Optimal Resource and Task Scheduling for IoT

The internet of things, or IoT, is a system of interrelated computing devices through which it is possible to transfer data over a network without the help of a human or computer interaction. These devices are provided with unique identifiers (UIDs) and embedded within hardware, objects, electronics, Internet connectivity, animals or people. They are equipped with a supportive Wireless Sensor Network (WSN). Each sensor node is connected to a gateway node through internet and these acts as a repository of user queries; they preprocess and separated into spatial and temporal tasks. The preprocessed tasks should be executed in a suitable sensor node or in a group of sensor nodes, which will make it effective for the application. Resource and task scheduling for the IoT systems was studied which minimizes average data rate and minimum task performing rates of IoT devices. To achieve this goal, we are proposing a hybrid resource and task scheduling algorithm by combining priority non pre-emptive algorithm and Ant Colony Optimization (ACO) to prioritize the tasks and find optimal path to direct them to its concerned sensor node for execution. Here we concentrate on the tasks which do not have a real-time requirement and can be stored in the task queues of the IoT devices and performed later.