Energy-Efficient Task Offloading and Trajectory Design for UAV-based MEC Systems
Mohamed El-Emary, Ali Ranjha, Diala Naboulsi, Razvan Stanica
Abstract
Sixth-generation and mobile edge computing (MEC) systems are expected to empower a wide range of applications. Unmanned aerial vehicles (UAVs) can play a vital role in improving network connectivity. Hence, our problem is to minimize the user equipment (UE) energy consumption during task offloading in a UAV assisted MEC system. To address the formulated NP-hard problem, we propose task scheduling and assignment algorithms for mapping UE tasks to fixed edge servers using UAV. Lastly, the simulation results demonstrate that the proposed algorithms yield better results than other benchmark methods in terms of total UE energy consumption.
Topics & Concepts
Computer scienceMobile edge computingEnergy consumptionServerBenchmark (surveying)User equipmentEnhanced Data Rates for GSM EvolutionTask (project management)Scheduling (production processes)Real-time computingEdge computingDistributed computingComputer networkMathematical optimizationArtificial intelligenceEngineeringBase stationMathematicsElectrical engineeringGeodesyGeographySystems engineeringUAV Applications and OptimizationIoT and Edge/Fog ComputingAdvanced Neural Network Applications