The contract net protocol has developed to specify problem solving communication for nodes in a distributed problem solving. Task distribution is affected by a negotiation process,a discussion carried on between node...The contract net protocol has developed to specify problem solving communication for nodes in a distributed problem solving. Task distribution is affected by a negotiation process,a discussion carried on between nodes with tasks to he executed and nodes that may be able to execute those tasks. In contract net protocol,once negotiation successes,tbe task execution is assumed to success. However,in real world,even though a task is awarded to successfully bidding nodes,it may be delayed. Such delay may badly propagate in whole system. Here,we introduce real-time constraints into contract net protocol to manage task execution for avoiding the, task's delay,or even though being delayed,the railure cannot propagate to whole system. In this paper,we first present a real-time contract net protocol which is an extension of contract net protocol with real-time constraints for distributed computing. Our proposition extends the basic negotiation protocol to negotiation and controlling execution or task. The controlling process is based on task deadline time,we also present an extension of the internode language of contract net protocol specification with real-time constraints.展开更多
The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,te...The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,temporary failures and failures of some TT&C resources,and so on.To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances,a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources.Firstly,the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed,and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance.Then,a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed,which includes a task layer,a resource layer,a central internal collaboration layer,and a central external collaboration layer.Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner,using efficient heuristic strategies in the task layer and the resource layer,respectively.We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer,the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements.Finally,a large number of simulation experiments were carried out and compared with various comparative algorithms.The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems,and has good application prospects.展开更多
Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed o...Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be executed.To improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this paper.In the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model.And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution.As in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario.And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention.Three cases of different scales demonstrate that the two modules cooperate well with each other.On the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced.On the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond.The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.展开更多
A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV s...A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.展开更多
文摘The contract net protocol has developed to specify problem solving communication for nodes in a distributed problem solving. Task distribution is affected by a negotiation process,a discussion carried on between nodes with tasks to he executed and nodes that may be able to execute those tasks. In contract net protocol,once negotiation successes,tbe task execution is assumed to success. However,in real world,even though a task is awarded to successfully bidding nodes,it may be delayed. Such delay may badly propagate in whole system. Here,we introduce real-time constraints into contract net protocol to manage task execution for avoiding the, task's delay,or even though being delayed,the railure cannot propagate to whole system. In this paper,we first present a real-time contract net protocol which is an extension of contract net protocol with real-time constraints for distributed computing. Our proposition extends the basic negotiation protocol to negotiation and controlling execution or task. The controlling process is based on task deadline time,we also present an extension of the internode language of contract net protocol specification with real-time constraints.
基金This work was supported in part by the National Natural Science Foundation of China(No.62373380).
文摘The practical engineering of satellite tracking telemetry and command(TT&C)is often disturbed by unpredictable external factors,including the temporary rise in a significant quantity of satellite TT&C tasks,temporary failures and failures of some TT&C resources,and so on.To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances,a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources.Firstly,the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed,and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance.Then,a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed,which includes a task layer,a resource layer,a central internal collaboration layer,and a central external collaboration layer.Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner,using efficient heuristic strategies in the task layer and the resource layer,respectively.We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer,the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements.Finally,a large number of simulation experiments were carried out and compared with various comparative algorithms.The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems,and has good application prospects.
基金supported by the National Key Research and Development Plan(Grant No.2021YFB3302501)the National Natural Science Foundation of China(Grant Nos.12102077,12161076,U2241263).
文摘Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be executed.To improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this paper.In the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model.And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution.As in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario.And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention.Three cases of different scales demonstrate that the two modules cooperate well with each other.On the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced.On the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond.The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.
基金National Natural Science Foundation of China (12202293)Sichuan Science and Technology Program (2023NSFSC0393,2022NSFSC1952)。
文摘A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.
