Improving mobile mass monitoring in the IoT environment based on Fog computing using an improved forest optimization algorithm  

作　　者：Tahere Motedayen Mahdi Yaghoobi Maryam Kheirabadi 

机构地区：[1]Department of Computer Engineering,Neyshabur Branch,Islamic Azad University,Neyshabur,Iran

出　　处：《Journal of Control and Decision》2024年第1期36-49,共14页控制与决策学报（英文）

摘　　要：In the IoT-based users monitor tasks in the network environment by participating in the data collection process by smart devices.Users monitor their data in the form of fog computing(mobile mass monitoring).Service providers are required to pay user rewards without increasing platform costs.One of the NP-Hard methods to maximise the coverage rate and reduce the platform costs(reward)is the Cooperative Based Method for Smart Sensing Tasks(CMST).This article uses chaos theory and fuzzy parameter setting in the forest optimisation algorithm.The proposed method is implemented with MATLAB.The average findings show that the network coverage rate is 31%and the monitoring cost is 11%optimised compared to the CMST scheme and the mapping of the mobile mass monitoring problem to meta-heuristic algorithms.And using the improved forest optimisation algorithm can reduce the costs of the mobile crowd monitoring platform and has a better coverage rate.

关 键 词：Internet of Things mobile mass monitoring forest optimization algorithm chaos theory fuzzy system 

分 类 号：TP391.44[自动化与计算机技术—计算机应用技术]