Energy-aware adaptation for mobile applications
ACM SIGOPS Operating Systems Review
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Automatic performance setting for dynamic voltage scaling
Wireless Networks
Run-time modeling and estimation of operating system power consumption
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
PARM: Power Aware Reconfigurable Middleware
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Middleware for efficient power management in mobile devices
Mobility '06 Proceedings of the 3rd international conference on Mobile technology, applications & systems
Autonomic Feature Selection for Application Classification
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Energy Consumption of Mobile YouTube: Quantitative Measurement and Analysis
NGMAST '08 Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies
IEEE Journal on Selected Areas in Communications
Practical power modeling of data transmission over 802.11g for wireless applications
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Supporting energy-driven adaptations in distributed environments
Proceedings of the 1st Workshop on Middleware and Architectures for Autonomic and Sustainable Computing
Hi-index | 0.00 |
The growing complexity of mobile applications coupled with slow progress in the development of batteries has led to the requirement of energy-awareness in mobile devices. Nevertheless, no general solution exists for supporting energy-awareness across various mobile platforms and application domains. To address the above mentioned problems, we propose a middleware framework which utilizes the concept of application classification, and power estimation to accomplish application-specific power management, as well as providing basic support for active power management and fundamental services for energy-aware applications. To this end, we have implemented a basic prototype reflecting the functionalities of our framework, and evaluated it using mobile YouTube.