Social Welfare-Based Task Assignment in Mobile Crowdsensing

Mobile crowdsensing (MCS) is a novel data-collection paradigm in the internet of things. Social welfare an important factor task allocation because it integrates interests all parties involved MCS and represents societal satisfaction. The ultimate goal to maximize social as much possible. Existing optimization research does not consider moral psychological characteristics people real world. In this study, real-world situation considered. A strategy, which includes two stages, formulated for allocation. generalized shortest path algorithm optimal pricing are proposed each stage. To evaluate algorithms, extensive simulation experiments conducted on datasets. experimental results demonstrate that algorithms produce desired effects, strategy significantly increases by 19% compared another method.