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Volume 21 No. 1
01 February 2016

Wentao Han,Xiaowei Zhu,Ziyan Zhu,Wenguang Chen,Weimin Zheng,Jianguo Lu

2016, 21(1): 1-16.   doi:10.1109/TST.2016.7399279
Abstract ( 167 HTML ( 5   PDF(14660KB) ( 157 )   Save

Weibo is the Twitter counterpart in China that has attracted hundreds of millions of users. We crawled an almost complete Weibo user network that contains 222 million users and 27 billion links in 2013. This paper analyzes the structural properties of this network, and compares it with a Twitter user network. The topological properties we studied include the degree distributions, connected components, distance distributions, reciprocity, clustering coefficient, PageRank centrality, and degree...

Huan Ma,Hao Ding,Yang Yang,Zhenqiang Mi,James Yifei Yang,Zenggang Xiong

2016, 21(1): 17-28.   doi:10.1109/TST.2016.7399280
Abstract ( 193 HTML ( 0   PDF(1768KB) ( 235 )   Save

To address the issue of internal network security, Software-Defined Network (SDN) technology has been introduced to large-scale cloud centers because it not only improves network performance but also deals with network attacks. To prevent man-in-the-middle and denial of service attacks caused by an address resolution protocol bug in an SDN-based cloud center, this study proposed a Bayes-based algorithm to calculate the probability of a host being an attacker and further presented a detection ...

Xi Guo,Hailing Li,Aziguli Wulamu,Yonghong Xie,Yajing Fu

2016, 21(1): 29-39.   doi:10.1109/TST.2016.7399281
Abstract ( 117 HTML ( 0   PDF(3140KB) ( 281 )   Save

In this paper, we study the skyline group problem over a data stream. An object can dominate another object if it is not worse than the other object on all attributes and is better than the other object on at least one attribute. If an object cannot be dominated by any other object, it is a skyline object. The skyline group problem involves finding k-...

Xinfeng Ye

2016, 21(1): 40-54.   doi:10.1109/TST.2016.7399282
Abstract ( 178 HTML ( 2   PDF(2178KB) ( 172 )   Save

In cloud computing applications, users’ data and applications are hosted by cloud providers. This paper proposed an access control scheme that uses a combination of discretionary access control and cryptographic techniques to secure users’ data and applications hosted by cloud providers. Many cloud applications require users to share their data and applications hosted by cloud providers. To facilitate resource sharing, the proposed scheme allows cloud users to delegate their access permission...

Samneet Singh,Yan Liu

2016, 21(1): 55-70.   doi:10.1109/TST.2016.7399283
Abstract ( 290 HTML ( 0   PDF(2936KB) ( 209 )   Save

Cloud monitoring is of a source of big data that are constantly produced from traces of infrastructures, platforms, and applications. Analysis of monitoring data delivers insights of the system’s workload and usage pattern and ensures workloads are operating at optimum levels. The analysis process involves data query and extraction, data analysis, and result visualization. Since the volume of monitoring data is big, these operations require a scalable and reliable architecture to extract, agg...

Rui Wang,Jinglei Zhang,Suli Ren,Qingjuan Li

2016, 21(1): 71-79.   doi:10.1109/TST.2016.7399284
Abstract ( 196 HTML ( 0   PDF(1363KB) ( 353 )   Save

In recent years, Compressed Sensing (CS) has been a hot research topic. It has a wide range of applications, such as image processing and speech signal processing owing to its characteristic of removing redundant information by reducing the sampling rate. The disadvantage of CS is that the number of iterations in a greedy algorithm such as Orthogonal Matching Pursuit (OMP) is fixed, thus limiting reconstruction precision. Therefore, in this study, we present a novel Reducing Iteration Orthogo...

O. Kotevska,A. Lbath,S. Bouzefrane

2016, 21(1): 80-88.   doi:10.1109/TST.2016.7399285
Abstract ( 234 HTML ( 3   PDF(3851KB) ( 388 )   Save

In this study, we present a framework based on a prediction model that facilitates user access to a number of services in a smart living environment. Users must be able to access all available services continuously equipped with mobile devices or smart objects without being impacted by technical constraints such as performance or memory issues, regardless of their physical location and mobility. To achieve this goal, we propose the use of cloudlet-based architecture that serves as distributed...

Lianzhang Zhu,Shouchao Tan,Weishan Zhang,Yong Wang,Xiwei Xu

2016, 21(1): 89-101.   doi:10.1109/TST.2016.7399286
Abstract ( 164 HTML ( 0   PDF(1845KB) ( 236 )   Save

Mobile devices are resource-limited, and task migration has become an important and attractive feature of mobile clouds. To validate task migration, we propose a novel approach to the simulation of task migration in a pervasive cloud environment. Our approach is based on Colored Petri Net (CPN). In this research, we expanded the semantics of a CPN and created two task migration models with different task migration policies: one that took account of context information and one that did not. We...

Muhammad Yasir Shabir,Asif Iqbal,Zahid Mahmood,AtaUllah Ghafoor

2016, 21(1): 102-113.   doi:10.1109/TST.2016.7399287
Abstract ( 225 HTML ( 7   PDF(2307KB) ( 216 )   Save

Cloud computing has become a significant computing model in the IT industry. In this emerging model, computing resources such as software, hardware, networking, and storage can be accessed anywhere in the world on a pay-per-use basis. However, storing sensitive data on un-trusted servers is a challenging issue for this model. To guarantee confidentiality and proper access control of outsourced sensitive data, classical encryption techniques are used. However, such access control schemes are n...

Zhenlong Yuan,Yongqiang Lu,Yibo Xue

2016, 21(1): 114-123.   doi:10.1109/TST.2016.7399288
Abstract ( 351 HTML ( 14   PDF(2383KB) ( 484 )   Save

Smartphones and mobile tablets are rapidly becoming indispensable in daily life. Android has been the most popular mobile operating system since 2012. However, owing to the open nature of Android, countless malwares are hidden in a large number of benign apps in Android markets that seriously threaten Android security. Deep learning is a new area of machine learning research that has gained increasing attention in artificial intelligence. In this study, we propose to associate the features fr...