Profit Maximization in Mobile Crowdsourcing: A Competitive Analysis

Mobile Crowdsourcing, which uses a crowd of workers to complete computer-complexity tasks, has become more and popular. How maximize the total profit, is difference between task utility worker costs, key design goal in such crowdsourcing system. However, this problem extremely hard because even offline situation, been proved be NP-hard. In online we need consider not only future unknown arrivals, but also heterogeneity both tasks workers. paper, address challenging from following aspects. To solve problem, first build an optimization framework formulate by explicitly modelling costs. Then, under framework, efficient assignment algorithms assign analyze efficiency our proposed algorithms, develop dual-fitting method primal objective dual objective. We prove that designed can achieve constant competitive ratio 2. Finally, conduct extensive trace-driven simulations demonstrate outperform baseline nearly 20% terms profit achieved.