Dynamic Path Selection for Cloud-based Multi-Hop Multi-Robot Wireless Networks

Abstract

In a cloud robotics system, communication between robots and between robots and the cloud are crucial from the application prospective. Due to the nature of the network technology (predominantly wireless) and nature of the network devices, direct communication between robots and between robots and the cloud is not feasible. Multi-hop communication is the only feasible solution in such scenarios. In Multi-hop communication, finding the optimal route between the end points is a complicated task. This becomes further complicated when the communicating nodes are mobile and do not have enough communication and computational power as in the case of robots. Though robots can compute the end-to-end path, it is a complicated task for them and is sometimes infeasible in practice due to their low computation and communication power. To overcome this problem, we propose a multi-hop communication model called Dynamic Path Selection using Cloud-based Multi-hop Multi-Robot (DPS-CMM) model, where instead of the robots, the cloud decides the end-to-end communication path which the robots need to use to communicate among themselves. In this model, the cloud provides the optimal path information of the robots to the Access Points (APs) such that source robot establishes a reliable communication path through the APs to reach the destination robot. In this paper, the DPS-CMM model provides the information of network topology and computes the path selection at the cloud instead of computing the same in robots level thereby increasing the life time of robotic networks. To validate this model, we use combination of NS-3 and Matlab-based simulations and compare our scheme with the existing state-of-the-art solutions.