Mobile CrowdSensing (MCS) has recently become a powerful paradigm that recruits users to cooperatively perform various tasks. In many realistic settings, users participate in real time and we have to… Click to show full abstract
Mobile CrowdSensing (MCS) has recently become a powerful paradigm that recruits users to cooperatively perform various tasks. In many realistic settings, users participate in real time and we have to recruit them in an online manner. The existing works usually formulate the online recruitment problem as a budgeted optimal stopping problem with submodular user utility, while we first argue that not only the budget but also the time constraints can jointly influence the recruitment performance. For example, if we have less budget but plenty of time, we should recruit users with more patience. Second, considering the user’s cooperative willingness, its contribution may be diminishing or even irregular. Hence, we also need to address not only submodular cases but also their non-submodular utility. In this paper, we study the online user recruitment problem with (non-)submodular utility under the budget and time constraints. To deal with the two constraints, we first estimate the number of users to be recruited and then recruit them in segments. Moreover, we extend the segmented strategy with a non-submodular utility, which has the submodularity ratio
               
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