Research On Task Allocation Algorithm Of Crowdsensing Based On Influence Propagation Models

With the rapid development of network technology and smart terminal devices,crowdsensing with mobility has attracted considerable attention as a novel crowdsourcing model.Unlike typical crowdsourcing,crowdsensing includes precise time and space criteria,that can access to time-specific sensing data by people in a specific time and space.In other words,workers must travel to a specified area at a given time to perform and complete a sensing task.The problem of task allocation has emerged as the most important research topic in crowdsourcing.Reasonable task allocation ensures the effectiveness and development of the crowdsourcing system.The current research results have the following limitations: The issue of understaffing arises,resulting in poor task completion;the spatiotemporal validity and relevance of workers and tasks are overlooked.Task allocation is researched in light of workers’ execution skill,time constraints,and other factors.The following are the key research findings:In crowdsourcing task allocation based on the influence propagation model,firstly,to address the problem of a lack of crowdsourcing workers,an initial propagation user selection algorithm is designed to recruit workers to participate in crowdsourcing.The successfully recruited workers can auction tasks for various time periods by submitting auction information.Secondly,a problem of task allocation with worker time limitations is given,with the goal of maximizing the platform utility.The reverse auction incentive mechanism is then combined with task allocation using an algorithm,and it is shown that the reverse auction incentive mechanism satisfies the properties of computational validity,individual rationality,feasibility,and authenticity.Finally,simulations show that the suggested selection algorithm has a wider range of influence than other algorithms and the task allocation method is more competitive and performant than other algorithms.In crowdsourcing task allocation based on discrete particle swarm optimization,firstly,the task allocation optimization issue with task space-time limitations is proposed to maximize social welfare.Secondly,a task allocation technique based on discrete particle swarm optimization is devised to examine the correlation between workers and tasks for the task allocation problem.Finally,simulation results reveal that the algorithm outperforms other algorithms in terms of competitiveness and performance.