Abstract—In this paper, a network-aware and source-aware video streaming system is proposed to support interactive multiuser communications within single-cell and multicell IEEE 802.11 networks. Unlike the traditional streaming video services, the strict delay constraints of an interactive video streaming system pose more challenges. These challenges include the heterogeneity of uplink and downlink channel conditions experienced by different users, the multiuser resource allocation of limited radio resources, the incorporation of the cross-layer design, and the diversity of content complexities exhibited by different video sequences. With the awareness of video content and network resources, the proposed system integrates cross-layer error protection mechanism and performs dynamic resource allocation across multiple users. We formulate the proposed system as to minimize the maximal end-to-end expected distortion received by all users, subject to maximal transmission power and delay constraints. To reduce the high dimensionality of the search space, fast multiuser algorithms are proposed to find the near-optimal solutions. Compared to the strategy without dynamically and jointly allocating bandwidth resource for uplinks and downlinks, the proposed framework outperforms by 2.18 7.95 dB in terms of the average received PSNR of all users and by 3.82 11.50 dB in terms of the lowest received PSNR among all users. Furthermore, the proposed scheme can provide more uniform video quality for all users and lower quality fluctuation for each received video sequence. Index Terms—Cross-layer design, joint uplink and downlink optimization, multiuser video communication, network-aware, wireless local area networks. I.

In this paper, we consider a multi-user optical grid environment where the optical grid network is shared among multiple users who have a high demand for data processing. In such multi-user grid environment, since the supercomputer can start the data processing only after the corresponding data file has reached it, one critical problem is how to effectively schedule large data file transfers on the optical grid network. In this paper, we propose four dynamic scheduling algorithms to address the issue of large file transfers on multi-user optical grid network. Two objectives, namely the efficiency and fairness, are considered to evaluate the performance of each scheduling algorithm. Efficiency aims at how to achieve the best overall quality of grid service, and fairness regards the service quality deviation among grid users. We study the performance of each algorithm, and a tradeoff between efficiency and fairness is shown by our results.

ABSTRACT We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Abstract—Efficient delivery of multimedia contents over wireless network is essential for future communication networks. However, content distribution and network engineering are traditionally studied separately, which leads to suboptimal network performance. In this paper, we consider the problem of scheduling and resource allocation for multi-user video streaming over downlink OFDM channels. The video streams are precoded with the SVC coding scheme, which offers both quality and temporal scalabilities. The OFDM technology provides the maximum flexibility of resource allocation in terms of time, frequency, and power. We propose a gradient-based scheduling and resource allocation algorithm, which explicitly takes account of video contents, deadline requirements, and the previous transmission results when calculating users ’ priority weights. Simulation results show that our proposed algorithm always outperforms the contentblind and deadline-blind algorithms, with a performance gain as much as 6 dB in terms of average user PSNR improvement in a congested network. I.

In multiuser rate allocation in a wireless network, strategic users can bias the rate allocation by misrepresenting their bandwidth demands to a base station, leading to an unfair allocation. Game-theoretical approaches have been proposed to address the unfair allocation problems caused by the strategic users. However, existing approaches rely on a time-consuming iterative negotiation process. Besides, they cannot completely prevent unfair allocations caused by inconsistent strategic behaviors. To address these problems, we propose a Search Based Pricing Mechanism to reduce the communication time and to capture a user's strategic behavior. Our simulation results show that the proposed method significantly reduce the communication time as well as converges stably to an optimal allocation. Keywords: