A Trusted Edge Resource Allocation Framework for Internet of Vehicles

With the continuous progress of information technique,assisted driving technology has become an effective technique to avoid traffic accidents.Due to the complex road conditions and the threat of vehicle information being attacked and tampered with,it is difficult to ensure information security.This paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time,calculate the appropriate speed,and plan a reasonable driving route for the driver.To solve these problems,this paper proposes a trusted edge resource allocation framework for assisted driving service,which includes two stages:the blockchain generation stage(the first stage)and assisted driving service stage(the second stage).Furthermore,in the first stage,a delay-and-throughput-oriented block generation model for the mobile terminal is designed.In the second stage,a balanced offloading algorithm for assisted driving service based on edge collaboration is proposed to solve the problems of unbalanced load of cluster mobile edge computing(MEC)servers and low resource utilization of the system.And this paper optimizes the throughput of blockchain and delay of the transportation network through deep reinforcement learning(DRL)algorithm.Finally,compared with joint computation and communication resources’allocation(JCCR)and resource allocation method based on binary offloading(RAB),our proposed scheme can optimize the delay by 7.4%and 26.7%,and support various application services of the vehicular networks more effectively.

Optical detection method of discharge mode transition of inductively coupled plasma in an atmosphere-breathing electric propulsion system

Plasma discharge stability is an important problem in atmosphere-breathing electric propulsion system when maintaining long-term missions at ultra-low earth orbit.This paper designed an inductively coupled plasma source to imitate the ionization section.The effect of inflow rate and Radio Frequency(RF)power on the plasma discharge mode transition is experimentally studied.A discharge mode detection method is proposed,which determines the discharge mode by identifying the morphology of the plasma core.By using the method,the discharge mode transition is quantified and a control model based on the parameter sensitivity is constructed.To verify the method,the spectra are measured and the electron temperature spatial distribution is calculated.And the method has been proven effective.The results show that the inductively coupled discharge contains capacitive components affected by the mass flow rate and the radio frequency power.The plasma characteristics can be maintained stably by controlling the radio frequency power when the mass flow rate randomly changes in a certain range.It is demonstrated that the application of detection method effectively identifies the discharge mode,which is a promising active control method for the plasma discharge mode.