A Task Allocation In IoT Using Ant Colony Optimization

Internet of Things (IoT) is a paradigm provides a possibility to connect several heterogeneous Things/Devices into internet. The heterogeneity of those devices is a big challenge in terms of traffic heterogeneity and services requirements. Furthermore, for the network stability, several considerations must be taken into account in order to execute any task by any IoT node. More precisely, the nodes random tasks distribution leads to fail some nodes and also to reduce the network lifetime. A task can be composed at least of one subtask, which holds a collection of capabilities that must be verified to obtain a relevant service. In this contribution, an algorithm based on the Ant Colony Optimization (ACO) to address the IoT task allocation issues. We assume that each subtask has only one capability, and the goal is to distribute the task capabilities to the most competent nodes for reducing resource consumption of the network. The simulation result shows that our proposed algorithm is more efficient also adaptable in terms of the desired capabilities and the shortest path length.