Provisioning Load Balancing in Time-Sensitive Task Allocation for Mobile Crowdsensing
Moirangthem Goldie Meitei, Ningrinla Marchang · Research Square · 2022
Abstract Task allocation is the mechanism which enables the allotment of sensing tasks to participating users in a Mobile Crowdsensing (MCS) environment. While conventional task allocation techniques focus on maximizing profit for either the platform or the user, our proposed task allocation scheme, called Load Balanced Task Allocation (LBTA) is geared towards user-oriented task allocation in order to mainly address altruistic MCS campaigns in which participants voluntarily contribute towards a common goal such as in citizen science-based projects. This paper deals with the problem of task allocation using a load balanced approach while trying to maximize the allocation of tasks at the same time. The proposed LBTA algorithm has been compared with a known algorithm and their relative performances have been analysed. Simulation results demonstrate that the proposed algorithm exhibits favourable performance for different crowdsensing scenarios.