Computer!! The one everyone uses almost every day in this busy world, a device capable of handling tasks from simple addition to complex tasks like launching rockets, but to sustain these tasks, and be a part of the huge networks like the internet and serve as an integrated part of IoT (internet of things) many different devices like cloud computing, servers are developed which can handle the request and return the appropriate response to the device. However, IoT device face certain issues among which the obtainability of on-going energy heads in one of the biggest issue and reason of this is because of the enormous amount of information that is created by using IoT devices and handling this information is one of the biggest constraints. To reduce these issues, many different schedulers were introduced like the optimized schedule task requests which enhances system productivity and performance, and the task scheduler whose objective is to divide tasks based on the available resources so the it reduces make span and time consumption. Hence to improve cloud computing many different meta-heuristics systems for task scheduling were introduced, but their throughput was far from the optimal state and needed upgrading. Keeping that in mind, this paper proposes an Opposition based sunflower optimization (OSFO) algorithm for enhancing the throughput of already available task schedulers in terms of cost, energy and makespan.
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