.png){kind=icon}
.png){kind=icon}
Return
A statistical prediction-based scheme for energy-aware multimedia data streaming
.png){kind=icon}
PRE
AI
DOI：10.1109/WCNC.2004.1311401.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The proliferation of multimedia-capable mobile devices and ubiquitous high-speed network technologies to deliver multimedia objects has fueled the demand of mobile streaming multimedia. A necessary criterion for the mass acceptance of mobile devices is acceptable battery, life of these devices. In this paper, we explore linear prediction-based client-side strategies to reduce the wireless network interface card (WNIC) energy consumption by transitioning the WNIC to a lower power consuming sleep state. The basic idea of this strategy is to selectively choose proper periods of time to suspend communication by switching the WNIC to sleep state. A linear prediction-based time series forecasting technique is used to predict future no-data intervals. Simulation results show that linear prediction-based strategy gives better results than those based on simple averaging [6].
Keywords:
linear prediction
time series forecasting
mobile multimedia
energy-aware streaming
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
0
Papers:
10
Citations:
0
Organization
No organization information available