An adaptive duty-cycle scheme for GPS scheduling in mobile location sensing applications

Mobile location sensing applications (MLSAs) represent an emerging genre of applications that exploit Global Positioning System (GPS) technology and facilitate location-based services. The design of MLSAs must incorporate a tradeoff between information accuracy and energy efficiency because GPS technology is energy expensive and unaffordable for most MLSA platforms, which are battery-powered and therefore resource-constrained. In this study, based on our observation that the reception of GPS signals is spatially and temporally correlated, we propose a novel algorithm called the Adaptive Duty Cycle (ADC) scheme to exploit the spatio-temporal localities in the design of GPS scheduling algorithms. Using a comprehensive set of evaluations, as well as realistic hiker mobility traces, we evaluate the ADC scheme in terms of data granularity and power consumption. The results demonstrate that the scheme can achieve the Pareto optimum in all test cases. Moreover, the scheme is simple, effective, and generalizable to other mobile location sensing applications.