A Participatory Budgeting based Truthful Budget-Limited Incentive Mechanism for Time-Constrained Tasks in Crowdsensing Systems
Chattu Bhargavi, Vikash Kumar Singh
TL;DR
The paper addresses time-constrained crowdsensing with a limited Government budget by introducing BULINC, a two-tier mechanism that first uses city-dweller votes to fund a subset of task requesters and then schedules those tasks into nonconflicting time slots while selecting executors under per-task budgets. The approach combines participatory budgeting with interval-based task slotting and a greedy, critical-payment allocation to ensure truthfulness, individual rationality, and budget feasibility, backed by theoretical guarantees and probabilistic analysis. Empirical comparisons against state-of-the-art baselines show BULINC achieves higher executor utility, maintains budget feasibility, and scales reasonably, illustrating its potential for transparent, participatory data collection in city sensing. The work contributes a novel integration of participatory budgeting into mobile crowdsensing, provides rigorous economic properties, and offers practical guidance for implementing budget-limited incentives in time-constrained, multi- requester/multi-executor settings.
Abstract
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.