A Greedy Task Allocation Mechanism for Time-Dependent Mobile Crowdsensing Systems
Moirangthem Goldie Meitei, Ningrinla Marchang · 2022
Task allocation is the process that facilitates the assignment of sensing activities or tasks to participants of a Mobile Crowdsensing (MCS) campaign. In traditional MCS environments, the purpose of task allocation is to maximize the profit of the organizing platform. However, the task allocation approach in these systems fail to deal with the specifics of time-dependent nature of the tasks and the issues that accompany time-dependent task allocation. Hence, we propose a novel mechanism called Time Dependent Task Allocation (TDTA) to allocate tasks in order to achieve maximum profit of the platform in a truly time-dependent mobile crowdsensing environment. In order to realize our goal, we also propose an algorithm for handling time-dependent task allocation called Interval Partition based Greedy Task Allocation (IPGTA). We then compare our proposed IPGTA algorithm with a baseline method and analyze their comparative performances. The simulation results indicate that IPGTA performs positively based on the parameters measured.