The growing interest for Internet of Things (IoT) both in public and private sector has introduced many research challenges in the areas of computational science, machine learning, cyber security and networking. The primary factor for having a robust IoT application is to keep the network alive, i.e., to ensure there is sufficient number of nodes up and running. This enables necessary data sessions from source IoT nodes to destination IoT nodes required for data fusion and artificial reasoning for intelligent application running over this ad-hoc network. In this paper, we propose our autonomous wireless charger platform in which a autonomous network unit will traverse through the critical area of the network and charges the IoT devices to ensure the network is alive. We will present a cross-layered optimization framework which jointly performs wireless charging power management, scheduling, interference avoidance, and routing. Our objective is to maximize the minimum sessions bottle neck, while all the nodes are alive within a specific interval.