<title>Proxy-Assisted Power-Friendly Streaming to Mobile Devices</title>

Abstract

Since multimedia applications are known to be resource-hungry and mobile devices are resource-poor, in

<title>Managing heterogeneous wireless environments via Hotspot servers</title>

“…This leads to inefficient power management for portables with multiple diverse communication interfaces and for systems where many client devices are present. Power-friendly transformations to media streams delivered to a client, and proxy-assisted prediction of packet delivery have been presented in [36]. Recent work [23] focused on managing power and QoS on the client side for multiple WNICs without considering other clients in the environment.…”

Chameleon: Application-Level Power Management

“…The proposed techniques either use dynamic voltage and frequency scaling (DVFS) [3,18,19,22,25,31,32] or application/middlewarebased adaptation [10,11,24,26] for energy savings. DVFS approaches extract energy savings by varying the processor speed; the techniques do not affect the amount of processing performed by the application-the processing is merely spread over longer time periods by lowering CPU speeds.…”

“…Application or middleware-based adaptation techniques trade the computational overhead for application quality; energy savings are extracted by reducing video quality [24,26], document quality [10] or data fidelity [11], and thus, the processing overheads. Proxy-based adaptation for reducing streaming video quality has been explored in [24,26].…”

An energy-aware framework for coordinated dynamic software management in mobile computers

“…Except for the work in [11,26], all the above works target non-energy related resources. Most investigate software adaptation for communication (network bandwidth) and computation resources (CPU cycles).…”

“…The Odyssey system was also extended to enable data fidelity adaptation for energy reduction [11]. The same philosophy is used in [26] to transform the requested network data stream to reduce receiving and decoding energy. All these approaches are OS-based and input data-centric.…”