Mobile computing is one of the largest untapped reservoirs in today's pervasive computing world as it has the potential to enable a variety of in situ, real-time applications. Yet, this computing paradigm suffers when the available resources-such as energy in the network, CPU cycles, memory, and I/O data rate-are limited. In this paper, the new paradigm of approximate computing is proposed to harness such potential and to enable energy-intensive mobile applications. A reduction in time and energy consumed by an application is obtained via closed-loop approximate computing by decreasing the amount of computation needed; such improvement, however, comes with the potential loss in accuracy. We present our framework on how approximation can be applied at different levels, namely, at the application level and the input data level. The effectiveness of the proposed closed-loop approach is validated both through extensive simulation and testbed experiments by comparing approximate versus exact-computation performance.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computational Theory and Mathematics