Open AccessDynamic Multi‐Task Allocation Method for Passenger Diffusion in Mobile Crowd Sensing
Author(s) -
Weijin JIANG,
Sijian LYU
Publication year - 2021
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2021.07.005
Subject(s) - computer science , heuristics , task (project management) , matching (statistics) , selection algorithm , incentive , crowdsensing , process (computing) , selection (genetic algorithm) , mathematical optimization , real time computing , algorithm , artificial intelligence , computer security , engineering , statistics , mathematics , systems engineering , economics , microeconomics , operating system
This paper aims to solve the problem of low efficiency, high cost and instability in opportunistic network transmission in the process of mobile group intelligence perception task allocation. Two multi‐task dynamic distribution methods based on Lowest cost Participant selection algorithm (LC‐PSA) based on user incentive cost and Least number Participant selection algorithm (LN‐PSA) based on number of users are proposed respectively. Through these two algorithms, the goal of minimizing the number of people and moving distance required for the task and reducing the system's incentive cost is achieved. Simulation experiments show that compared with similar algorithms, the number of participants in the task distribution scheme selected by the LN‐PSA algorithm is reduced by 24.0%, and the system resource consumption is lower, which can provide stable services for the system when users are insufficient in emergencies. Compared with the traditional greedy heuristics algorithm, the LC‐PSA algorithm reduces the total system cost by 37.74% and has better overall performance in the comparison experiment.