IEEE Access (Jan 2020)
Energy-Efficient Biocooperative Video-Aware QoS-Based Multiobjective Cross-Layer Optimization for Wireless Networks
Abstract
Video streaming is becoming increasingly popular due to the emergence of different video applications and services and the exponential growth in demand for multimedia applications. Streaming video over an error-prone network is technically challenging due to unpredictable channel conditions and demands for different types of quality of service (QoS) from various types of applications. The traditional Open System Interconnection (OSI) layered approach is designed for data transfer, and it performs specific operations independent of other layers. This approach may not work efficiently for wireless video streaming applications in which video quality is greatly affected by the network condition, link quality, and ability of the system to adapt to the channel conditions. This paper is primarily aimed at developing an algorithm to enhance video streaming over wireless local area networks using a biocooperative video-aware QoS-based multiobjective cross-layer optimization (MO-CLD) approach. First, the wireless video streaming optimization problem is formulated and modeled. To solve the optimization problem, we proposed a bioinspired optimization algorithm to jointly optimize the source rate and packet rate loss using dual decomposition. The simulation results show that the proposed biocooperative multiobjective optimization scheme using particle swarm optimization (PSO) relatively maintains and enhances the video streaming quality in error-prone transmission environments to ultimately support wireless multimedia applications and services. More importantly, the end-to-end delay and complexity are reduced significantly, which eventually lead to improvements in the scheme efficiency and video quality compared to basic cross-layer optimization (B-CLD).
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