PSAllocator:Multi-Task Allocation for Participatory Sensing with Sensing Capability Constraints

Wang, Jiangtao and Wang, Yasha and Zhang, Daqing and Wang, Feng and He, Yuanduo and Ma, Liantao (2017) PSAllocator:Multi-Task Allocation for Participatory Sensing with Sensing Capability Constraints. In: CSCW '17 Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. ACM, New York, pp. 1139-1151. ISBN 9781450343350

Full text not available from this repository.


This paper proposes a novel multi-task allocation framework, named PSAllocator, for participatory sensing (PS). Different from previous single-task oriented approaches, which select an optimal set of users for each single task independently, PSAllocator attempts to coordinate the allocation of multiple tasks to maximize the overall system utility on a multi-task PS platform. Furthermore, PSAllocator takes the maximum number of sensing tasks allowed for each participant and the sensor availability of each mobile device into consideration. PSAllocator utilizes a two-phase offline multi-task allocation approach to achieve the near-optimal goal. First, it predicts the participants' connections to cell towers and locations based on historical data from the telecom operator; Then, it converts the multi-task allocation problem into the representation of a bipartite graph, and employs an iterative greedy process to optimize the task allocation. Extensive evaluations based on real-world mobility traces show that PSAllocator outperforms the baseline methods under various settings.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
Deposited By:
Deposited On:
14 Mar 2019 16:10
Last Modified:
27 Apr 2022 07:34