Most of previous video recording devices in mobile vehicles commonly store captured video contents locally.With the rapid development of 4G/Wi Fi networks,there emerges a new trend to equip video recording devices wit...Most of previous video recording devices in mobile vehicles commonly store captured video contents locally.With the rapid development of 4G/Wi Fi networks,there emerges a new trend to equip video recording devices with wireless interfaces to enable video uploading to the cloud for video playback in a later time point.In this paper,we propose a QoE-aware mobile cloud video recording scheme in the roadside vehicular networks,which can adaptively select the proper wireless interface and video bitrate for video uploading to the cloud.To maximize the total utility,we need to design a control strategy to carefully balance the transmission cost and the achieved QoE for users.To this purpose,we investigate the tradeoff between cost incurred by uploading through cellular networks and the achieved QoE of users.We apply the optimization framework to solve the formulated problem and design an online scheduling algorithm.We also conduct extensive trace-driven simulations and our results show that our algorithm achieves a good balance between the transmission cost and user QoE.展开更多
To cope with the rapid growth of mobile video, video providers have leveraged cloud technologies to deploy their mobile video service system for more cost-effective and scalable performance. The emergence of Software-...To cope with the rapid growth of mobile video, video providers have leveraged cloud technologies to deploy their mobile video service system for more cost-effective and scalable performance. The emergence of Software-Defined Networking(SDN) provides a promising solution to manage the underlying network. In this paper, we introduce an SDN-enabled cloud mobile video distribution architecture and propose a joint video placement, request dispatching and traffic management mechanism to improve user experience and reduce the system operational cost. We use a utility function to capture the two aspects of user experience: the level of satisfaction and average latency, and formulate the joint optimization problem as a mixed integer programming problem. We develop an optimal algorithm based on dual decomposition and prove its optimality. We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee user experience.展开更多
基金supported in part by the National Science Foundation of China under Grant 61272397,Grant 61572538,Grant 61174152,Grant 61331008in part by the Guangdong Natural Science Funds for Distinguished Young Scholar under Grant S20120011187
文摘Most of previous video recording devices in mobile vehicles commonly store captured video contents locally.With the rapid development of 4G/Wi Fi networks,there emerges a new trend to equip video recording devices with wireless interfaces to enable video uploading to the cloud for video playback in a later time point.In this paper,we propose a QoE-aware mobile cloud video recording scheme in the roadside vehicular networks,which can adaptively select the proper wireless interface and video bitrate for video uploading to the cloud.To maximize the total utility,we need to design a control strategy to carefully balance the transmission cost and the achieved QoE for users.To this purpose,we investigate the tradeoff between cost incurred by uploading through cellular networks and the achieved QoE of users.We apply the optimization framework to solve the formulated problem and design an online scheduling algorithm.We also conduct extensive trace-driven simulations and our results show that our algorithm achieves a good balance between the transmission cost and user QoE.
基金supported by the State Key Program of National Natural Science Foundation of China(Grant No.61233003)National Natural Science Foundation of China(Grant No.61503358)
文摘To cope with the rapid growth of mobile video, video providers have leveraged cloud technologies to deploy their mobile video service system for more cost-effective and scalable performance. The emergence of Software-Defined Networking(SDN) provides a promising solution to manage the underlying network. In this paper, we introduce an SDN-enabled cloud mobile video distribution architecture and propose a joint video placement, request dispatching and traffic management mechanism to improve user experience and reduce the system operational cost. We use a utility function to capture the two aspects of user experience: the level of satisfaction and average latency, and formulate the joint optimization problem as a mixed integer programming problem. We develop an optimal algorithm based on dual decomposition and prove its optimality. We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee user experience.
