Crowdsensing, also known as participatory sensing, is a method of data collection that involves gathering information from a large number of common people (or individuals), often using mobile devices or other personal technologies. This paper considers the set-up with multiple task requesters and several task executors in a strategic setting. Each task requester has multiple heterogeneous tasks and an estimated budget for the tasks. In our proposed model, the Government has a publicly known fund (or budget) and is limited. Due to limited funds, it may not be possible for the platform to offer the funds to all the available task requesters. For that purpose, in the first tier, the voting by the city dwellers over the task requesters is carried out to decide on the subset of task requesters receiving the Government fund. In the second tier, each task of the task requesters has start and finish times. Based on that, firstly, the tasks are distributed to distinct slots. In each slot, we have multiple task executors for executing the floated tasks. Each task executor reports a cost (private) for completing the floated task(s). Given the above-discussed set-up, the objectives of the second tier are: (1) to schedule each task of the task requesters in the available slots in a non-conflicting manner and (2) to select a set of executors for the available tasks in such a way that the total incentive given to the task executors should be at most the budget for the tasks. For the discussed scenario, a truthful incentive based mechanism is designed that also takes care of budget criteria. Theoretical analysis is done, and it shows that the proposed mechanism is computationally efficient, truthful, budget-feasible, and individually rational. The simulation is carried out, and the efficacy of the designed mechanism is compared with the state-of-the-art mechanisms.

翻译：群智感知，也称为参与式感知，是一种数据收集方法，涉及从大量普通人（或个人）中收集信息，通常使用移动设备或其他个人技术。本文考虑在策略性环境中存在多个任务请求者和多个任务执行者的场景。每个任务请求者拥有多个异质任务以及一个预估的任务预算。在我们提出的模型中，政府拥有一个公开已知且有限的资金池。由于资金有限，平台可能无法向所有可用的任务请求者提供资金。为此，在第一层级中，由城市居民对任务请求者进行投票，以决定获得政府资金的任务请求者子集。在第二层级中，每个任务请求者的任务都有开始时间和结束时间。基于此，首先将任务分配到不同的时隙。在每个时隙中，我们有多个任务执行者来执行所发布的任务。每个任务执行者报告完成所发布任务的成本（私有信息）。基于上述讨论的场景，第二层级的目标是：(1) 以无冲突的方式将任务请求者的每个任务安排在可用时隙中；(2) 选择一组执行者来执行可用任务，使得支付给任务执行者的总激励不超过任务预算。针对所讨论的场景，设计了一种基于诚实的激励机制，同时考虑了预算约束。理论分析表明，所提出的机制在计算上高效、诚实、预算可行且个体理性。进行了仿真实验，并将所设计机制的有效性与当前最优机制进行了比较。