检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]国防科学技术大学计算机学院并行与分布处理国家重点实验室,湖南长沙410073
出 处:《软件学报》2009年第6期1574-1590,共17页Journal of Software
基 金:国家自然科学基金Nos.60621003;60873215;国家重点基础研究发展计划(973)No.2005CB321801;高等学校全国优秀博士学位论文作者专项No.200141~~
摘 要:P2P网络中节点间的距离信息是实现拓扑感知以优化覆盖网应用以及解决网络监管等问题的基础.P2P网络的大规模、自组织、高度动态等复杂特征使得要准确、完全地测量节点间的距离信息面临着极大的困难.因此,研究者们提出各种预测技术,目前对网络距离预测技术的研究已成为P2P领域的研究热点.首先,提出了一个网络距离预测技术的研究框架,指出了研究的重点以及相关技术问题,分析了研究历史;其次,对各种预测方法加以分类,在分类的基础上,介绍了各种典型的预测方法并进行了对比分析;最后总结了各种精确性度量标准,并指出了未来的研究趋势.The distance information between nodes in P2P network is the basis for achieving topology-awareness which aims at optimizing the applications of overlay and solving the problems such as network monitoring. However, it seems infeasible to accurately and completely measure the distances between nodes due to the characteristics of P2P, such as being large-scale, self-organized, highly dynamic and so on. Consequently, researchers have put forward various prediction methods, and currently the network distance prediction technology is emerging as a new hotspot of research in P2P area. Firstly, a research framework is proposed, based on which the main aspects and the related technical issues of the research are analyzed. Meanwhile, the research history and the analysis of the classification are investigated. Many typical methods are introduced and compared. Lastly, the metrics of precision, as well as future research trends of network distance prediction is reviewed.
关 键 词:网络距离 网络坐标 距离预测 延迟预测 坐标计算 拓扑感知 覆盖网
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.222