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2015 IEEE 12th International Conference on e-Business Engineering最新文献

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A Queuing-Network-Based Approach to Performance Evaluation of Service Compositions 基于排队网络的服务组合性能评价方法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.31
Gang Zhou, Yunni Xia, K. Yu, Qiang Chen, Ping Gu
Performance prediction is one of the most important research topics of service-oriented systems. To investigate the performance of composite services in queuing condition, this paper introduces a queuing-network-based model. Analytical methods are introduced to evaluate the queue-length, wait-time and completion-duration. The case study (especially the case of airline ticket booking application) shows that the proposed model captures real-world composite services effectively. Through Monte-carlo simulations in the case study, we show analytical models are verified by simulative results.
性能预测是面向服务系统的重要研究课题之一。为了研究组合服务在排队条件下的性能,本文引入了一个基于排队网络的模型。引入了求解排队长度、等待时间和完成时间的解析方法。案例研究(特别是机票预订应用程序的案例)表明,所提出的模型有效地捕获了真实世界的组合服务。通过实例研究中的蒙特卡罗模拟,表明分析模型得到了仿真结果的验证。
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引用次数: 0
A Framework for Workload-Aware Views Materialisation of Semantic Databases 语义数据库工作负载感知视图实体化框架
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.13
Tomasz Zlamaniec, K. Chao, Nick Godwin, N. Shah, Raymond Farmer
Views materialisation is well known in the context of relational databases. However, unlike relational databases, the semantic graph model lacks restrictive structure. Instead, the semantic data rely on an evolving schema. This resulted in a challenge for views materialisation while allowing for open repositories of data to emerge. Open repositories combine knowledge from many different areas. Therefore, it can be assumed that various data structures within a repository may exhibit different daily access patterns, i.e. That the user interests change during the day. This research verifies this assumption and proposes a new views selection model. By analysing how access patterns of individual views contribute to the overall system workload, the proposed model aims at selection of candidates offering the highest reduction of the peak workload. The proposed selection method has been integrated as a part of a new optimisation framework, which operates as a proxy for a SPARQL-enabled database. The approach has a potential to accelerate the adaptation of views materialisation for SPARQL. The proposed approach is evaluated both experimentally and using qualitative analysis.
视图实体化在关系数据库环境中是众所周知的。然而,与关系数据库不同,语义图模型缺乏约束结构。相反,语义数据依赖于不断发展的模式。这给视图实体化带来了挑战,同时又允许出现开放的数据存储库。开放存储库结合了来自许多不同领域的知识。因此,可以假设存储库中的各种数据结构可能表现出不同的日常访问模式,即用户兴趣在一天中发生变化。本研究验证了这一假设,并提出了一种新的视图选择模型。通过分析单个视图的访问模式如何对整个系统工作负载产生影响,该模型旨在选择能够最大限度地减少峰值工作负载的候选视图。建议的选择方法已经集成为新的优化框架的一部分,该框架作为启用sparql的数据库的代理进行操作。这种方法有可能加速对SPARQL视图实体化的适应。通过实验和定性分析对该方法进行了评价。
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引用次数: 1
Attribute-Based Encryption Goes X.509 基于属性的加密采用X.509
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.73
Florian Reimair, Johannes Feichtner, Peter Teufl
Key authentication as well as an intended recipient not having a key available are, among others, challenges that public key infrastructures (PKIs) still face. Trusted third parties work around these issues. However, identity-based encryption (IBE) systems and later attribute-based encryption (ABE) systems were designed to address these exact challenges. Unfortunately, such schemes became only practicable after public key infrastructures have been picked up by industry. In this work, we present our approach on standing the above mentioned challenges. We propose to utilize recent developments on centralized key storage solutions to bring the features of IBE/ABE systems to PKI-based IT infrastructures. We describe our IBE/ABE emulation approach, present our prototype and give a thorough security evaluation. We found that it is possible to emulate IBE/ABE schemes without compromising security.
密钥身份验证以及没有可用密钥的预期接收者是公钥基础设施(pki)仍然面临的挑战之一。可信的第三方可以解决这些问题。然而,基于身份的加密(IBE)系统和后来的基于属性的加密(ABE)系统的设计正是为了解决这些挑战。不幸的是,这些计划只有在公开密码匙基础设施被工业界采用后才可行。在这项工作中,我们提出了应对上述挑战的方法。我们建议利用集中密钥存储解决方案的最新发展,将IBE/ABE系统的特性引入基于pki的IT基础设施。我们描述了我们的IBE/ABE仿真方法,展示了我们的原型,并给出了彻底的安全评估。我们发现可以在不影响安全性的情况下模拟IBE/ABE方案。
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引用次数: 7
A Recommendation System for Travel Services Based on Cyber-Anima 基于网络动物的旅游服务推荐系统
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.28
Mi Zhang, Yinsheng Li, Aiqin Zhou, Zhou Fang
In recent years, recommendation systems have developed greatly, and is so widely used in online systems such as book, movie or friend recommendation. Current recommendation systems have problems with cold start and new entry. Cyber-Anima is a cyber-image of a user's anima, and we can derive one's cyber-anima by its user input and other observations of the user. With Cyber-Anima, we can build a recommendation system. The system take the concepts in cyber-anima into consideration and build relations between these concepts and user behavior to make further recommendations. We do some experiment with the dataset from travelhub.cn, which is a platform for travel services and is sponsored by the national technology plan. From the experiment, our implementation is better than FISM and Item-based collaborative and the time cost is reasonable.
近年来,推荐系统得到了很大的发展,广泛应用于书籍、电影或朋友推荐等在线系统中。当前的推荐系统存在冷启动和新条目的问题。Cyber-Anima是用户anima的网络图像,我们可以通过用户输入和用户的其他观察得出一个人的Cyber-Anima。有了Cyber-Anima,我们可以建立一个推荐系统。该系统考虑了网络动画中的概念,并建立了这些概念与用户行为之间的关系,从而提出进一步的建议。我们用travelhub.cn的数据集做了一些实验。travelhub.cn是一个由国家科技计划资助的旅游服务平台。实验结果表明,我们的实现优于FISM和基于item的协同,且时间成本合理。
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引用次数: 2
Common Features Based Volunteer and Voluntary Activity Recommendation Algorithm 基于共性特征的志愿者及志愿者活动推荐算法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.17
Feng Tian, Yan Chen, Xiaoqian Wang, Tian Lan, Q. Zheng, K. Chao
In general, the dataset of volunteer recommendation systems shows the sparsity, while a volunteer recommendation system required performing the function of recommending voluntary activities interesting to a specific volunteer. To our knowledge, there exists no such kind of recommendation systems. To begin with, this paper firstly presents an analysis of a dataset collected from a real volunteering application website and discovered two features: the locations between the volunteers and the voluntary activities are in close proximity, and the resulting graph which describes the participation relationship between volunteers and voluntary activities is a kind of bipartite, showing many small communities inside it. We call the first discovery 'geographically closely participating', and the second discovery 'participating together'. Based on these findings, a rating matrix, featuring a matching method for the recommendation algorithm has been constructed. Secondly, we propose a weighted Personal Rank algorithm to implement the required functions of a volunteer recommendation system by employing the registration information of volunteers and voluntary activities. This includes the volunteers' preferences, activities and location etc. The comparison of proposed method with the rating matrix-based collaborative filter algorithm and the Personal Rank algorithms shows that our proposed method outperforms them.
一般来说,志愿者推荐系统的数据集显示出稀疏性,而志愿者推荐系统需要执行推荐特定志愿者感兴趣的志愿活动的功能。据我们所知,目前还不存在这样的推荐系统。首先,本文对一个真实的志愿服务应用网站的数据集进行了分析,发现了两个特征:志愿者与志愿活动之间的位置非常接近,并且生成的描述志愿者与志愿活动之间参与关系的图是一种二部图,其中显示了许多小社区。我们称第一次发现为“地理上紧密参与”,第二次发现为“共同参与”。基于这些发现,我们构建了一个评级矩阵,其中包含了推荐算法的匹配方法。其次,我们提出了一种加权个人排名算法,利用志愿者的注册信息和志愿活动来实现志愿者推荐系统所需的功能。这包括志愿者的喜好、活动和地点等。将该方法与基于评级矩阵的协同过滤算法和个人排名算法进行了比较,结果表明该方法具有较好的性能。
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引用次数: 5
Relaxation Based SaaS for Repairing Failed Queries over the Cloud Computing 基于松弛的SaaS在云计算上修复失败查询
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.49
Abderrahim Ait Wakrime, S. Benbernou, Saïd Jabbour
Cloud Computing based Software as a Service (SaaS) combines multiple Web Services to satisfy a SaaS request, therefore SaaS should be able to dynamically seek replacements for faulty or underperforming services, thus performing self-healing. However, it may be the case of available services that do not match all user's request, leading the system to grind to a halt. It is better to have an alternative candidate in the cloud while not fullfilling all the constraints. In this paper, we provide a Relaxation SaaS solution to repair the failed user's query by rewriting it with an approximation. It is based on an incremental approach that exploits Quantified Satisfiability (QSAT) problem to repair the query and provide an alternative SaaS that leads to a successful request closed to the original one with maximized Quality of Service (QoS).
基于云计算的软件即服务(SaaS)结合了多个Web服务来满足SaaS请求,因此SaaS应该能够动态地寻找故障或性能不佳的服务的替代品,从而执行自我修复。但是,可能出现可用服务与所有用户的请求不匹配的情况,从而导致系统陷入停顿。最好在云中有一个备选方案,同时不满足所有约束。在本文中,我们提供了一个松弛的SaaS解决方案,通过近似重写来修复失败的用户查询。它基于一种增量方法,该方法利用Quantified Satisfiability (QSAT)问题来修复查询,并提供一种可替代的SaaS,该SaaS导致一个成功的请求接近原始请求,并具有最大的服务质量(QoS)。
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引用次数: 9
A Heuristic Resource Scheduling Algorithm of Cloud Computing Based on Polygons Correlation Calculation 基于多边形关联计算的云计算启发式资源调度算法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.68
Jingnan Tang, Liang Luo, Kai-Ming Wei, Xun Guo, Xiao-yu Ji
Cloud computing provides utility-oriented IT services for users worldwide, and it enables offering various kinds of applications to consumer in scientific or business field based on a pay-as-you-go model. Although cloud computing is still in its infancy, the scale of cloud infrastructure is expanding fast, which result in huge energy consumption and operating costs. Due to the complex architecture of cloud infrastructure, it is hard to evaluate and optimize energy consumption of cloud infrastructure in a non-intrusive manner under varying application, user configurations and requirements. In this paper, we present Bin-Balancing Algorithm (BBA), an innovative resource scheduling algorithm for private clouds that integrating the advantages of both bin packing solutions and polygons correlation calculations. BBA is designed to optimize energy consumption, while considering the task deadline, host PE (processing element), memory and bandwidth. Polygons correlation calculation integrated in BBA is used to meet the elastic characteristics of cloud computing services. BBA is validated and well compared with existing resource scheduling algorithms in Cloud Sim toolkit. The results demonstrate that BBA can save energy in cloud infrastructure while balancing the loss of performance and SLA of cloud users.
云计算为全世界的用户提供面向实用的IT服务,并基于现收现付模式向科学或商业领域的消费者提供各种应用程序。虽然云计算仍处于起步阶段,但云基础设施的规模正在迅速扩大,这导致了巨大的能源消耗和运营成本。由于云基础设施的架构复杂,在不同的应用、用户配置和需求下,很难以非侵入式的方式评估和优化云基础设施的能耗。在本文中,我们提出了bin - balancing Algorithm (BBA),这是一种创新的私有云资源调度算法,它综合了bin packing解决方案和多边形相关计算的优点。BBA的设计是为了优化能耗,同时考虑任务截止日期、主机PE(处理元素)、内存和带宽。采用集成在BBA中的多边形关联计算,满足云计算服务的弹性特点。在Cloud Sim工具包中对BBA进行了验证,并与现有的资源调度算法进行了比较。结果表明,BBA可以在平衡云用户的性能和SLA损失的同时节省云基础设施的能源。
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引用次数: 4
Integration of Sensors to Improve Customer Experience: Implementing Device Integration for the Retail Sector 集成传感器以改善客户体验:实现零售部门的设备集成
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.71
Mark Anderson, Joseph Bolton
Within the retail sector, a broad range of sensing devices are used to capture data to be interpreted into retail intelligence. The sensors many capture simplified data sets, such as the number of customers who have walked through a doorway or down an aisle, to more complex data, such as demographic or behavioural data. For a retailer this provides an opportunity of analyzing a rich source of information to optimize the customer experience and thereby improve sales. However, the sensors that are deployed are typically manufactured by different vendors, and may be installed over an extended period of time. This leads to difficulties when integrating and triangulating the data in an automated system as each retailer may have a bespoke collection of capture devices. This paper reports upon a project to overcome these challenges through the adoption of approaches taken in Field Device Integration (FDI), commonly used to integrate sensors and actuators in a manufacturing environment. The paper proposes an architectural model based on investigative work, and also discusses a related issue that has arisen in the implementation of the framework, that of multitenancy.
在零售领域,广泛的传感设备用于捕获数据,并将其解释为零售智能。这些传感器可以捕捉简单的数据集,比如走过门口或走过过道的顾客数量,也可以捕捉更复杂的数据,比如人口统计或行为数据。对于零售商来说,这提供了一个分析丰富信息源的机会,以优化客户体验,从而提高销售额。然而,所部署的传感器通常是由不同的供应商制造的,并且可能需要安装很长一段时间。这导致在自动化系统中集成和三角测量数据时遇到困难,因为每个零售商可能都有定制的捕获设备集合。本文报告了一个通过采用现场设备集成(FDI)方法来克服这些挑战的项目,该方法通常用于集成制造环境中的传感器和执行器。本文提出了一个基于调查工作的架构模型,并讨论了在实施该框架时出现的一个相关问题,即多租户问题。
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引用次数: 14
Learning Factor Selection for Boosted Matrix Factorisation in Recommender Systems 推荐系统中增强矩阵分解的学习因子选择
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.18
N. Chowdhury, Xiongcai Cai, Cheng Luo
Matrix factorisation (MF), an effective recommendation algorithm, predicts user preferences on items based on the historical preferences of other like-minded users. Classical MF methods do not explicitly distinguish the significances across the underlying factors that determine a users' preference on an item. The identical contribution of latent factors during learning results unnecessary updates on unimportant variables that leads to slower and suboptimal convergence. In this paper, we propose a new matrix factorisation method that not only seeks the intrinsic and outstanding factors that determine the users' preferences but also systematically reinforces the contribution generated by these factors. Based on boosting, a factor selection mechanism is developed to account the variable importance of latent factors to generate an ensemble recommender on the selected subspace of the latent factors by the principle of model uncertainty reduction. The proposed method is evaluated against a variety of the state-of-the-art methods of recommender systems on three publicly available benchmark datasets. The results confirm the effectiveness and efficiency of the proposed method.
矩阵分解(MF)是一种有效的推荐算法,它根据其他志同道合的用户的历史偏好来预测用户对物品的偏好。经典MF方法没有明确区分决定用户对某一物品偏好的潜在因素的重要性。在学习过程中,潜在因素的相同贡献导致对不重要变量的不必要更新,从而导致较慢和次优收敛。在本文中,我们提出了一种新的矩阵分解方法,它不仅寻求决定用户偏好的内在和突出因素,而且系统地强化了这些因素产生的贡献。在助推的基础上,建立了考虑潜在因素重要性变化的因素选择机制,利用模型不确定性减少的原理,在潜在因素所选择的子空间上生成集成推荐器。在三个公开可用的基准数据集上,对推荐系统的各种最新方法进行了评估。实验结果证实了该方法的有效性和高效性。
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引用次数: 0
Research on mobile readers' continuance intention: A reading type perspective 基于阅读类型视角的移动读者延续意向研究
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.56
Xiao Jiang
Readers' continuance use is the basis for the development of mobile reading. This paper conducted an empirical research on mobile readers' continuance intention. The mobile readers are categorized into four groups: information readers, culture readers, recreation readers and research readers. Structural equation modeling is employed to empirically identify the factors that influence the main three types of mobile readers' continuance intention. The results show that, the factors and their significance are different in the three types of reader groups.
读者的持续使用是移动阅读发展的基础。本文对移动读者的继续阅读意愿进行了实证研究。移动读者可以分为四类:信息读者、文化读者、娱乐读者和研究读者。本文采用结构方程模型对影响主要三类移动读者继续阅读意愿的因素进行实证分析。结果表明,三种类型的读者群体的影响因素及其意义有所不同。
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引用次数: 1
期刊
2015 IEEE 12th International Conference on e-Business Engineering
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