An iterative semi-static bandwidth sharing and scheduling policy is proposed that provably approaches the quality of the optimal static sharing policy while updating operator coordination only once per hyperperiod.
Maximizing Real-Time Video QoE via Bandwidth Sharing under Markovian setting
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abstract
We consider the problem of optimizing Quality of Experience (QoE) of clients streaming real-time video, served by networks managed by different operators that can share bandwidth with each other. The abundance of real-time video traffic is evident in the popularity of applications like video conferencing and video streaming of live events, which have increased significantly since the recent pandemic. We model the problem as a joint optimization of resource allocation for the clients and bandwidth sharing across the operators, with special attention to how the resource allocation impacts clients' perceived video quality. We propose an online policy as a solution, which involves dynamically sharing a portion of one operator's bandwidth with another operator. We provide strong theoretical optimality guarantees for the policy. We also use extensive simulations to demonstrate the policy's substantial performance improvements (of up to ninety percent), and identify insights into key system parameters (e.g., imbalance in arrival rates or channel conditions of the operators) that dictate the improvements.
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Adaptive Bandwidth Sharing for Optimizing QoE of Real-Time Video
An iterative semi-static bandwidth sharing and scheduling policy is proposed that provably approaches the quality of the optimal static sharing policy while updating operator coordination only once per hyperperiod.