Maintaining temporal consistency of real-time data is important for cyber-physical systems.Most of the previous studies focus on uniprocessor systems.In this paper,the problem of temporal consistency maintenance on mu...Maintaining temporal consistency of real-time data is important for cyber-physical systems.Most of the previous studies focus on uniprocessor systems.In this paper,the problem of temporal consistency maintenance on multiprocessor platforms with instance skipping was formulated based on the(m,k)-constrained model.A partitioned scheduling method SC-AD was proposed to solve the problem.SC-AD uses a derived sufficient schedulability condition to calculate the initial value of m for each sensor transaction.It then partitions the transactions among the processors in a balanced way.To further reduce the average relative invalid time of real-time data,SC-AD judiciously increases the values of m for transactions assigned to each processor.Experiment results show that SC-AD outperforms the baseline methods in terms of the average relative invalid time and the average valid ratio under different system workloads.展开更多
Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lif...Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.展开更多
基金Project(2020JJ4032)supported by the Hunan Provincial Natural Science Foundation of China。
文摘Maintaining temporal consistency of real-time data is important for cyber-physical systems.Most of the previous studies focus on uniprocessor systems.In this paper,the problem of temporal consistency maintenance on multiprocessor platforms with instance skipping was formulated based on the(m,k)-constrained model.A partitioned scheduling method SC-AD was proposed to solve the problem.SC-AD uses a derived sufficient schedulability condition to calculate the initial value of m for each sensor transaction.It then partitions the transactions among the processors in a balanced way.To further reduce the average relative invalid time of real-time data,SC-AD judiciously increases the values of m for transactions assigned to each processor.Experiment results show that SC-AD outperforms the baseline methods in terms of the average relative invalid time and the average valid ratio under different system workloads.
基金Supported by the National Natural Science Foundation of China(No.90820302,60805027)the Research Fund for Doctoral Program of Higher Education(No.200805330005)the Academician Foundation of Hunan(No.2009FJ4030)
文摘Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.
