Real-time task assignment in hyperlocal spatial crowdsourcing under budget constraints

@article{To2016RealtimeTA,
  title={Real-time task assignment in hyperlocal spatial crowdsourcing under budget constraints},
  author={Hien To and Liyue Fan and Luan Tran and Cyrus Shahabi},
  journal={2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)},
  year={2016},
  pages={1-8}
}
  • Hien To, Liyue Fan, +1 author C. Shahabi
  • Published 2016
  • Computer Science
  • 2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Spatial Crowdsourcing (SC) is a novel platform that engages individuals in the act of collecting various types of spatial data. This method of data collection can significantly reduce cost and turnover time, and is particularly useful in environmental sensing, where traditional means fail to provide fine-grained field data. In this study, we introduce hyperlocal spatial crowdsourcing, where all workers who are located within the spatiotemporal vicinity of a task are eligible to perform the task… Expand
A Real-Time Framework for Task Assignment in Hyperlocal Spatial Crowdsourcing
TLDR
This study introduces hyperlocal spatial crowdsourcing, where all workers who are located within the spatiotemporal vicinity of a task are eligible to perform the task (e.g., reporting the precipitation level at their area and time), and studies the hardness of the task assignment problem in the offline setting and proposes online heuristics which exploit the spatial and temporal knowledge acquired over time. Expand
Budget-aware online task assignment in spatial crowdsourcing
TLDR
This paper formally defines a novel problem called Get-aware O nline task A (BOA) in spatial crowdsourcing applications which aims to maximize the number of assigned worker-task pairs under budget constraints where workers appear dynamically on platforms and proposes an efficient threshold-based greedy algorithm called Greedy-RT which utilizes a random generated threshold to prune the pairs with large travel cost. Expand
Specialty-Aware Task Assignment in Spatial Crowdsourcing
TLDR
This paper proposes two efficient heuristics to solve the problem of specialty-aware task assignment in spatial crowdsourcing, where each worker has fine-grained charge for each of their skills, and the goal is to maximize the total number of completed tasks based on tasks' budget and requirements on particular skills. Expand
Multi-Objective Optimization Based Allocation of Heterogeneous Spatial Crowdsourcing Tasks
TLDR
Effective heuristic methods, including multi-round linear weight optimization and enhanced multi-objective particle swarm optimization algorithms are proposed to achieve adequate Pareto-optimal allocation in heterogeneous spatial crowdsourcing. Expand
A reliable task assignment strategy for spatial crowdsourcing in big data environment
TLDR
This paper first studies a practical problem of task assignment, namely reliability aware spatial crowdsourcing (RA-SC), which takes the constrained tasks and numerous dynamic workers into consideration, and reveals the typical property of the proposed problem, and designs an effective strategy to achieve a high reliability of the task assignment. Expand
Predictive Task Assignment in Spatial Crowdsourcing: A Data-driven Approach
TLDR
This work studies a novel spatial crowdsourcing problem, namely Predictive Task Assignment (PTA), which aims to maximize the number of assigned tasks by taking into account both current and future workers/tasks that enter the system dynamically with location unknown in advance and proposes a two-phase data-driven framework. Expand
Task assignment in spatial crowdsourcing: challenges and approaches
  • Hien To
  • Engineering, Computer Science
  • SIGSPATIAL PhD Symposium
  • 2016
TLDR
This paper discusses the unique challenges of spatial crowdsourcing: task assignment, incentive mechanism, worker's location privacy and the absence of real-world datasets. Expand
Toward a real-time and budget-aware task package allocation in spatial crowdsourcing
TLDR
A real-time, budget-aware task package allocation for spatial crowdsourcing (RB-TPSC) with the dual objectives of improving the task allocation rate and maximizing the expected quality of results from workers under limited budgets is proposed. Expand
Task Allocation in Spatial Crowdsourcing: Current State and Future Directions
TLDR
The future trends and open issues of SC task allocation are investigated, including skill-based task allocation, group recommendation and collaboration, task composition and decomposition, and privacy-preserving task allocation. Expand
Destination-aware Task Assignment in Spatial Crowdsourcing
TLDR
A destination-aware task assignment problem that concerns the optimal strategy of assigning each task to proper worker such that the total number of completed tasks can be maximized whilst all workers can reach their destinations before deadlines after performing assigned tasks is studied. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 35 REFERENCES
Task matching and scheduling for multiple workers in spatial crowdsourcing
TLDR
This paper shows that a baseline approach that performs a task-matching first, and subsequently schedules the tasks assigned per worker in a following phase, does not perform well, and adds a third phase in which to improve the assignment per the output of the scheduling phase, and thus further improves the quality of matching and scheduling. Expand
A Server-Assigned Spatial Crowdsourcing Framework
TLDR
This article formally defines the maximum task assignment (MTA) problem in spatial crowdsourcing, and proposes alternative solutions to address these challenges by exploiting the spatial properties of the problem space, including the spatial distribution and the travel cost of the workers. Expand
Maximizing the number of worker's self-selected tasks in spatial crowdsourcing
TLDR
This paper proves that the spatial crowd-sourcing problem in which the workers autonomously select their tasks is NP-hard, and proposes two exact algorithms based on dynamic programming and branch-and-bound strategies for small number of tasks. Expand
GeoCrowd: enabling query answering with spatial crowdsourcing
TLDR
This paper introduces a taxonomy for spatial crowdsourcing, and focuses on one class of this taxonomy, in which workers send their locations to a centralized server and thereafter the server assigns to every worker his nearby tasks with the objective of maximizing the overall number of assigned tasks. Expand
Scalable Spatial Crowdsourcing: A Study of Distributed Algorithms
TLDR
This work proposes a class of approaches that utilizes an online partitioning method to reduce the problem space across a set of cloud servers to construct independent bipartite graphs and solve the spatial task assignment problem in parallel. Expand
Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers
TLDR
It is proved that the RDB-SC problem is NP-hard and intractable, and three effective approximation approaches are proposed, including greedy, sampling, and divide-and-conquer algorithms, which can dynamically maintain moving workers and spatial tasks with low cost. Expand
Maximum Complex Task Assignment: Towards Tasks Correlation in Spatial Crowdsourcing
TLDR
This paper formally defines the Maximum Complex Task Assignment (MCTA) problem and proposes alternative solutions and performs various experiments to investigate and verify the usability of the proposed approach to crowdsource spatial complex tasks. Expand
GeoTruCrowd: trustworthy query answering with spatial crowdsourcing
TLDR
A number of heuristics and utilizing real-world and synthetic data in extensive sets of experiments show that the problem is NP-hard and one can achieve close to optimal performance with the cost of a greedy approach, by exploiting the problem's unique characteristics. Expand
SCAWG: A toolbox for generating synthetic workload for spatial crowdsourcing
TLDR
This work proposes a synthetic workload generator for the SC applications, namely SCAWG1, to produce common datasets for experimentation, thus leading to reproducible research and developed an open-source toolbox to demonstrate the feasibility and applicability ofSCAWG. Expand
A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing
TLDR
This paper argues that existing location privacy techniques are not sufficient for SC, and a mechanism based on differential privacy and geocasting that achieves effective SC services while offering privacy guarantees to workers is proposed. Expand
...
1
2
3
4
...