Jingwu Cui

System Scheduling for Multi-Description Video Streaming Over Wireless Multi-Hop Networks

Providing real-time multimedia applications over wireless multi-hop networks is a challenging problem because the wireless channels are highly sensitive to delay, interference and topology changes. Multiple description coding (MDC), as a new emerging error-resilient technique, has been widely used recently in wireless video transmission. Its fundamental principle is to generate multiple correlated descriptions such that each description approximates the source information with a certain level of fidelity. Inevitably, MDC introduces many description streams which may influence each other and thus, reasonable system scheduling is needed to provide a satisfied video quality. The novelty of this work is to investigate the optimal distributed scheduling for multiple competing MDC streams in a resource-limited wireless multi-hop network. This is achieved by joint optimization of MDC, rate control and multipath routing. Two joint optimal algorithms, namely a distributed rate control and routing (DRCR) and a simplified DRCR algorithm, are proposed to solve this problem with constraints that arise from the multiple description streams among multiple users via multiple paths. Both algorithms are designed in a distributed manner that is amenable to on-line implementation for wireless networks. Theoretical analysis and simulation results are provided which demonstrate the effectiveness of our proposed joint schemes.

Distributed Scheduling for Video Streaming over Multi-Channel Multi-Radio Multi-Hop Wireless Networks

An important issue of supporting multi-user video streaming over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resources while, at the same time, to meet each videos QoS (Quality of Service) requirement. In this work, we study the problem of video scheduling over multi-channel multiradio multi-hop networks with the goals of minimizing the video distortion. At first, we construct a general distortion model according to the networks transmission mechanism, as well as videos rate-distortion characteristics. Then, by joint considering the channel assignment, rate allocation and routing, we develop a fully distributed scheduling scheme to get an optimal QoS performance. Furthermore, the realization of the distributed scheduling scheme through cooperation among the channel, link and source is the highlight of this paper. Extensive simulation results are provided which demonstrate the effectiveness of our proposed scheme.

A Robust Resolution-Enhancement Scheme for Video Transmission Over Mobile Ad-Hoc Networks

Historically, Error-Resilient (ER) video transmission and Super-Resolution (SR) image reconstruction techniques have evolved separately. In this paper, we propose a coordinated application of ER and SR to enhance the resolution of image transmitted over mobile ad-hoc networks. In order to combat error propagation, a flexible multiple description coding method based on shifted 3-D SPIHT (3-D Set Partitioning In Hierarchical Trees) algorithm is presented to generate variable independent descriptions (substreams) according to the network condition. And then, a novel unequal error protection strategy based on the priority level is provided to assign a higher level of error protection to more important parts of bitstream. Moreover, a robust SR algorithm is proposed in the presence of different kinds of packet loss rate to enhance the image resolution. Experimental results indicate that the proposed robust resolution-enhancement scheme outperforms the competing methods from the aspects of PSNR (Peak-Signal-to-Noise Ratio) and visual quality under different packet loss rates.

Cross-Layer Rate Allocation for Multimedia Applications in Pervasive Computing Environment

An important issue for supporting multimedia applications in multiple heterogeneous networks, a typical pervasive computing environment, is how to optimize the rate allocation by intelligently utilizing the available network resources while, at the same time, to meet each applications QoS (Quality of Service) requirement. In this work, we develop and evaluate a rate allocation scheme in terms of audio and video applications based on a cross-layer design framework. At first, we construct a general distortion model according to the observed parameters in each network, as well as each applications rate-distortion characteristic. Then, the rate allocation is formulated as a convex optimization problem that minimizes the sum of the expected distortion of all applications. Furthermore, the realization of the distributed rate allocation algorithm for achieving an optimal or close-to-optimal end-to-end QoS under the overall limited resource budget is the highlight of this paper. Simulation results are provided which demonstrate the effectiveness of our proposed distributed rate allocation scheme.

Cooperative Spectrum Sensing Using Free Probability Theory

Free probability theory, which has became a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large random matrices. In this paper, using free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radios. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance compared with the energy detection techniques even for the case of a small sample of observations.

Robust cooperative spectrum sensing schemes for fading channels in cognitive radio networks

In cognitive radio systems, cooperative spectrum sensing can detect the presence of the primary user accurately. In practice, however, since the sensing observations are forwarded to a data collector through fading channels, the sensing performance is severely degraded. To deal with this problem, in this paper, we first propose a secondary user selection based cooperative spectrum sensing method to improve sensing performance by decreasing the reporting errors introduced by the fading channels. More specifically, only the secondary users with better signal-to-noise ratio (SNR) for reporting channels are allowed to send their local binary decisions (0 or 1) to the data collector while the others will send nothing. Additionally, we further propose a diversity based cooperative spectrum sensing method which applies existing space-time coding. By exploiting space diversity in CR network, the reporting errors introduced by the fading channel can be decreased and then the sensing performance is improved significantly. For either proposed cooperative spectrum sensing method, the sensing performance is derived and the analytical performance results are given. Our analysis and numerical results verify that proposed methods outperform the conventional cooperative spectrum sensing with OR-rule by taking into account the error effect on the reporting channels.

Green multimedia communications over Internet of Things

In this paper, we consider a power-aware multimedia communications over internet of things (IoT). Specifically, we consider a generic IoT scenario where a multimedia server provides heterogeneous applications without knowing the applications quality of experience (QoE) model and playout period. Our objective aims at dynamically adjusting the power allocation for each application over a uncertain period to maximize the system overall mean opinion score (MOS). Note that the practical QoE model can be observed over time, but the underlying functional relationship between the power and MOS is unknown. The highlight of this paper is to develop a dynamic powering algorithm, in which one learns the satisfaction function and optimizes power-aware user satisfaction with on-line operation. More precisely, the proposed algorithm performance is measured in terms of loss which denotes the MOS loss compared to the optimal one. Numerical simulation results validate the efficiency of the proposed algorithm.

Utilization-based VM consolidation scheme for power efficiency in cloud data centers

Cloud computing offers utility-oriented services to users, which is supported by large-scale data center. Although virtualized data centers provide high performance computing service, they also consume enormous amount of power. To solve the problem, dynamic consolidation of Virtual Machines (VMs) is considered as an efficient way to reduce power consumption and guarantee Quality of Service (QoS). Live migration is applied into the dynamic consolidation, which allows VMs to be migrated to other hosts and aims to minimize the number of hosts in data centers. However, the migration overhead is essential to be taken into account and massive migrations will lead to performance degradation and extra power consumption. In this paper, we propose a utilization-based migration algorithm (UMA) to migrate VMs to stable hosts, which efficiently reduces migration time and power consumption. Experiment results show that our UMA can reduce about 77.5%-82.4% migrations and save up to 39.3% -42.2% power consumption compared with the MinPower policy.

Toward green service in cloud: From the perspective of scheduling

In this paper, we address energy-oriented service in cloud computing environment. Specifically, we consider a generic cloud scenario where different kinds of servers provide multi-class service without knowing the user demand in advance. In general, this work provides a green scheduling in the cloud by explicitly addressing 1) the number of the server for each service, and 2) a dynamic scheduling scheme that specifies how to assign the users to different servers. At first, energy-aware scheduling in cloud is formulated by an optimization problem where QoS constraint is expressed by a probability formulation. Then, we propose a random dynamic scheduling scheme to deal with the demand uncertainty based on Monto-Carlo sampling. Moreover, we show that the proposed scheduling scheme possesses a desirable property since it inherits from the problem of known user demand. Subsequently, we present exact steps to implement the proposed scheduling. Finally, numerical simulation results are provided to validate its efficiency.

Media-Aware Distributed Scheduling over Wireless Body Sensor Networks

Distributed scheduling for hybrid media flows over wireless body sensor network faces three technical challenges: constrained communication channel, random node placement and strict transmission latency. In this work, we study this problem by jointly considering the above three challenges to achieve the minimum media distortion and optimal network resource utilization. At first, we construct a general flow transmission model according to networks transmission mechanism, as well as media-aware flows characteristics. Then, a distributed scheduling scheme is proposed based on dynamic network resource update. It is proved that the proposed scheme can achieve the optimal scheduling solution with an exponential convergence rate, and an explicit form of the asymptotic convergence rate is provided. Furthermore, the realization of the distributed scheduling scheme through the collaboration between the network and the sources is the highlight of this paper. Extensive simulation results are provided to demonstrate the effectiveness of our proposed scheme.