Dynamic monitoring, multiple packet transmission and adaptation to changes in channel quality by adjusting the packet transmission rates according to certain optimization criteria provided greater throughput. The key feature of the proposed method is the combination of the following two factors: 1) detection of intrinsic channel conditions by measuring the fluctuation of noise to signal ratio via the standard deviation, and 2) the detection of packet loss induced through congestion.  We have shown that the use of such techniques in a WMN can significantly improve performance in terms of the packet sending rate.  The effectiveness of the proposed method was demonstrated in a simulated wireless network testbed via packet-level simulation.

The Internet has become a universal communication network tool. It has evolved from a platform that supportsbest-effort traffic to one that now carries different traffic types including those involving continuous media withQuality of Service (QoS) requirements. As more services are delivered over the Internet, we face increasing riskto their availability given that malicious attacks on those Internet services continue to increase. Several networkshave witnessed Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks over the past few yearswhich have disrupted QoS of network services, thereby violating the Service Level Agreement (SLA) between theclient and the Internet Service Provider (ISP). Hence DoS or DDoS attacks are major threats to network QoS. Inthis paper we survey techniques and solutions that have been deployed to thwart DoS and DDoS attacks and weevaluate them in terms of their impact on network QoS for Internet services. We also present vulnerabilities thatcan be exploited for QoS protocols and also affect QoS if exploited. In addition, we also highlight challenges thatstill need to be addressed to achieve end-to-end QoS with recently proposed DoS/DDoS solutions.

The Scalable Video Coding (SVC) amendment of the H.264/AVC standard is an up-to-date video compression standard. The various scalable layers have different contribution to the quality of the reconstructed video sequence due to the use of hierarchical prediction and the drift propagation. This paper proposes a novel trapezoidal-unequal error protection (UEP) scheme which significantly reduces the redundancy but rarely decreases the performance by taking into account the characteristics of the video coding and the adoptive forward error correction (FEC) sufficiently. In order to optimally distribute FEC codes, the paper then proposes a layer-aware distortion model to accurately estimate the decrement of video quality caused by the loss of quality enhancement layers, drift propagation and error concealment in the scalable H.264/AVC video. Experimental results show that the proposed trapezoidal UEP scheme has better robustness and in the meanwhile reduces the coding redundancy greatly in different channel circumstance compared with the traditional UEP scheme.

As smartphone clients are restricted in computational power and bandwidth it is important to minimise the overhead of transmitted messages and since it results in processing time when implementing a web service. This paper identifies and studies methods that reduce the amount of data being transferred via wireless links between a Web service client and a Web service. The goal is to improve the end-to-end service execution time by reducing the bottleneck presented by the limited bandwidth in an ubiquitous environment. Measurements are performed in a real environment based on a web service prototype providing public transport information for the city of Hamburg in Germany, using actual wireless links with a mobile smartphone device. The existing SOAP based web service is evaluated against a REST based web service using the data exchange formats JSON, XML and Fast Infoset.

After more than a decade of research, system securityand resilience is now the major technological barrier forthe Cognitive Radio (CR) to be adopted by the telecommunication industry. New ideas are required tomake CR networks secure and robust against attacks taking advantage the inherent characteristics of the CR functionality. This work explores key points that urgentlyneed to be addressed.

Long Term Evolution (LTE) of 3GPP provides high bandwidth for data transfer. Having high bandwidth transfer will exhaust the user equipment (UE)'s battery power quickly. To extend the UE's battery lifetime the 3GPP standards for LTE support Enhanced Discontinuous Reception (DRX). The DRX allow an idle UE to save battery by turning off the radio receiver for a predefined period. Since the Transmission Time Interval (TTI) is related to the size of the data block passed from the higher networks layers to the radio link layer, the DRX scheduler should vary the resource allocation of each user basis on TTI. In this paper, we have evaluated the influences of the TTI sizes as well as the effects of LTE DRX Light and Deep Sleep mode on power consumption for Voice and Web traffic.