The Internet of Things (IoT) is a collection of different devices that contain different software and hardware technologies to communicate with other devices using unique addressing methods [1,2]. The IoT devices collect data from their surroundings through various sensors and exchange them [2]. As a result, IoT system applied in various fields such as smart homes, smart cities, transportation, e-health care, agriculture, and industries. Cloud Computing (CC) [3] is an emerging computing technology that, due to its capabilities, can provide all the resources needed for the quality of IoT services for IoT. The CC system consists of a large number of Data Centers (DCs), each DC also consists of a large number of Virtual Machines (VMs). But due to the long geographical distance with IoT devices on the network Edge Computing (EC), the CC system is not suitable for delay-sensitive IoT devices such as emergency monitoring, and energy usage measurements from a smart grid, cause long delays that may not be acceptable for some applications in today's world [3,4]. Therefore, to solve this problem, the computing resources should be closer to the network EC devices, and the CC system is very suitable for this and can provide the resources needed to reduce the workload in cloud DC, facilitate task processing, facilitate networking, and facilitate the storage of data generated by IoT sensors, with the lowest amount of communication cost and delay [4-7]. Each server or Fog Computing (FC) node is a virtualized system equipped with a wireless communication unit, simpler processing and computing devices for data, and data storage cards. When FC nodes receive more task requests from IoT devices that exceed their capacity, they can offload some of their load to cloud layer DCs [8-10]. In other words, CC and FC are models of hosting services over the Internet for IoT devices. Fig. 8.1 shows the architecture of IoT-Fog-Cloud system, with CC in the top layer, FC in the middle layer, and IoT devices in the bottom layer. Task Scheduling (TSch) is an effective method for efficient management of virtual resources of the FC and EC environment [11] based on specific constraints and deadlines by different users, which can be used to assign the set of requested tasks by users or existing IoT devices to FC and CC resources in order to execute them [12-16]. According to Fig. 8.1, in the proposed TSch model that is considered for scheduling the task requests of IoT devices in the FC system, Fog Broker (FB) is the main part and is located in the FC layer, which includes three main parts: Task Administrator (TA), Resource Monitoring Service (RMS), and Task Scheduler (TSR). The TA receives all task requests from various IoT devices, and then forwards them to the TSR, maintaining their required resources and attributes. Also, RMS is responsible for collecting information on FC resources and monitoring the status of FC resources. TSR unit is the main core of FB unit, and TSch algorithms are executed in it. According to the characteristics of the sent task requests as well as the capabilities of the available FC resources, the TSR schedules the tasks for execution and processing by assigning the appropriate FC nodes to the task requests. Finally, the processed task requests are sent back to the FB and from there to the respective users or IoT devices [12-16]. In order to allocate FC resources based on the demand of users or IoT devices, fully flexible infrastructure virtualization that uses IoT task Handbook of Whale Optimization Algorithm.
