Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experimen...Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.展开更多
随着5G的广泛应用,边缘计算技术被用于任务卸载和处理,基于博弈论的边缘计算策略成为当前研究领域中的热点.本文以最大化用户体验质量(Quality of Experience,QoE)为目标,研究时间约束条件下的多用户任务卸载问题.本文首先从通信模型、...随着5G的广泛应用,边缘计算技术被用于任务卸载和处理,基于博弈论的边缘计算策略成为当前研究领域中的热点.本文以最大化用户体验质量(Quality of Experience,QoE)为目标,研究时间约束条件下的多用户任务卸载问题.本文首先从通信模型、计算模型和时间约束三个方面建立系统模型,然后将优化问题转换为博弈问题,给出并证明存在纳什均衡解.本文提出了一种分布式多用户卸载算法(Distributed Multi-User Offloading,DMUO),首次实现了多用户在单时隙内同步更新策略,显著降低了计算开销并提升了收敛速度.理论分析表明,DMUO算法能够收敛至纳什均衡解,并给出了迭代次数的上限.此外,通过分析最坏情况策略与最优解的性能差距,验证了算法的鲁棒性.仿真实验表明,DMUO算法具有优异的收敛性和系统性能,证明了其在大规模边缘计算环境中的可扩展性和实际适用性.展开更多
文摘Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.
文摘随着5G的广泛应用,边缘计算技术被用于任务卸载和处理,基于博弈论的边缘计算策略成为当前研究领域中的热点.本文以最大化用户体验质量(Quality of Experience,QoE)为目标,研究时间约束条件下的多用户任务卸载问题.本文首先从通信模型、计算模型和时间约束三个方面建立系统模型,然后将优化问题转换为博弈问题,给出并证明存在纳什均衡解.本文提出了一种分布式多用户卸载算法(Distributed Multi-User Offloading,DMUO),首次实现了多用户在单时隙内同步更新策略,显著降低了计算开销并提升了收敛速度.理论分析表明,DMUO算法能够收敛至纳什均衡解,并给出了迭代次数的上限.此外,通过分析最坏情况策略与最优解的性能差距,验证了算法的鲁棒性.仿真实验表明,DMUO算法具有优异的收敛性和系统性能,证明了其在大规模边缘计算环境中的可扩展性和实际适用性.
