A Constant-Factor Approximation for Bounded Task Allocation Problem in Crowdsourcing

Shuang Wu, Xiaofeng Gao, Fan Wu, Guihai Chen

Abstract: As the technology advances, there are more and more mobile crowdsensing (MCS) platforms that try to leverage these devices to improve the quality of our life. In this paper, we consider a bounded task allocation problem (BTAP) in MCS platforms that involve the time-sensitive and location-dependent tasks. We first formulate the bounded task allocation problem as an integer programing problem and prove its NP-hardness. Then we propose an approximated algorithm to solve the problem with (2+ε)-approximated ratio and show that it is a tight bound. So far as we know, we are the first to give a constant approximated ratio for such task allocation problems. Finally, we make some simulations to show the performance of our scheme comparing with other two benchmarks.

External IDs:dblp:conf/globecom/WuGWC17