Predictive Resource Management for Wearable Computing

Achieving crisp interactive response in resource-intensive applications such as augmented reality, language translation, and speech recognition is a major challenge on resource-poor wearable hardware. In this paper we describe a solution based on multi-fidelity computation supported by predictive resource management. We show that such an approach can substantially reduce both the mean and the variance of response time. On a benchmark representative of augmented reality, we demonstrate a 60% reduction in mean latency and a 30% reduction in the coefficient of variation. We also show that a history-based approach to demand prediction is the key to this performance improvement.

• Type: Conference
• Year: 2003
• Where: MOBISYS
• Authors: Dushyanth Narayanan, Mahadev Satyanarayanan
• Keywords: Augmented Reality, Crisp Interactive Response, Mean Latency, MOBISYS 2003, Wireless Networks