Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reli...Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.展开更多
Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission ...Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.展开更多
Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translat...Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translation validators attempt to verify that program transformations preserve semantics. In this work, we adopt this approach to formally verify that the clock semantics and data dependence are preserved during the compilation of the Signal compiler. Translation valida- tion is implemented for every compilation phase from the initial phase until the latest phase where the executable code is generated, by proving the transformation in each phase of the compiler preserves the semantics. We represent the clock semantics, the data dependence of a program and its trans- formed counterpart as first-order formulas which are called clock models and synchronous dependence graphs （SDGs）, respectively. We then introduce clock refinement and depen- dence refinement relations which express the preservations of clock semantics and dependence, as a relation on clock mod- els and SDGs, respectively. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.展开更多
基金supported by Science and Technology Project of China Southern Power Grid Company Limited under Grant Number 036000KK52200058(GDKJXM20202001).
文摘Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.
基金supported by the Science and Technology Project of the State Grid Corporation of China under Grant Number 5400202199541A-0-5-ZN。
文摘Power Line Communications-Artificial Intelligence of Things(PLC-AIo T)combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence(AI)to provide data collection and transmission capabilities for PLC-AIo T devices in smart parks.With the development of smart parks,their emerging services require secure and accurate time synchronization of PLC-AIo T devices.However,the impact of attackers on the accuracy of time synchronization cannot be ignored.To solve the aforementioned problems,we propose a tampering attack-aware Deep Q-Network(DQN)-based time synchronization algorithm.First,we construct an abnormal clock source detection model.Then,the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway.Finally,the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIo T in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights.Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.
文摘Translation validation was invented in the 90＇s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translation validators attempt to verify that program transformations preserve semantics. In this work, we adopt this approach to formally verify that the clock semantics and data dependence are preserved during the compilation of the Signal compiler. Translation valida- tion is implemented for every compilation phase from the initial phase until the latest phase where the executable code is generated, by proving the transformation in each phase of the compiler preserves the semantics. We represent the clock semantics, the data dependence of a program and its trans- formed counterpart as first-order formulas which are called clock models and synchronous dependence graphs （SDGs）, respectively. We then introduce clock refinement and depen- dence refinement relations which express the preservations of clock semantics and dependence, as a relation on clock mod- els and SDGs, respectively. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.
