Energy Efficiency Analysis and Optimization on Mobile Video Wireless Delivery

Micro-electronic industry has been boosting the capability of wireless mobile devices on full-scale. However, battery, as the only power source of most mobile devices, is experiencing a relatively slow development. Therefore, how to optimally utilize the limited battery energy on mobile devices under a predefined performance requirement becomes a critical issue. On the other hand, it is still unclear that how the battery capacity consumption is allocated on different working pattern of a specific video codec under various tempo-spatial scales and parameters, which has posed a design challenge on power management on multimedia communication system. Furthermore, an optimization method is needed to be proposed and experimentally tested to achieve the tradeoff between the computational complexity and the distortion of multimedia delivery in order to discover the relationship and interaction between computational parameters of multimedia communication and battery capacity consumption. From point of view of battery-aware system design and optimization, batteries discharging characteristics and a precise model under different thermal condition still need an exhaustive investigation. In this paper, we proposed a dynamic frequency scaling algorithm to optimize the energy efficiency on each sensor node under the different ambient thermal condition. A new battery model with thermal parameter is proposed and analyzed in order to predict the scheduling of dynamic frequency scaling. Experiment results indicate the efficiency and effectiveness of the proposed optimization framework, and the insight of the relationship between scheduling of dynamic frequency scaling and battery discharging curves under different environmental temperature. Adviser: Song C