Loading...
| Friend's email | |
| Your name | |
| Your email | |
| enter code | |
This page was sent successfuly
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 47559 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Movaghar Rahimabadi, Ali
- Abstract:
- Execution speed seriously bothers application developers and users for wearable devices such as Google Glass. Intensive applications like Mobile Augmented Reality (MAR) suffer from significant delays when CPU is busy. Energy is another concern when the devices are in low battery level but users need them for urgency use. To ease such pains, one approach is to expand the computational power by cloud offloading. This paradigm works well when the available Internet access has enough bandwidth. Another way, however, is to leverage nearby devices for computation offloading, which is known as device-to-device (D2D) offloading. In this paper, we present Dandelion, a unified code offloading system for wearable devices that leverages both the nearby devices and cloud for performance acceleration and energy efficiency. To the best of our knowledge, Dandelion is the first generic code offloading system for wearable computing with a reference implementation on Google Glass. Dandelion includes a programmer friendly framework based on Java annota-tion, a lightweight offloading service, and a runtime task scheduler to make offloading decisions. We design a real-time vision-based application and several parallel execution benchmark methods for Dandelion performance evaluation. Extensive experiments on a testbed of Google Glass and Android phones demonstrate that Dandelion achieves up to 5.1X execution speedup and can quickly recover from errors caused by network disruption
- Keywords:
- Device to Device Communications ; Wearable Assistive Device ; Mobile Clouds ; Computation Offloading ; Google Glass ; Mobile Device ; Ambient Cloud
Digital Object List-
محتواي کتاب - view
Bookmark