Dynamic Resource Allocation for Scalable Video Streaming in OFDMA Wireless Networks

Abstract

Mobile video streaming is a successful example of Cyber-Physical-Social Systems (CPSS). How to schedule network resources and provide better mobile video streaming services for mobile users are very important. Scalable video streaming is regarded as a promising technology in wireless networks where the cognitive femtocells are overlaid within the coverage area of a macrocell network. In this paper, we study dynamic resource allocation for scalable video streaming over cache-enabled wireless networks with time-varying channel conditions. We formulate the scalable video streaming problem as a stochastic optimization problem which aims at maximizing the time-averaged system utility subject to the timeaveraged video cache constraint at the server and the cross-tier interference constraint on the primary user under the sparse deployment scenario of femtocells. By employing the Lyapunov optimization theory, we design a dynamic cache and resource allocation (DCRA) algorithm to solve this problem. Furthermore, the problem is decomposed into three subproblems, i.e., video layer selection, cache placement, and wireless resource allocation. Via solving these subproblems, we derive the video layer selection and cache placement strategies, and a wireless resource allocation algorithm to manage the cross-tier interference. Simulation results demonstrate the advantages of the proposed DCRA for streaming scalable video over time-varying wireless networks.

Research on Vehicle-to-Road Collaboration and End-to-End Collaboration for Multimedia Services in the Internet of Vehicles

“…In the face of different network channel environments in practical application scenarios, users can selectively receive the video enhancement layer. Users with good channel conditions can receive the base layer and more enhancement layers [5] . To better guarantee the video quality and allocate resources reasonably and efficiently in the Telematics scenario, this paper considers reducing the pressure for macro base stations by increasing the joint work of 5G base station type RSU and UAV mobile base stations.…”

“…Author Feng [14] proposes a joint cache allocation and multicast delivery scheme for reactive systems delivering video on demand, and develops a joint design of cache bandwidth allocation algorithm and delivery mechanism for active systems playing video periodically. Jiao [15] investigates dynamic resource allocation for scalable video streams over cache-enabled wireless networks with time-varying channel conditions, and proposes a dynamic cache and resource allocation ( DCRA) algorithm. Author S. Fang [16] proposes a stochastic network algorithm (SNC)-based approach to obtain upper bounds on the random playback latency of an in-vehicle video content delivery network with cacheenabled RSUs.…”

“…Since the channel gain of the base layer multicast group is based on the worst user, it can be expressed as (5) Assuming that the received rate is and the transmit power is , the required bandwidth of the base layer is calculated based on Shannon's formula (6) where represents Gaussian noise. The enhancement layer is provided for the user multicast group, which is jointly provided by the macro base station, the 5G base station type RSU, and the UAV base station.…”

“…To guarantee the transmission, the policy needs to satisfy . In order to achieve the average data volume downloaded by the macro base station as smaller, the amount of RSU data required by the vehicle user to request and the amount of data required by the MBS to download, respectively, are noted as (15) (16) (17) Where the amount of data of a single video file is denoted as and the requested probability is denoted as . The optimization problem can be expressed as (18) The analysis of the model based on a hierarchical Markov chain, the root state 0 represents the state that the user makes a request for the file, each layer represents a time slot, and the possible cases in the chain are passed through the sequence of states .…”