Hierarchical Data Aggregation with Data Offloading Scheme for Fog Enabled IoT Environment
作者机构:Department of Computer Science and EngineeringKings College of EngineeringPunalkulam613303TamilnaduIndia Department of Computer Science and EngineeringUniversity College of EngineeringAriyalur621704TamilnaduIndia
出 版 物:《Computer Systems Science & Engineering》 (计算机系统科学与工程(英文))
年 卷 期:2023年第44卷第3期
页 面:2033-2047页
核心收录:
学科分类:0809[工学-电子科学与技术(可授工学、理学学位)] 08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:Internet of things fog computing barnacles mating optimizer data offloading data aggregation
摘 要:Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things(IoT)*** the emergence of IoT-based services,the industry of internet-based devices has *** number of these devices has raised from millions to billions,and it is expected to increase further in the near ***,additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user *** data aggregation models for Fog enabled IoT environ-ments possess high computational complexity and communication ***-fore,in order to resolve the issues and improve the lifetime of the network,this study develops an effective hierarchical data aggregation with chaotic barnacles mating optimizer(HDAG-CBMO)*** HDAG-CBMO technique derives afitness function from many relational matrices,like residual energy,average distance to neighbors,and centroid degree of target ***,a chaotic theory based population initialization technique is derived for the optimal initial position of ***,a learning based data offloading method has been developed for reducing the response time to IoT user requests.A wide range of simulation analyses demonstrated that the HDAG-CBMO technique has resulted in balanced energy utilization and prolonged lifetime of the Fog assisted IoT networks.