- Shuhao Liu;Baochun Li;
Software-Defined Networking(SDN) has emerged as a promising direction for next-generation network design. Due to its clean-slate and highly flexible design, it is believed to be the foundational principle for designing network architectures and improving their flexibility, resilience, reliability, and security. As the technology matures,research in both industry and academia has designed a considerable number of tools to scale software-defined networks, in preparation for the wide deployment in wide-area networks. In this paper, we survey the mechanisms that can be used to address the scalability issues in software-defined wide-area networks. Starting from a successful distributed system, the Domain Name System, we discuss the essential elements to make a large scale network infrastructure scalable. Then, the existing technologies proposed in the literature are reviewed in three categories: scaling out/up the data plane and scaling the control plane. We conclude with possible research directions towards scaling software-defined wide-area networks.
2015年03期 v.20 221-232页 [查看摘要][在线阅读][下载 507K] [下载次数：61 ] |[网刊下载次数：0 ] |[引用频次：1 ] |[阅读次数：0 ] - Jianjiang Li;Jie Wu;Zhanning Ma;
With the rise of various cloud services, the problem of redundant data is more prominent in the cloud storage systems. How to assign a set of documents to a distributed file system, which can not only reduce storage space, but also ensure the access efficiency as much as possible, is an urgent problem which needs to be solved.Space-efficiency mainly uses data de-duplication technologies, while access-efficiency requires gathering the files with high similarity on a server. Based on the study of other data de-duplication technologies, especially the Similarity-Aware Partitioning(SAP) algorithm, this paper proposes the Frequency and Similarity-Aware Partitioning(FSAP) algorithm for cloud storage. The FSAP algorithm is a more reasonable data partitioning algorithm than the SAP algorithm. Meanwhile, this paper proposes the Space-Time Utility Maximization Model(STUMM), which is useful in balancing the relationship between space-efficiency and access-efficiency. Finally, this paper uses 100 web files downloaded from CNN for testing, and the results show that, relative to using the algorithms associated with the SAP algorithm(including the SAP-Space-Delta algorithm and the SAP-Space-Dedup algorithm), the FSAP algorithm based on STUMM reaches higher compression ratio and a more balanced distribution of data blocks.
2015年03期 v.20 233-245页 [查看摘要][在线阅读][下载 375K] [下载次数：37 ] |[网刊下载次数：0 ] |[引用频次：6 ] |[阅读次数：0 ] - Qinghai Liu;Hong Shen;Yingpeng Sang;
Anonymized data publication has received considerable attention from the research community in recent years. For numerical sensitive attributes, most of the existing privacy-preserving data publishing techniques concentrate on microdata with multiple categorical sensitive attributes or only one numerical sensitive attribute.However, many real-world applications can contain multiple numerical sensitive attributes. Directly applying the existing privacy-preserving techniques for single-numerical-sensitive-attribute and multiple-categorical-sensitiveattributes often causes unexpected disclosure of private information. These techniques are particularly prone to the proximity breach, which is a privacy threat specific to numerical sensitive attributes in data publication. In this paper, we propose a privacy-preserving data publishing method, namely MNSACM, which uses the ideas of clustering and Multi-Sensitive Bucketization(MSB) to publish microdata with multiple numerical sensitive attributes.We use an example to show the effectiveness of this method in privacy protection when using multiple numerical sensitive attributes.
2015年03期 v.20 246-254页 [查看摘要][在线阅读][下载 391K] [下载次数：55 ] |[网刊下载次数：0 ] |[引用频次：14 ] |[阅读次数：0 ] - Xiaofan Zhao;Hong Shen;
We consider the problem of packing d-dimensional cubes into the minimum number of 2-space bounded unit cubes. Given a sequence of items, each of which is a d-dimensional.d 3/ hypercube with side length not greater than 1 and an infinite number of d-dimensional.d 3/ hypercube bins with unit length on each side, we want to pack all of the items in the sequence into the minimum number of bins. The constraint is that only two bins are active at anytime during the packing process. Each item should be orthogonally packed without overlapping other items. Items are given in an online manner without the knowledge of or information about the subsequent items. We extend the technique of brick partitioning for square packing and obtain two results: a three-dimensional box and d-dimensional hyperbox partitioning schemes for cube and hypercube packing, respectively. We design5.43-competitive and 32/21 2d-competitive algorithms for cube and hypercube packing, respectively. To the best of our knowledge these are the first known results on 2-space bounded cube and hypercube packing.
2015年03期 v.20 255-263页 [查看摘要][在线阅读][下载 579K] [下载次数：27 ] |[网刊下载次数：0 ] |[引用频次：0 ] |[阅读次数：0 ]
- Boyuan Liu;Wenhui Fan;Tianyuan Xiao;
Fuzzy Cognitive Map(FCM) is an inference network, which uses cyclic digraphs for knowledge representation and reasoning. Along with the extensive applications of FCMs, there are some limitations that emerge due to the deficiencies associated with FCM itself. In order to eliminate these deficiencies, we propose an unsupervised dynamic fuzzy cognitive map using behaviors and nonlinear relationships. In this model, we introduce dynamic weights and trend-effects to make the model more reasonable. Data credibility is also considered while establishing a machine learning model. Subsequently, we develop an optimized Estimation of Distribution Algorithm(EDA) for weight learning. Experimental results show the practicability of the dynamic FCM model. In comparison to the other existing algorithms, the proposed algorithm has better performance in terms of convergence and stability.
2015年03期 v.20 285-292页 [查看摘要][在线阅读][下载 321K] [下载次数：35 ] |[网刊下载次数：0 ] |[引用频次：1 ] |[阅读次数：0 ] - Yuanlin Chen;Yueting Chai;Yi Liu;Yang Xu;
When consumers make purchase decisions, they generally refer to the reviews generated by other consumers who have already purchased similar products in order to get more information. Online transaction platforms provide a highly convenient channel for consumers to generate and retrieve product reviews. In addition,consumers can also vote reviews perceived to be helpful in making their decision. However, due to diverse characteristics, consumers can have different preferences on products and reviews. Their voting behavior can be influenced by reviews and existing review votes. To explore the influence mechanism of the reviewer, the review,and the existing votes on review helpfulness, we propose three hypotheses based on the consumer perspective and perform statistical tests to verify these hypotheses with real review data from Amazon. Our empirical study indicates that review helpfulness has significant correlation and trend with reviewers, review valance, and review votes. In this paper, we also discuss the implications of our findings on consumer preference and review helpfulness.
2015年03期 v.20 293-305页 [查看摘要][在线阅读][下载 700K] [下载次数：147 ] |[网刊下载次数：0 ] |[引用频次：26 ] |[阅读次数：0 ] - Yanli Yang;Hao Guo;Tian Tian;Haifang Li;
Link prediction attempts to estimate the likelihood of the existence of links between nodes based on available brain network information, such as node attributes and observed links. In response to the problem of the poor efficiency of general link prediction methods applied to brain networks, this paper proposes a hierarchical random graph model based on maximum likelihood estimation. This algorithm uses brain network data to create a hierarchical random graph model. Then, it samples the space of all possible dendrograms using a Markov-chain Monte Carlo algorithm. Finally, it calculates the average connection probability. It also employs an evaluation index.Comparing link prediction in a brain network with link prediction in three different networks(Treponemapallidum metabolic network, terrorist networks, and grassland species food webs) using the hierarchical random graph model, experimental results show that the algorithm applied to the brain network has the highest prediction accuracy in terms of AUC scores. With the increase of network scale, AUC scores of the brain network reach 0.8 before gradually leveling off. In addition, the results show AUC scores of various algorithms computed in networks of eight different scales in 28 normal people. They show that the HRG algorithm is far better than random prediction and the ACT global index, and slightly inferior to local indexes CN and LP. Although the HRG algorithm does not produce the best results, its forecast effect is obvious, and shows good time complexity.
2015年03期 v.20 306-315页 [查看摘要][在线阅读][下载 622K] [下载次数：64 ] |[网刊下载次数：0 ] |[引用频次：10 ] |[阅读次数：0 ] <正>Tsinghua Science and Technology was started publication in 1996.It is an international academic journal sponsored by Tsinghua University and is published bimonthly.This journal aims at presenting the up-to-date scientific achievements in computer science,electronic engineering,and other IT fields.It is indexed by EI and other abstracting indexes.From 2012,the journal enters into IEEE Xplore Digital Library and all papers published there are freely downloadable.This special issue is devoted to addressing new challenges in Big Data computation and communications(Big Com).We intend to bring together researchers,developers,and practitioners interested in Big Data analytics,
2015年03期 v.20 316页 [查看摘要][在线阅读][下载 53K] [下载次数：21 ] |[网刊下载次数：0 ] |[引用频次：0 ] |[阅读次数：0 ]