A Webpage Offloading Framework for Smart Devices.
Saved in:
| Title: | A Webpage Offloading Framework for Smart Devices. |
|---|---|
| Authors: | Zhang, Jin, Liu, Weilai, Zhao, Wenjian, Ma, Xuan, Xu, Haocong, Liu, Chengcheng, Yu, Haiyang, Gong, Xiaoli |
| Source: | Mobile Networks & Applications; Oct2018, Vol. 23 Issue 5, p1350-1363, 14p |
| Subject Terms: | JAVASCRIPT programming language, CLOUD computing, HOME wireless technology, CELL phones, ENERGY consumption |
| Abstract: | Smart devices such as mobile phones and smart TVs are widely used for enriching our daily activities. Although their power source and processing speed are limited, it is necessary for these devices to provide certain computation power. To enhance computation capability on smart devices, offloading is proposed as one of the effective approaches. However, it requires extra efforts for developers to implement the offloading mechanism for each application. HTML5 standard provides a feature called Web Worker which allows web pages to spawn separate threads as workers. Since each worker holds individual execution environments and contexts, it is appropriate for offloading without complex partition. In this paper, we present a generic offloading framework for JavaScript Web Worker named Web Worker Offloading Framework (WWOF). This framework can offload the workers from browsers to the cloud easily and seamlessly. The Web Worker runs on an offloading server instead of on the browser, and exchanges data with clients via WebSocket. To prove the feasibility of this framework, we evaluated several benchmarks on different platforms including PCs, tablets, mobile phones and smart TVs. It is verified that this framework is able to suppress the devices’ power consumption and to increase the execution speed, while running a heavy workload. [ABSTRACT FROM AUTHOR] |
| Copyright of Mobile Networks & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
Full Text Finder 
Nájsť tento článok vo Web of Science Be the first to leave a comment!