Dynamic deployment and quality adaptation for mobile augmented reality applications

Abstract

With the increasing popularity of smartphones and netbooks, more and more applications are developed for the mobile platform. Notwithstanding the recent advances in mobile hardware, most mobile devices still lack sufficient resources (e.g. CPU power, memory) to execute complex multimedia applications such as augmented reality. Application developers also have difficulties to cope with the changing device context (e.g. network connectivity, remaining battery life) and the many different hardware platforms and operating systems to run applications on. Therefore, we introduce the concept where the developer can provide different configurations of an application, each having different resource requirements and a different quality offered to the end user. The middleware framework presented in this paper will select and deploy the configuration offering the best quality possible for the current connectivity and available resources. As these change over time, the framework will dynamically adapt the configuration and deployment at runtime, enhancing the quality by offloading parts of the application when a remote server is discovered, or gracefully degrading the quality when the network connection is lost. Based on experimental results on the augmented reality use case the performance and effectiveness of our middleware has been characterized in different scenarios.

Mobile computation offloading architecture for mobile augmented reality, case study: Visualization of cetacean skeleton

“…Some studies, such as [18][19] [20], point to the need for MAR applications must adapt to the constraints of mobile platforms on which to run. This concept is not new, since previous work treated this adaptation as plasticity and is widely used in the context of development of type Rich-Client Applications [21].…”

Cloud- Based Mobile Augmentation in Mobile Cloud Computing

“…These resources include the remote cloud data centres [20], group of nearby mobile computing devices [21], hybrid model with heterogeneous computing resources [22] or to the proximate resourceful computing devices [23].…”

Adaptive deployment and configuration for mobile augmented reality in the cloudlet

“…At runtime a clone VM is instantiated at the server side, and the application transparently switches between execution at the device or at the clone. Giurgiu et al [5] and Verbelen et al [6] use OSGi components offloadable units. Monitoring information is used to build a graph model of the software, from which graph cutting algorithms calculate the optimal deployment.…”