An intelligent mobile based decision support system for retinal disease diagnosis
Decision Support Systems
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Energy consumption is one of the main concerns that refrain users from fully exploiting their smart phone capabilities. Guided by energy measurements on smart phones, which show that some services performed in parallel require less energy than their stand-alone executions, we investigate the possibility to delay some services to the time when other services have already been scheduled in such a way the total energy consumption is minimized once all services are accomplished. We define two new energy optimization problems, called {\em Single Overlapping Pair (SOP)} and {\em Multiple Overlapping Pairs (MOP)}. The former assumes that a delay-tolerant service must be paired with a single pre-scheduled service, the latter that a delay-tolerant service may be paired with multiple pre-scheduled services. We propose new algorithms to solve both SOP and MOP optimally in polynomial time, when the set of services to be executed is known in advance. Finally, we evaluate the benefits of the energy-efficient pairing strategy via simulations on synthetic traces. The results of our preliminary experiments show a neat energy gain achievable by pairing executions, if compared to stand-alone executions. Indeed, the solution for SOP shows a 30% decrease in energy consumption, while the one for MOP shows a 70% decrease in energy demanding.