文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速...文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速文件共享并降低网络带宽消耗,文中提出了PLAR(Popularity and Locality-based Adaptive Replication)算法.PLAR采用了基于位置信息和流行度的复本管理算法,该算法还同时引入了混合式的服务器选择策略以及远程增强策略.PLAR算法在文中的Granary对等广域网存储系统中得到了实现.实验表明,通过PLAR算法下载速率平均能提高60%以上,有效提高了共享速度并减少带宽消耗.展开更多
Big data is an emerging term in the storage indus- try, and it is data analytics on big storage, i.e., Cloud-scale storage. In Cloud-scale （or EB-scale） file systems, load bal- ancing in request workloads across a m...Big data is an emerging term in the storage indus- try, and it is data analytics on big storage, i.e., Cloud-scale storage. In Cloud-scale （or EB-scale） file systems, load bal- ancing in request workloads across a metadata server cluster is critical for avoiding performance bottlenecks and improv- ing quality of services. Many good approaches have been pro- posed for load balancing in distributed file systems. Some of them pay attention to global namespace balancing, making metadata distribution across metadata servers as uniform as possible. However, they do not work well in skew request dis- tributions, which impair load balancing but simultaneously increase the effectiveness of caching and replication, in this paper, we propose Cloud Cache （C2）, an adaptive and scal- able load balancing scheme for metadata server cluster in EB-scale file systems. It combines adaptive cache diffusion and replication scheme to cope with the request load balanc- ing problem, and it can be integrated into existing distributed metadata management approaches to efficiently improve their load balancing performance. C2 runs as follows： 1） to run adaptive cache diffusion first, if a node is overloaded, load- shedding will be used; otherwise, load-stealing will be used; and 2） to run adaptive replication scheme second, if there is a very popular metadata item （or at least two items） causing a node be overloaded, adaptive replication scheme will be used,in which the very popular item is not split into several nodes using adaptive cache diffusion because of its knapsack prop- erty. By conducting performance evaluation in trace-driven simulations, experimental results demonstrate the efficiency and scalability of C2.展开更多
The bane of achieving a scalable distributed file sharing system is the centralized data system and single server oriented file [sharing] system. In this paper, the solution to the problems in a distributed environmen...The bane of achieving a scalable distributed file sharing system is the centralized data system and single server oriented file [sharing] system. In this paper, the solution to the problems in a distributed environment is presented. Thus, inability to upload sizeable files, slow transportation of files, weak security and lack of fault tolerance are the major problems in the existing system. Hence, the utmost need is to build a client-server network that runs on two or more server systems in order to implement scalability, such that when one server is down, the other(s) would still hold up the activities within the network. And to achieve this reliable network environment, LINUX network operating system is recommended among others as a preferred platform for the synchronization of the server systems, such that every user activity like sending of internal memos/mails, publication of academic articles, is replicated;thereby, achieving the proposed result. Hence, Scalable Distributed File Sharing System provides the robustness required to having a reliable intranet.展开更多
文摘文件共享服务是对等网络中的一个重要应用,数据传输速率逐渐取代响应延迟成为影响用户体验的首要因素.文中研究了对等网络中的副本管理算法,这对于提高对等网络应用的可靠性,降低带宽消耗具有重要的意义.为了在广域网络存储系统中加速文件共享并降低网络带宽消耗,文中提出了PLAR(Popularity and Locality-based Adaptive Replication)算法.PLAR采用了基于位置信息和流行度的复本管理算法,该算法还同时引入了混合式的服务器选择策略以及远程增强策略.PLAR算法在文中的Granary对等广域网存储系统中得到了实现.实验表明,通过PLAR算法下载速率平均能提高60%以上,有效提高了共享速度并减少带宽消耗.
文摘Big data is an emerging term in the storage indus- try, and it is data analytics on big storage, i.e., Cloud-scale storage. In Cloud-scale （or EB-scale） file systems, load bal- ancing in request workloads across a metadata server cluster is critical for avoiding performance bottlenecks and improv- ing quality of services. Many good approaches have been pro- posed for load balancing in distributed file systems. Some of them pay attention to global namespace balancing, making metadata distribution across metadata servers as uniform as possible. However, they do not work well in skew request dis- tributions, which impair load balancing but simultaneously increase the effectiveness of caching and replication, in this paper, we propose Cloud Cache （C2）, an adaptive and scal- able load balancing scheme for metadata server cluster in EB-scale file systems. It combines adaptive cache diffusion and replication scheme to cope with the request load balanc- ing problem, and it can be integrated into existing distributed metadata management approaches to efficiently improve their load balancing performance. C2 runs as follows： 1） to run adaptive cache diffusion first, if a node is overloaded, load- shedding will be used; otherwise, load-stealing will be used; and 2） to run adaptive replication scheme second, if there is a very popular metadata item （or at least two items） causing a node be overloaded, adaptive replication scheme will be used,in which the very popular item is not split into several nodes using adaptive cache diffusion because of its knapsack prop- erty. By conducting performance evaluation in trace-driven simulations, experimental results demonstrate the efficiency and scalability of C2.
文摘The bane of achieving a scalable distributed file sharing system is the centralized data system and single server oriented file [sharing] system. In this paper, the solution to the problems in a distributed environment is presented. Thus, inability to upload sizeable files, slow transportation of files, weak security and lack of fault tolerance are the major problems in the existing system. Hence, the utmost need is to build a client-server network that runs on two or more server systems in order to implement scalability, such that when one server is down, the other(s) would still hold up the activities within the network. And to achieve this reliable network environment, LINUX network operating system is recommended among others as a preferred platform for the synchronization of the server systems, such that every user activity like sending of internal memos/mails, publication of academic articles, is replicated;thereby, achieving the proposed result. Hence, Scalable Distributed File Sharing System provides the robustness required to having a reliable intranet.
