本文针对流媒体Cloud-P2P存储模式中的副本选择,提出一种基于蚁群算法的改进算法(replica selectionalgorithm in Cloud-P2P based on ant colony algorithm, C2P2RSA2),建立副本选择度量标准(副本节点的网络带宽、网络延时等)与蚁群信...本文针对流媒体Cloud-P2P存储模式中的副本选择,提出一种基于蚁群算法的改进算法(replica selectionalgorithm in Cloud-P2P based on ant colony algorithm, C2P2RSA2),建立副本选择度量标准(副本节点的网络带宽、网络延时等)与蚁群信息素的映射,定义了副本信息素概率,最后得到一组副本资源的最优解.实验表明,与PARSA算法(Pheromone-base Ant colony Replica adaptive Selection Algorithm in cloud storage)和最佳副本选择算法比较,在平均访问时间增加2%–5%的情况下,本文的算法对云副本节点的负载率减少15%–25%.展开更多
The tail latency of end-user requests,which directly impacts the user experience and the revenue,is highly related to its corresponding numerous accesses in key-value stores.The replica selection algorithm is crucial ...The tail latency of end-user requests,which directly impacts the user experience and the revenue,is highly related to its corresponding numerous accesses in key-value stores.The replica selection algorithm is crucial to cut the tail latency of these key-value accesses.Recently,the C3 algorithm,which creatively piggybacks the queue-size of waiting keys from replica servers for the replica selection at clients,is proposed in NSDI 2015.Although C3 improves the tail latency a lot,it suffers from the timeliness issue on the feedback information,which directly influences the replica selection.In this paper,we analysis the evaluation of queuesize of waiting keys of C3,and some findings of queue-size variation were made.It motivate us to propose the Prediction-Based Replica Selection(PRS)algorithm,which predicts the queue-size at replica servers under the poor timeliness condition,instead of utilizing the exponentially weighted moving average of the state piggybacked queue-size as in C3.Consequently,PRS can obtain more accurate queue-size at clients than C3,and thus outperforms C3 in terms of cutting the tail latency.Simulation results confirm the advantage of PRS over C3.展开更多
文摘本文针对流媒体Cloud-P2P存储模式中的副本选择,提出一种基于蚁群算法的改进算法(replica selectionalgorithm in Cloud-P2P based on ant colony algorithm, C2P2RSA2),建立副本选择度量标准(副本节点的网络带宽、网络延时等)与蚁群信息素的映射,定义了副本信息素概率,最后得到一组副本资源的最优解.实验表明,与PARSA算法(Pheromone-base Ant colony Replica adaptive Selection Algorithm in cloud storage)和最佳副本选择算法比较,在平均访问时间增加2%–5%的情况下,本文的算法对云副本节点的负载率减少15%–25%.
文摘The tail latency of end-user requests,which directly impacts the user experience and the revenue,is highly related to its corresponding numerous accesses in key-value stores.The replica selection algorithm is crucial to cut the tail latency of these key-value accesses.Recently,the C3 algorithm,which creatively piggybacks the queue-size of waiting keys from replica servers for the replica selection at clients,is proposed in NSDI 2015.Although C3 improves the tail latency a lot,it suffers from the timeliness issue on the feedback information,which directly influences the replica selection.In this paper,we analysis the evaluation of queuesize of waiting keys of C3,and some findings of queue-size variation were made.It motivate us to propose the Prediction-Based Replica Selection(PRS)algorithm,which predicts the queue-size at replica servers under the poor timeliness condition,instead of utilizing the exponentially weighted moving average of the state piggybacked queue-size as in C3.Consequently,PRS can obtain more accurate queue-size at clients than C3,and thus outperforms C3 in terms of cutting the tail latency.Simulation results confirm the advantage of PRS over C3.
