Optimal Selection of Crowdsourcing Workers Balancing Their Utilities and Platform Profit

Sujan Sarker, Md Abdur Razzaque, Mohammad Mehedi Hassan, Ahmad Almogren, Giancarlo Fortino, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

In a mobile crowdsourcing system (MCS), a platform outsources sensing tasks to numerous mobile worker devices. The collected data are analyzed and the processed information is shared among many other interested users. The platform pays the workers for the sensing data and earns money from the users receiving processed information services. Distributing the sensing workloads among the potential workers so as to maintain the required data quality and to make a reasonable amount of profit is a challenging problem for such a platform. In this paper, we develop a workload allocation policy that makes a reasonable tradeoff between worker utilities and platform profit. It quantifies the utility (i.e., the quality of sensed data) of a worker as a function of worker mobility, current location, and past sensing records. The workload allocation problem is formulated as a multiobjective nonlinear programming (MONLP) problem which aims to make the desired tradeoff between worker utilities and platform profit. The allocation problem is shown to be NP-hard and thus we develop two greedy algorithms with relaxed constraints to achieve polynomial time solutions. Performance of the proposed workload allocation policy is evaluated in a distributed computation environment using MATLAB. The results show its effectiveness compared to state-of-the-art methods in terms of platform profit, quality of sensing data, and request service satisfaction.

Original languageEnglish (US)
Article number8731644
Pages (from-to)8602-8614
Number of pages13
JournalIEEE Internet of Things Journal
Volume6
Issue number5
DOIs
StatePublished - Oct 2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • Crowdsourcing
  • platform profit
  • reputation
  • sensing quality
  • utility

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