MeURep: A novel user reputation calculation approach in personalized cloud services
MeURep: A novel user reputation calculation approach in personalized cloud services
复制标题
MeURep：个性化云服务中一种新颖的用户信誉计算方法
DOI：
10.1371/journal.pone.0217933
复制
发表时间：
2019-06
期刊：
影响因子：
3.7
通讯作者：
Yindong Chen
中科院分区：
文献类型：
--
作者：
Jianlong Xu;Xin Du;Weihong Cai;Changsheng Zhu;Yindong Chen
用户可靠性对于个性化云服务至关重要。在云计算环境中，为用户提供了大量的云服务。随着云服务数量的指数级增长，用户很难从等效或相似的候选服务中选择合适的服务。服务质量（QoS）已成为选择的重要标准，用户可以根据观察到的其他用户的QoS数据进行个性化选择，但很难保证用户的可靠性。实际上，不可靠的用户可能会提供不可靠的QoS数据，并对个性化云服务选择产生负面影响。因此，如何确定可靠的QoS数据，个性化的云服务选择仍然是一个重要的问题。为了衡量每个用户的可靠性，提出了一个基于用户信誉的云服务选择框架，并提出了一种新的用户信誉计算方法MeURep，包括L1-MeURep和L2-MeURep。实验结果表明，MeURep算法具有更高的效率.
User reliability is notably crucial for personalized cloud services. In cloud computing environments, large amounts of cloud services are provided for users. With the exponential increase in number of cloud services, it is difficult for users to select the appropriate services from equivalent or similar candidate services. The quality-of-service (QoS) has become an important criterion for selection, and the users can conduct personalized selection according to the observed QoS data of other users; however, it is difficult to ensure that the users are reliable. Actually, unreliable users may provide unreliable QoS data and have negative effects on the personalized cloud service selection. Therefore, how to determine reliable QoS data for personalized cloud service selection remains a significant problem. To measure the reliability for each user, we present a cloud service selection framework based on user reputation and propose a new user reputation calculation approach, which is named MeURep and includes L1-MeURep and L2-MeURep. Experiments are conducted, and the results confirm that MeURep has higher efficiency than previously proposed approaches.
登录
查看更多内容
一种使用贝叶斯网络模型的云服务 QoS 预测新方法
影响因子：
3.9
作者：
Li Wenrui;Zhang Pengcheng;Leung Hareton;Ji Shunhui
通讯作者：
Ji Shunhui
DOI：
10.1109/aina.2017.173
发表时间：
2017-03
期刊：
2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA)
影响因子：
--
作者：
A. Alkalbani;Lekhaben Gadhvi;B. Patel;F. Hussain;Ahmed Mohamed Ghamry;O. Hussain
通讯作者：
A. Alkalbani;Lekhaben Gadhvi;B. Patel;F. Hussain;Ahmed Mohamed Ghamry;O. Hussain
影响因子：
2.7
作者：
Li, Baichuan;Li, Rong-Hua;Yu, Jeffrey Xu
通讯作者：
Yu, Jeffrey Xu
云服务的QoS排名预测
DOI：
10.1109/tpds.2012.285
发表时间：
2013-06-01
影响因子：
5.3
作者：
Zheng, Zibin;Wu, Xinmiao;Wang, Jianmin
通讯作者：
Wang, Jianmin
影响因子：
3.9
作者：
Mubeen, Saad;Asadollah, Sara Abbaspour;Behnam, Moris
通讯作者：
Behnam, Moris