A New Harmony Search Based Allocation Algorithm For Location Dependent Tasks In Crowdsensing

Crowd sensing has emerged as a compelling paradigm for collecting sensing data over a vast area.This thesis studies importance of the crowd sensing,variety of its uses in our daily life,the critical task allocation problem in crowd sensing,maximization of the net reward of the platform under the time budget constraints of smartphone users and different quality requirements of tasks.This problem is particularly challenging because of its NP-hardness.Traditional optimization methods cannot solve this problem efficiently in limited time.We propose a Harmony Search(HS)based meta-heuristic allocation algorithm to solve the problem quickly.Our experiments show that our allocation algorithm is better than other existing methods about the reward of the platform.