Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks
For network engineers designing energy-efficient real-time wireless systems, this work provides a more efficient solution to a known scheduling problem.
This paper addresses the problem of minimizing energy consumption in real-time wireless networks by controlling packet transmission rates. The authors propose an algorithm that decomposes the optimal sample path through critical tasks, achieving significantly faster performance than the existing MoveRight algorithm.
It has been shown that using appropriate channel coding schemes in wireless environments, transmission energy can be significantly reduced by controlling the packet transmission rate. This paper seeks optimal solutions for downlink transmission control problems, motivated by this observation and by the need to minimize energy consumption in real-time wireless networks. Our problem formulation deals with a more general setting than the paper authored by Gamal et. al., in which the MoveRight algorithm is proposed. The MoveRight algorithm is an iterative algorithm that converges to the optimal solution. We show that even under the more general setting, the optimal solution can be efficiently obtained through an approach decomposing the optimal sample path through certain "critical tasks" which in turn can be efficiently identified. We include simulation results showing that our algorithm is significantly faster than the MoveRight algorithm. We also discuss how to utilize our results and receding horizon control to perform on-line transmission scheduling where future task information is unknown.