基于web的云社区的云服务动态排名:基于评级的云服务发现和多级排名的高效算法

A. Quadir, V. Vijayakumar
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引用次数: 10

摘要

云中的信任评估取决于QoS属性。在评估CSP的可信度时,传统的信任评估方法没有考虑不断动态变化的QoS属性。为了解决确定web中CSP的可信度问题,提出了保持周期性变化的QoS属性的基于评级的动态发现(RBDD)和以有效方式对发现的CSP进行排名的多层排名(MLR)算法。这种方法使我们能够从云审计员的感知中评估CSP的可信度。评估结果表明,RBDD能够感知CSP的行为变化,并发现动态可信服务提供商,与其他方法相比,MLR算法基于CC需求对其进行排名,具有高精度和最小的时间复杂性。由于缺乏标准化,所提出的系统已经用合成数据集进行了验证。
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Dynamic ranking of cloud services for web based cloud communities: Efficient algorithm for rating based discovery and multi-level ranking of cloud services
Trust assessment in cloud depends on QoS attributes. While evaluating the trustworthiness of the CSPs, traditional methods of trust assessment do not take into account QoS attributes that keep changing dynamically. To address the issue of determining the trustworthiness of CSPs in web, rating based dynamic discovery (RBDD) of QoS attributes that keeps changing periodically and multi-layer ranking (MLR) algorithm that ranks the discovered CSPs in an efficient manner have been proposed. This approach allows us to evaluate CSPs trustworthiness from cloud auditors perception. evaluation results indicates that the RBDD is capable of sensing behavioural changes in CSPs and discovers the dynamic trustworthy service providers and MLR algorithm ranks them based on CC requirements with high accuracy and minimal time complexity compared to other approaches. The proposed system has been validated with synthetic dataset owing to absence of standardisation.
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来源期刊
International Journal of Web Based Communities
International Journal of Web Based Communities Social Sciences-Communication
CiteScore
2.00
自引率
0.00%
发文量
30
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