We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satis...Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.展开更多
混洗差分隐私(SDP)模型能兼顾用户端的隐私保护程度和服务器端发布结果的可用性,更适用于隐私保护的大数据收集和统计发布场景。针对目前SDP频率估计方法的洗牌效率较低和混洗过程安全性不足等问题,进行以下工作:首先,设计基于优化椭圆...混洗差分隐私(SDP)模型能兼顾用户端的隐私保护程度和服务器端发布结果的可用性,更适用于隐私保护的大数据收集和统计发布场景。针对目前SDP频率估计方法的洗牌效率较低和混洗过程安全性不足等问题,进行以下工作:首先,设计基于优化椭圆曲线的混洗差分隐私盲签名算法(SDPBSA),以实现对篡改或伪造信息的鉴别,提高混洗过程的安全性;其次,提出矩阵列重排转置(MCRT)洗牌方法,以利用随机的矩阵列重排和矩阵转置操作实现数据混洗,提高混洗过程的效率;最后,结合上述方法构建完整的SDP频率估计隐私保护框架——SM-SDP(SDP based on blind Signature and Matrix column rearrangement transposition),并通过理论分析讨论它的隐私性和误差级别。在Normal、Zipf和IPUMS(Integrated Public Use Microdata Series)等数据集上的实验结果表明,相较于Fisher-Yates、ORShuffle(Oblivious Recursive Shuffling)和MRS(Message Random Shuffling)等洗牌方法,MCRT洗牌方法的洗牌效率提升了1~2个数量级;相较于mixDUMP、PSDP(Personalized Differential Privacy in Shuffle model)和HP-SDP(Histogram Publication with SDP)等频率估计方法,SM-SDP框架在不同比例恶意数据存在时的均方误差(MSE)降低了2~11个数量级。展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金supported by the National Natural Science Foundation of China(71671035)。
文摘Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.
文摘混洗差分隐私(SDP)模型能兼顾用户端的隐私保护程度和服务器端发布结果的可用性,更适用于隐私保护的大数据收集和统计发布场景。针对目前SDP频率估计方法的洗牌效率较低和混洗过程安全性不足等问题,进行以下工作:首先,设计基于优化椭圆曲线的混洗差分隐私盲签名算法(SDPBSA),以实现对篡改或伪造信息的鉴别,提高混洗过程的安全性;其次,提出矩阵列重排转置(MCRT)洗牌方法,以利用随机的矩阵列重排和矩阵转置操作实现数据混洗,提高混洗过程的效率;最后,结合上述方法构建完整的SDP频率估计隐私保护框架——SM-SDP(SDP based on blind Signature and Matrix column rearrangement transposition),并通过理论分析讨论它的隐私性和误差级别。在Normal、Zipf和IPUMS(Integrated Public Use Microdata Series)等数据集上的实验结果表明,相较于Fisher-Yates、ORShuffle(Oblivious Recursive Shuffling)和MRS(Message Random Shuffling)等洗牌方法,MCRT洗牌方法的洗牌效率提升了1~2个数量级;相较于mixDUMP、PSDP(Personalized Differential Privacy in Shuffle model)和HP-SDP(Histogram Publication with SDP)等频率估计方法,SM-SDP框架在不同比例恶意数据存在时的均方误差(MSE)降低了2~11个数量级。
