Research On Resource Allocation Strategy Of Task Offloading In Maritime Edge Computing Networks

With the vigorous development of our country’s marine industry,unmanned surface vehicles are widely used in environmental monitoring,marine surveys,security and rescue in unknown and dangerous sea areas due to their light size and low investment cost.More and more resource-intensive tasks,such as surface rescue and salvage,are also appearing in the business needs of unmanned surface vehicles.These changes have increased the energy consumption of unmanned surface vehicles to complete tasks and put forward higher requirements for the unmanned surface vehicles’ own computing capabilities.Mobile Edge Computing(MEC)deploys service nodes at the edge of the network to provide users with computing and storage services,making it possible for users to reduce their own energy consumption while meeting delay constraints.When the unmanned surface vehicles’ operating area is far away from the base station vehicle,due to long-distance transmission,the channel conditions between some unmanned vehicles and the base station vehicle may be extremely poor,and communication cannot be performed to complete the offloading and transmission of computing tasks.The introduction of relay communication technology into the maritime edge computing network can effectively solve the channel fading problem in the wireless transmission process,and improve the quality of the wireless communication link between the unmanned surface vehicles and the base station vehicle,which is one of the effective methods to solve this problem.This paper focuses on the maritime edge computing network and studies the unmanned surface vehicles’ task offloading joint resource allocation strategy.The optimization goal is to minimize the energy consumption of the unmanned surface vehicles and extend the working duration of the unmanned surface vehicles.The main work of this thesis is as follows.For the multi-unmanned surface vehicles and single-relay vehicle computation offloading scenario under the Time Division Multiple Access(TDMA)working mode,the unmanned surface vehicles can choose to use direct link or relay link in the assigned time slot for offloading the task to the base station vehicle.Firstly,a detailed mathematical description of the communication and computation model in this scenario is provided in this thesis,then the optimization problem of joint unmanned surface vehicles’ communication mode,communication time slot and offloading data volume decision is constructed.Furthermore,by analyzing and transforming the proposed problem,the original problem is transformed into a convex optimization problem,and the Lagrange duality method is used to solve the optimization problem.The simulation analysis verifies that the proposed algorithm can effectively reduce the total energy consumption of the system under the premise of satisfying the delay constraint compared with benchmark algorithms such as time average distribution scheme.For the offloading scenario of multi-unmanned surface vehicles and multi-relay vehicles under Orthogonal Frequency Division Multiple Access(OFDMA)working mode,the system will allocate different sub-carriers for different unmanned surface vehicles to communicate with the base station ship through direct link or relay link.After constructing the communication model in this scenario,an optimization problem of joint relay selection and sub-carrier power allocation is described and an iterative algorithm based on the Lagrange dual decomposition method is proposed for solving this problem in this thesis.The simulation results show that,compared with other traditional subcarrier allocation schemes,the proposed algorithm can effectively reduce the energy consumption of the unmanned surface vehicles fleet during the offloading transmission process while meeting the requirements of different unmanned surface vehicles’ offloading data volume.