MAUI: Making Smartphones Last Longer with Code Offload
- Eduardo Cuervo ,
- Aruna Balasubramanian ,
- Dae-ki Cho ,
- Alec Wolman ,
- Stefan Saroiu ,
- Ranveer Chandra ,
- Paramvir Bahl
ACM MobiSys 2010 |
Published by Association for Computing Machinery, Inc.
This paper presents MAUI, a system that enables fine-grained energy-aware offload of mobile code to the infrastructure. Previous approaches to these problems either relied heavily on programmer support to partition an application, or they were coarse-grained requiring full process (or full VM) migration. MAUI uses the benefits of a managed code environment to offer the best of both worlds: it supports fine-grained code offload to maximize energy savings with minimal burden on the programmer. MAUI decides at run-time which methods should be remotely executed, driven by an optimization engine that achieves the best energy savings possible under the mobile device’s current connectivity constrains. In our evaluation, we show that MAUI enables: 1) a resource-intensive face recognition application that consumes an order of magnitude less energy, 2) a latency-sensitive arcade game application that doubles its refresh rate, and 3) a voice-based language translation application that bypasses the limitations of the smartphone environment by executing unsupported components remotely.
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Overcoming language barriers using MAUI
The Mobile Assistance Using Infrastructure (MAUI) project enables a new class of CPU- and data-intensive applications that seamlessly augment the cognitive abilities of users by exploiting speech recognition, NLP, vision, machine learning, and augmented reality. it overcomes the energy limitations of handhelds by leveraging nearby computing infrastructure. This demo, recorded in July of 2009, is one of the first, if not the first phone speech-to-speech, language-to-language real-time translator. We used MAUI to perform real-time Spanish to English speech translation using Bing Translator, and Windows Speech Recognition and Speech Synthesis services running on a nearby edge node. This demo was implemented on a Windows Mobile 6.5 HTC AT&T Fuze. The system was first publicly demonstrated live at the Microsoft Research Faculty Summit 2009 on July 14.…