Abstract
With the emergence of smart grids, adopting dynamic energy pricing models has become both possible and desirable. With such a pricing dynamicity, great savings in energy costs can be achieved in telecommunication systems when energy is procured efficiently through carefully designed real-time resource schedulers. Broadly speaking, existing scheduling algorithms can be categorized into two classes: online and off-line. Off-line algorithms are not practical merely because of their need for prior knowledge of future system information. In this paper, we propose an efficient online power procurement and allocation scheduler that maximizes a long-term system utility function without the need for prior knowledge of future system information, where the system utility function is expressed in such a way that the gain coming from serving the users and the cost of the procured energy are traded off for one another. We propose an approach that allows us to derive closed-form instantaneous energy procurement and resource allocations that are functions only of the actual instantaneous system parameters. Our approach computes the optimal power procurement and users’ allocation per time slot in an online fashion with very low computational complexity. Using simulations, we study the efficiency of the proposed approach under various parameters and quantify the energy costs that our approach can potentially save.
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