Exploiting the untapped potential of mobile distributed computing via approximation

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, I/O data rate–are limited. In this article, the new paradigm of is proposed to harness such potential and to enable real-time computation-intensive mobile applications in resource-limited and uncertain environments. A reduction in time and energy consumed by an application is obtained via approximate computing by decreasing the amount of computation needed; such improvement, however, comes with the potential loss in accuracy. Hence, a Mobile Distributed Computing framework, is introduced to determine the ‘approximable’ tasks in an application and a light-weight algorithm is devised to select the approximate version of the tasks in an application during run time. The effectiveness of the proposed approach is validated through extensive simulation and testbed experiments by comparing approximate versus exact-computation performance.