## 2 Literature Review  
Previous studies are related to scheduling algorithms to minimize monetary costs and execution time in the cloud, multiple VMs and different price models to get the lowest cost and faster workflow execution times. In line with this research, particle swarm optimization (PSO) algorithms including non-dominated sort PSO (NPSSO) and \(\varepsilon\)-fuzzy PSO were developed. NSPSO is a development of PSO to improve the selection of each particle so that non-domination comparisons are more effective. \(\varepsilon\)-Fuzzy PSO combines a fuzzy mechanism and PSO to find the best agreed on solution [10; 11; 12]. [PERSON] and [PERSON] [13] developed the heterogeneous earliest-finish-time (MOHEFT) multi-objective method and applied it for scheduling on Amazon EC2. MOHEFT is a development of HEFT, where HEFT is intended for a single object solution and MOHEFT develops it further so that it can be a solution for multiple objects. SPEA2 is an improvement of NSGAII and SPEA2 achieved by improving the NSGAII and SPEA2 evolutionary algorithms [14]. However, none of the mentioned algorithms can be directly applied to the cloud environment because they are mostly designed for traditional computing environments. [PERSON] et al. [15] designed fuzzy dominance sort heterogeneous earliest finish (FDHEFT) method which is a development of HEFT in order to reduce the cost and execution time of workflows simultaneously. FDHEFT is divided into two phases, namely the task prioritizing phase and the instance selection phase. The task prioritizing phase will determine the priority of each task and the instance selection phase will determine the best task to execute. Compared to MOHEFT, FDHEFT has a better execution time and gets a better solution with fuzzy dominance sort [3; 13; 14; 15; 16; 17; 18]. Intelligent systems are very useful in this modern world and important for business as an aid to improve the business processes strength as well as reduce weaknesses to become a leader in the industry. Intelligent systems over the internet are also known as the Internet of Things. This is due to devices such as mobile phones, refrigerators, watches and others being able to connect to the internet to collecting data and analyze it and thus provide convenience to the user. The devices can help users to perform better and improve productivity, help decision making and it has become a trend for the intelligent systems to operate within digital ecosystems [19; 20; 21]. One example intelligent systems over the internet to boot business processes are the so-called Smart Retail Systems. These smart retail systems help businesses by collecting data from customers when they enter the door with the help of a device such as a camera. The camera is connected to the cloud and starts facial recognition, collecting data, analyzing and predicting customer behavior. As a result, businesses can identify which of the product or services that most customers need and want, what product is suitable for this type of gender or businesses can eventually advertise trending products or services from the result thus successfully increasing the profitability of the business [5; 22; 23; 24]. The next benefit or good circumstances that intelligent systems over the internet can provide is traffic monitoring systems. This system is the combination of both software and devices as well as connections to the cloud. Traffic lights are connected to the cloud and collect data, analyze it and make decisions for it on how many seconds or minutes should the traffic go to green, yellow and red. If accidents happen or a traffic jam has occurred, the monitoring systems will automatically reanalyze the data and make new decisions for that. There are also some cons for this system, like when there is a power failure, the system will be shut down and there will eventually be traffic problems. When the power is back on, the traffic monitoring systems need to be reset in order for it to run normally and collect data again, reanalyze and make its own decisions which takes a while.