Complex Task Allocation in Spatial Crowdsourcing: A Task Graph Perspective

Liang Wang, Xueqing Wang, Zhiwen Yu, Qi Han, Bin Guo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we study a novel spatial crowdsourcing scenario, where a complex outsourced task is divided into a group of subtasks with dependency relationships. Under this scenario, we investigate a Task Graph Assignment problem in Spatial Crowdsourcing (TGA-SC), which strives to achieve an optimal task assignment solution, with the goal of minimizing the overall makespan and idle time, simultaneously. We propose two heuristic approaches, namely random walk-based algorithm RwalkS, and layered evolutionary algorithm LayGA to tackle TGA-SC problem. Using two real-world data sets, we implement extensive experiments to show the superiority of our proposed approaches.

Original languageEnglish
Title of host publicationWireless Algorithms, Systems, and Applications - 16th International Conference, WASA 2021, Proceedings
EditorsZhe Liu, Fan Wu, Sajal K. Das
PublisherSpringer Science and Business Media Deutschland GmbH
Pages226-234
Number of pages9
ISBN (Print)9783030861360
DOIs
StatePublished - 2021
Event16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021 - Nanjing, China
Duration: 25 Jun 202127 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12939 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021
Country/TerritoryChina
CityNanjing
Period25/06/2127/06/21

Keywords

  • Directed Acyclic Graph (DAG)
  • Spatial Crowdsourcing
  • Task allocation

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