Paper—A Novel Genetic and Intelligent Scheme for Service Trading in IoT Fog Networks A Novel Genetic and Intelligent Scheme for Service Trading in IoT Fog Networks https://doi.org/10.3991/ijim.v16i10.30479 Ayoub Alsarhan 1(*) , Bashar Alkhawaldeh 2 , Atalla Fahed Al-Serhan 3 , Muhsen Alkhalidy 2 1 Department of Information Technology, Hashemite University, Zarqa, Jordan 2 Computer Science Department, Hashemite University, Zarqa, Jordan 3 Department of Business Administration, Al-Bayt University, Al-Mafraq, Jordan ayoubm@hu.edu.jo Abstract—The evolution of the current centric cloud to distributed clouds such as fog presents a suitable path to counteract the intolerable processing delays for time-critical applications. It is anticipated that more fog nodes (FN) will be connected to the IoT paradigm to improve the quality of service and meet the requirements of emerging IoT applications. Typically, the owner manages these FN nodes opening up promising doors towards new business opportunities. Thus, this paper considers fog computing driven network that consists of a set of FNs, distributed on the network edge to serve cloud clients. Cloud service provider (CSP), in turn, can offer new services, defne a profle for each service, and set generate revenue. However, new schemes should be developed to make this dynamic business model economically feasible. In this context, we propose a new intelligent scheme for service trading, in which a new genetic algorithm is developed for selecting a set of optimal clients that maximize CSP’s proft using game theory for setting the service price. Game theory captures the confict between cloud clients and CSP, where clients and CSP try to maximize their respective utilities. While CSP attempts to maximize proft, each client tries to negotiate for a lower service price. Simulation results stress that the CSP can maximize proft by utilizing computational resources effciently and selecting service requests with the highest possible bid. Keywords—fog computing, Internet of Things (IoT), game theory, genetic algorithm 1 Introduction The Internet of Things (IoT) has been thriving in terms of the number of connected devices/things as well as the applications. The industry and academia anticipate that all of electronics devices can be soon connected to the internet, revolutionizing our life style. [1–5]. As a result, huge computing resources are needed to process the large data generated by all types of IoT devices [1–4]. The past years have witnessed the signif- icant innovation of cloud computing technologies and rapid deployment of practical iJIM ‒ Vol. 16, No. 10, 2022 191