Name
Abstract | ||
|---|---|---|
Energy consumption of wireless data transmission, a significant part of the overall energy consumption on a mobile device, is context-dependent—it depends on both internal and external contexts, such as application workload and wireless signal strength. In this paper, we propose an event-driven framework that can be used for efficient power management on mobile devices. The framework adapts the behavior of a device component or an application to the changes in contexts, defined as events, according to developer-specified event-condition-action (ECA) rules that describe the power management mechanism. In contrast to previous work, our framework supports complex event processing. By correlating events, complex event processing helps to discover complex events that are relevant to power consumption. Using our framework developers can implement and configure power management applications by editing event specifications and ECA rules through XML-based interfaces. We evaluate this framework with two applications in which the data transmission is adapted to traffic patterns and wireless link quality. These applications can save roughly 12 percent more energy compared to normal operation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TC.2012.113 | IEEE Trans. Computers |
Keywords | Field | DocType |
wireless data transmission,mobile device,power management,complex event processing,efficient power management,configure power management application,complex event,power consumption,framework developer,correlating event,event-driven framework,power management mechanism,wireless networks,mobile communication,energy management,pattern matching,user interfaces,energy efficiency,mobile computing,xml | Mobile computing,Power management,Energy management,Wireless network,Data transmission,Computer science,Efficient energy use,Complex event processing,Real-time computing,Energy consumption,Distributed computing | Journal |
Volume | Issue | ISSN |
61 | 12 | 0018-9340 |
Citations | PageRank | References |
5 | 0.42 | 17 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Xiao | 1 | 546 | 46.32 |
| Wei Li | 2 | 447 | 68.94 |
| Matti I. Siekkinen | 3 | 500 | 43.06 |
| Petri Savolainen | 4 | 101 | 8.17 |
| Antti Yla--Jaaski | 5 | 158 | 12.04 |
| Pan Hui | 6 | 4577 | 309.30 |