Energy and Delay Aware Task Assignment Mechanism for UAV-based IoT Platform

Unmanned Aerial Vehicles (UAVs) are gaining much momentum due to the vast number of their applications. In addition to their original missions, UAVs can be used simultaneously for offering Value Added Internet of Things Services (VAIoTS) from the sky. VAIoTS can be achieved by equipping UAVs with suitable IoT payloads and organizing UAVs’ flights using a central System Orchestrator (SO). SO holds the complete information about UAVs, such as their current positions, their amount of energy, their intended use-cases or flight missions, and their onboard IoT device(s). To ensure efficient VAIoTSs, there is a need for developing a smart mechanism that would be executed at the SO in order to take into account two major factors: i) the UAVs’ energy consumption and ii) the UAVs’ operation time. To effectively implement this mechanism, this paper presents three complementary solutions, named Energy Aware UAV Selection (EAUS), Delay Aware UAV Selection (DAUS), and Fair Trade-off UAV Selection (FTUS), respectively. These solutions use Linear Integer Problem (LIP) optimizations. While the EAUS solution aims to reduce the energy consumption of UAVs, the DAUS solution aims to reduce the operational time of UAVs. Meanwhile, FTUS uses a bargaining game to ensure a fair trade-off between the energy consumption and the operation time. The results obtained from the performance evaluations demonstrate the efficiency and the robustness of the proposed schemes. Each solution demonstrates its efficiency at achieving its planned goals.