REEWA: Runtime energy estimation for web activities on smartphones

Smartphone users spend more than 80% of their phone time accessing web information, which could cause undesirably large energy drain. To provide web information, a web activity may invoke asynchronous execution in different hardware devices. Thus, traditional energy estimation methods based on system statistics are usually insufficient to capture the secluded energy cost. In this paper, we propose REEWA, a runtime energy estimation framework for web activities on smartphones. In sharp contrast to the traditional modeling methods, REEWA features a design to provide highly accurate and low-overhead energy estimation based on hardware performance counters that can accurately record hardware-level events. Specifically, REEWA features (1) a set of energy models for smartphone hardware components involved in web activities, which are built based on their respective performance counters; (2) a correlation study on the counter selection process that provides the best tradeoff between the estimation accuracy and overhead; (3) a performance counter management mechanism for activity deployment. We prototyped and evaluated REEWA in two real android smart-phones. The results show that, compared to traditional estimation methods, REEWA achieves an average 33% higher estimation accuracy with a negligible overhead (less than 1%, worst-case). We applied REEWA to support heterogeneous core scheduling for web activities, which can help reduce 40% energy consumption.