Work Capacity of Regulated Freelance Platforms: Fundamental Limits and Decentralized Schemes

Avhishek Chatterjee, Lav R. Varshney, Sriram Vishwanath

Research output: Contribution to journalArticlepeer-review


Crowdsourcing of jobs to online freelance platforms is rapidly gaining popularity. Most crowdsourcing platforms are uncontrolled and offer freedom to customers and freelancers to choose each other. This works well for unskilled jobs e.g., image classification with no specific quality requirement since freelancers are functionally identical. For skilled jobs e.g., software development with specific quality requirements, however, this does not ensure that the maximum number of job requests is satisfied. In this paper, we determine the capacity of regulated freelance systems, in terms of maximum satisfied job requests, and propose centralized schemes that achieve capacity. To ensure decentralized operation and freedom for customers and freelancers, we propose simple schemes compatible with the operation of current crowdsourcing platforms that approximately achieve capacity. Furthermore, for settings where the number of job requests exceeds capacity, we propose a scheme that is agnostic of that information, but is optimal and fair in declining jobs without wait.

Original languageEnglish (US)
Pages (from-to)3641-3654
Number of pages14
JournalIEEE/ACM Transactions on Networking
Issue number6
StatePublished - Dec 2017


  • Terms-Freelance platforms
  • capacity
  • decentralized algorithms
  • queuing

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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