Optimized Distributed Resource Management in Fog Computing by Using Ant-Colony Optimization

Increasing smart and connected devices in Internet of things (IoT), many connected devices send processing requests to cloud computing systems. Cloud computing introduces latency in communication and data transfer, especially in realtime and time sensitive processings. Fog computing is a promising solution to improve the efficiency and reduce the data volume transported to the cloud involving computing and storage capabilities of edge in an efficient manner. Distributed nature of Fog computing require to implement of efficient distributed resource management systems. In this paper we address resource management in fog computing and try to find the shortest route to resources in a distributed manner by applying ant colony optimization (ACO). In details, we apply swarm intelligence feature of ant colony and its combination with traveling salesman to find the shortest route. We further propose the parameter optimization techniques to improve the performance of ACO. We evaluate the performance of proposed algorithm using computer simulations. The simulation results confirm the effectiveness of proposed method. .