针对命名数据网络(Named Data Networks,NDN)中数据缓存的问题,提出了一种基于分布式部分可观测马尔科夫决策过程(Dec-POMDP)的缓存优化模型。在该模型框架下,NDN网络节点间以分布式协作的方式逐渐收敛至最优联合缓存策略,从而使NDN中...针对命名数据网络(Named Data Networks,NDN)中数据缓存的问题,提出了一种基于分布式部分可观测马尔科夫决策过程(Dec-POMDP)的缓存优化模型。在该模型框架下,NDN网络节点间以分布式协作的方式逐渐收敛至最优联合缓存策略,从而使NDN中的有限缓存资源得到充分利用。仿真实验表明,与现有NDN缓存方法相比,该方法能有效提升NDN网络的缓存效率,实现较高的缓存命中率及较小的请求平均跳数。展开更多
Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delay...Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.展开更多
文摘针对命名数据网络(Named Data Networks,NDN)中数据缓存的问题,提出了一种基于分布式部分可观测马尔科夫决策过程(Dec-POMDP)的缓存优化模型。在该模型框架下,NDN网络节点间以分布式协作的方式逐渐收敛至最优联合缓存策略,从而使NDN中的有限缓存资源得到充分利用。仿真实验表明,与现有NDN缓存方法相比,该方法能有效提升NDN网络的缓存效率,实现较高的缓存命中率及较小的请求平均跳数。
基金supported by the National Science Foundation for Young Scholars of China(6130123471401175)
文摘Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.
