Two-level Computation Offloading to Optimize the Energy Consumption of UAV-mounted Edge Nodes

The utilization of Unmanned Aerial Vehicles (UAVs) in Internet of Things (IoT) applications has recently gained widespread popularity. Recently, fixed-edge servers have been used for computation offloading services to IoT devices. These nodes have troublesome installations in geographically constrained areas and are not easy to replace in case of sudden failure in remote areas. UAV nodes can be utilized as mobile Edge servers to overcome these problems. Their importance can be visualized in various applications like disaster management, offshore industries, military applications, healthcare, and wildlife conservation. Since UAVs run on battery, saving energy becomes a primary challenge. This paper proposes an architecture that provides a two-level offloading mechanism for IoT devices to minimize energy consumption. When computation offloading happens from IoT devices to their respective UAV-mounted Edge nodes, they do not need to wait if Edge server capacity is exhausted. In such a case, UAV offloads to another suitable one in its network. In this way, Edge nodes are more efficiently utilized than when a single UAV-mounted Edge node has to serve all its IoT devices. Using our model, we can also provide better services to IoT users. The proposed model uses game theory to utilize the Nash Equilibrium to solve this problem. The simulation work evaluates the accuracy of the proposed architecture and finds a significant difference in energy consumption between the case of offloading from IoT devices to respective UAVs and the case of the proposed model.