Energy-Efficient Future High-Definition TV

The rapidly growing IPTV market has resulted in increased traffic volumes raising concerns over Internet energy consumption. In this paper, we explore the dynamics of TV viewing behavior and program popularity in order to devise a strategy to minimize energy usage. We evaluate the impact of our strategy by calculating the power consumption of IPTV delivered over an IP-over-WDM network, considering both standard definition and high definition TV. Caches are used to reduce energy consumption by storing the most popular programs at nodes closer to the end user. We then use our knowledge of viewing behaviors to generate a time-driven content replacement strategy to maximize cache hit ratios and minimize energy use. We develop a mixed integer linear programming (MILP) model to evaluate the power consumption of the network while performing time-driven content replacements on caches and validate the results by simulation. Finally, we extend our model to perform content replacements on caches with sleep-mode capabilities which can save power by reducing their size. Our results show that time-based content replacements with such variable caches increase cache hit ratios and so reduces the overall power consumption by up to 86% compared to no caching. Our findings also show that more power savings are achieved for high definition TV compared to standard definition TV, so this strategy will be beneficial in the long term.