Design and evaluation of characteristic incentive mechanisms in Mobile Crowdsensing Systems

摘要: Abstract In this paper we identify basic design issues of Mobile Crowdsensing Systems and investigate some characteristic challenges. We define the components an MCS – Task, Server Crowd functions describing/governing their interactions. three qualitatively different types Tasks; (a) those whose added utility is proportional to size (b) progress Task (c) reversely Task. For a given type finite Budget, makes offers agents based on Incentive Policy. On other hand, each agent that receives offer decides whether it will undertake or not, inferred cost (computed via Cost function) Join policies, take into account several aspects, such as number quality participating agents, execution possible network effects, present in real-life systems. evaluate impact performance selected for both Server, terms execution, Budget efficiency Workload balance Crowd. Experimental findings demonstrate key features various policies indicate are more effective enabling efficiently manage its while providing satisfactory incentives effectively executing system Tasks. Interestingly, incentive current crowd participation achieve better trade-off between completion budget expense.