Finite-state Markov chain (FSMC) models have often been used to characterize the wireless channel. The fitting is typically performed by partitioning the range of the received signal-to-noise ratio (SNR) into a set of intervals (states). Different partitioning criteria have been proposed in the literature, but none of them was targeted to facilitating the analysis of the packet delay and loss performance over the wireless link. In this paper, we propose a new partitioning approach that results in an FSMC model with tractable queueing performance. Our approach utilizes Jake's level-crossing analysis, the distribution of the received SNR, and the elegant analytical structure of Mitra's producer-consumer fluid queueing model. An algorithm is provided for computing the various parameters of the model, which are then used in deriving closed-form expressions for the effective bandwidth (EB) subject to packet loss and delay constraints. Resource allocation based on the EB is key to improving the perceived capacity of the wireless medium. Numerical investigations are carried out to study the interactions among various key parameters, verify the adequacy of the analysis, and study the impact of error control parameters on the allocated bandwidth for guaranteed packet loss and delay performance.

The perceived video quality in a wireless streaming application strongly depends on the channel's dynamics and the fluctuations of the source bit rate. In this paper, we introduce two channel-adaptive rate control schemes for slowly and fast varying channels, respectively. Both schemes account for the playback buffer occupancy in the joint optimization of the source rate and channel-code forward error correction parameters. For the first scheme, we assume that the channel state does not change during the transmission of a video frame. We optimize the channel-code parameters and maximize the per-frame source rate subject to satisfying a constraint on the probability of delivering the next video frame within a buffer-occupancy-dependent critical time ( ). For the second scheme, we allow the channel state to change within the frame delivery period, and we compute the optimal system parameters and maximize the source rate while satisfying a constraint on the mean frame delivery time. Our schemes aim at maintaining the occupancy of the playback buffer around a predefined threshold value, hence ensuring continuous video playback. Simulation and numerical investigations are carried out to study the interactions among various key parameters and verify the adequacy of the analysis.Index Terms-Adaptive forward error correction (FEC), channel-code optimization, playback buffer control, source rate control, wireless channels.

No abstract

No abstract

Internet of things IoT is playing a remarkable role in the advancement of many fields such as healthcare, smart grids, supply chain management, etc. It also eases people's daily lives and enhances their interaction with each other as well as with their surroundings and the environment in a broader scope. IoT performs this role utilizing devices and sensors of different shapes and sizes ranging from small embedded sensors and wearable devices all the way to automated systems. However, IoT networks are growing in size, complexity, and number of connected devices. As a result, many challenges and problems arise such as security, authenticity, reliability, and scalability. Based on that and taking into account the anticipated evolution of the IoT, it is extremely vital not only to maintain but to increase confidence in and reliance on IoT systems by tackling the aforementioned issues. The emergence of blockchain opened the door to solve some challenges related to IoT networks. Blockchain characteristics such as security, transparency, reliability, and traceability make it the perfect candidate to improve IoT systems, solve their problems, and support their future expansion. This paper demonstrates the major challenges facing IoT systems and blockchain's proposed role in solving them. It also evaluates the position of current researches in the field of merging blockchain with IoT networks and the latest implementation stages. Additionally, it discusses the issues related to the IoT-blockchain integration itself. Finally, this research proposes an architectural design to integrate IoT with blockchain in two layers using dew and cloudlet computing. Our aim is to benefit from blockchain features and services to guarantee a decentralized data storage and processing and address security and anonymity challenges and achieve transparency and efficient authentication service.

In recent years, the growing interest in video-based applications has resulted in a rapid increase in wireless data traffic and meeting the stringent quality-of-experience (QoE) requirements for such type of traffic poses a great challenge given the scarce spectrum. As a consequence, new approaches have been investigated to tackle this problem and one promising solution proposed by researchers is to exploit deviceto-device (D2D) communication in video transmission. D2D communication has been presented as an innovation that can improve the cellular network performance by exploiting the proximity-based service between closely-located devices. It enhances the spectral and energy efficiencies, improves the capacity of the network and reduces the communication delay as well. Despite the above-mentioned advantages, there are some challenges in video transmission over D2D networks that need to be addressed. These issues include proposing methods for improving the quality of video streaming, management of the possible resulting interference between the D2D links and regular cellular links, resource allocation as well as appropriate selection of the mode of operation. Besides, issues related to D2D-based video caching such as clustering, energy consumption and the use of incentive-based schemes have also been discussed. In this paper, we examine the challenges of video streaming over D2D networks and comprehensively review the available solutions proposed in the literature.

No abstract

In this paper, a joint adaptive power allocation and channel coding optimization scheme is proposed. This scheme exploits the difference in importance among bits used to represent an image or video signal. An offline iterative algorithm is developed to find the optimum combination of coding and power to be used for the transmission of individual bits. Optimality here is in the sense of minimizing the mean square error (MSE) which results in a better quality of the reconstructed image. Simulation results show that bits of significant importance should always be coded and allocated most of the transmitted power while bits of less significance may be sent without coding and with less allocated power. This is done while maintaining the average per-bit energy at the same level. Simulation results also show that the proposed combined approach achieves a gain of about 3 dB when compared to the case of coding alone. In addition, the proposed scheme outperforms the case of power allocation alone while reducing the peak-to-average power ratio.