Distributed ACO Based Reputation Management in Crowdsourcing

Crowdsourcing is an economical and efficient tool that hires human labour to execute tasks which are difficult to solve otherwise. Verification of the quality of the workers is a major problem in Crowd sourcing. We need to judge the performance of the workers based on their history of service and it is difficult to do so without hiring other workers. In this paper, we propose an Ant Colony Optimization (ACO) based reputation management system that can differentiate between good and bad workers. Using experimental evaluation, we show that, the algorithm works fine on the real scenario and efficiently differentiate workers with higher reputations.