Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/2709 2019 2019 Part-time Research Scholar, Jamal Mohammed College, Baharathidasan University, Trichy, Tamil Nadu State, India Syed Syed Associate Prof. in Computer Science Dept., Jamal Mohammed College, Baharathidasan University, Trichy, Tamil Nadu State, India T. Abdul Razzak Affiliation Department of Computer Science, Umm Al Qura University, Makkah, Saudi Arabia Muhammad Abid Jamil Due to the continual advancements in the Internet of Things (IoT), which generate enormous volumes of data, the cloud computing infrastructure recently has received the most significance. to meet the demands made by the network of IoT devices. It is anticipated that the planned Fog computing system would constitute the next development in cloud computing. The optimal distribution of computing capacity to reduce processing times and operating costs is one of the tasks that fog computing confronts. In the IoT, fog computing is a decentralized computing approach that moves data storage and processing closer to the network's edge. This research article discusses a unique technique for lowering operating expenses and improving work scheduling in a cloud-fog environment. Non-dominated sorting genetic algorithm II (NSGA-II) is a proposal that is presented in this paper. Its purpose is to allocate service requests with the multi-objective of minimising finishing time and running cost. Determining the Pareto front that is associated with a group of perfect solutions, which are sometimes referred to as non-dominated solutions or Pareto sets, is the fundamental objective of the Pareto NSGA-II. There is a contradiction between the environmental and economic performances, which is shown by the Pareto set of sub-optimal solutions that are the consequence of the bi-objective issue. 2024 2024 122 137 10.54216/JISIoT.120209 https://www.americaspg.com/articleinfo/18/show/2709