A truthful mechanism for time-bound tasks in IoT-based crowdsourcing with zero budget

Crowdsourcing is a process of engaging a ‘ crowd ’ or a group of common people for accomplishing the tasks. In this work, the time-bound tasks allocation problem in IoT-based crowdsourcing is investigated in strategic setting. The proposed model consists of multiple task providers (or task requesters) and several IoT devices (or task executors), and each of the task providers carries a task that have start time and completion time. Each of the participating IoT devices provide a preference ordering (order of their interest for the tasks) over a subset of tasks. Given the time bound tasks and ranking (or preference ordering) of the task executors, the objectives are: (1) to assign the tasks to different slots so that they are non-conflicting in nature, and (2) to allocate at most one task to each of the task executors from their respective preference ordering. To achieve the above objectives, a truthful mechanism is proposed namely T ruthful M echanism for T ime-bound T asks in IoT-based Crowdsourcing (TMTTC). Through theoretical analysis, it is proved that TMTTC satisfies the properties such as computational efficiency , truthfulness , Pareto optimality , and The Core . Through simulation, it is shown that TMTTC performs better than benchmark mechanism on the ground of truthfulness .