Earticle

An effective decentralized metadata management schema is critical to a reliable and scal-able large-scale distributed storage system. With regard to the defects of huge expansion cost and high sensitivity to cluster alteration borne in both the hash-based and subtree-based metadata management schemas, a metadata server (MDS) clustering schema based on con-sistent hash structure, named DSVL, is proposed. By introducing virtual MDS into the con-sistent MDS cluster, it can effectively balance MDS cluster load. Besides, the standby mecha-nism and the lazy update policy are merged and applied to the MDS cluster to accomplish rapid MDS failover as well as zero data migration in case of cluster alteration. The results of prototype system and simulation test prove that DSVL, with the features of balanced metadata distribution, rapid failover, flexible scalability and zero data migration amount in case of node alteration, can meet the demands for flexible and effective management of large-scale data storage systems with ever increasing data amount.

With the coming of the big data age, more and more string dictionaries need to be processed. The existing string dictionary indexes are either too space-consuming, or lack of locality of reference, making them inapplicable in the external memory environment. Targeted with these problems, first we design a new succinct representation of Patricia trie using LOUDS encoding. Then applying it to external memory indexing problem, we propose a new string dictionary index SB-trie, which is not only succinct on space, but also has good locality of reference, making it I/O efficient in external memory environment. Experiments show that SB-trie consumes less space and has greater searching performance in disk environment.

Certificateless public key cryptography (CL-PKC), does not require the use of the certificate to guarantee the authenticity of public keys. It does rely upon the use of a trusted third party (TTP), who is in possession of a master key. CL-PKC does not suffer from the key escrow property. Thus, CL-PKC can be seen as a model for the use in public key cryptography. In this paper, we proposed a new certificateless Chameleon signature scheme based on bilinear pairings. The proposed scheme is more efficient than AL-Riyami and Pateson [10] schemes. And our scheme is un-forgeable under the hardness assumption of the q-strong Diffie-Hellman problem and Computational Diffie-Hellman problem.

In SaaS, since the service provider may be un-trusted, it is essential for tenants to enable query result correctness and completeness. However, existing data authentication methods can not fit well with the customized multi-tenants sharing storage mode. This paper put forward a multi-tenant data authentication model (TCDA). TCDA is a composite structure that constructs pivot authentication tree (α-tree) on the pivot table and combines it with signature set (β-set) built on sparse table to ensure that malicious insiders can't modify the data in pivot table and sparse table. The main contribution of TCDA is it can guarantee the tenant query result in one tree travels and return the verification object corresponding to the result on pivot table and sparse table. And in this paper, we propose an improved TCDA model to minimize the processing overhead through appending aggregation signature of the node descendants to the internal α-tree node. We demonstrate effectiveness of our model compare with MHT and DSAC through the experiment.

For the lack of "density-based spatial clustering with noise" (DBSCAN) algorithm in dealing with large data sets, MapReduce programming model is proposed to achieve the clustering of DBSCAN. Map functions to complete the data analysis, and get clustering rules in different data objects; Then Reduce functions merge these clustering rules to get a final result. Experimental results show: the DBSCAN of MapReduce running on the cloud computing platform Hadoop has good speedup and scalability.

Synthesis analysis is the effective process for solving problems in Software engineering. We provide description for scheduler concept by using synthesis analysis. We presented implementation of architecture design alternatives for scheduler concept based on design algebra concept. During the process of alternative space analysis different alternative solutions are searched and also evaluating the different design solutions based on quality criteria or constraints. This is more effective processes for designing the different systems based on quality criteria and constraints. In this paper balancing design alternatives for this concept with object oriented design methods.

With the growing popularity of outsourced databases (ODBs), access control for multiple users with different privileges in outsourced environments is required in more and more applications. Under the assumption that ODBs may be interested in the original data value, or delay the update operations when end users cannot verify the results, this paper attempts to enhance ODBs with finegrained access control for multiple users with less impact on their other functionalities. Our work can be divided into two parts. In the first part, we propose a method to enforce the access control rules by encrypting the original table and using the keys to distinguish various rights. In addition to read/non-read rights, read/update rights can be distinguished in our encrypted table. We also implement validation-only rights for ODBs and oblige them to fulfill any update validation without knowing the original data. In the second part, we study the query evaluation over the encrypted table. Two kinds of B+ tree indexes on each column are designed, which can accelerate the selection in ODBs.

Ontology alignment finds matching elements from different ontologies. A number of ontology alignment techniques have been proposed. But few of them are adaptive to fuzzy ontologies alignment. A key problem is that formulas for computing similarity between elements from precise ontologies can’t be directly applied to those elements from fuzzy ontologies. In this paper, we exploit WordNet to compute similarity between two words. And Inspired by formula for computing similarity between two formal concepts from concept lattice, we propose an effective similarity formula for computing similarity between classes from different fuzzy ontologies. Also, we present an algorithm which is global optimal for aligning fuzzy ontologies. A prototype is implemented and the experiment shows that our approach is worthy.

Software Maintainability is the ability of the system to undergo changes with a degree of ease and Quality assurance refers to planned and systematic production that provides confidence in a product. This paper describes the different issues of software maintainability and quality assurance in the agile environment. This paper also presents the different metrics that improve the overall quality of the software maintainability in the agile environment. This paper proposes the model of software maintainability and quality assurance in the agile environment. The approach that is used is based on the customer requirements by iterative interaction with customers to provide the best requirement with assured quality.

With the advent of the information age, the data volumes of various industries are in explosive growth, which increasingly highlights the importance of data. When a disaster occurs, how to recover the data completely and rapidly is one of the important issues receiving common concerns throughout the current industrial and academic circles. Based on the traditional disaster recovery system, this paper researches and implements a PRS algorithm-based distributed disaster recovery system[1, 2] called OsnDDR, which ensures the high availability of the system under the circumstance of continuous disasters or multi-node damage. The system adopts PRS algorithm based on RS erasure code [3] to reduce the storage resource consumption caused by the data redundancy and designs the load balancing strategy to guarantee the load balancing of each disaster recovery center in the system.

Tree structures are used extensively in domains such as XML data management, web log analysis, biological computing, and so on. In this paper we introduce the problem of mining frequent sequential trees in a large tree sequence database. We present a framework for mining frequent sequential trees in a so-called tree sequence database. Basically, this framework employs a transformation-based approach which converts the sequential tree mining problem into a traditional sequence mining problem. Our approach firstly mines frequent trees in the tree sequence database. Secondly, we perform a database transformation by means of tree-containment computation to generate a sequence database. Thirdly, after the transformation, frequent sequence patterns can be mined in the newly created sequence database using a conventional sequence mining technique. Finally we perform an inverted transformation process on the output of sequence mining to obtain sequential tree patterns. Experimental results on synthetic datasets show that the proposed framework is both effective and efficient in finding frequent sequential trees in a large tree sequence database.

Currently, the usage of social networking sites are increasing rapidly. Social networks are used to connect people, share information between users and maintain relation between friends. Hundreds of thousands of people are using these social networking services like Facebook, twitter etc., User security is the main aspect in present days from person to person interaction. There is a major task of online social network is information filtering. An online social network provides the little support for allowing sharing the information on the user walls. In this paper we propose to introduce efficient user security mechanism in transmission of messages from one user to another user. So we describe to develop methodology called machine learning algorithm called decision tree algorithm for security in their user walls. Our experimental results show efficient learning process in extracting feedback process generation in customized system operations in online social networks. In this we also consider the functionalities of each user in relevant data sharing of social networks.

The problem of difference teaching is solved by that the data mining is used in network instructional platform of "Modern Educational Technology". This paper introduces difference teaching and data mining, analyzes learning elements and data in network instructional platform, elaborate the realization of the difference teaching by the application of data mining. Practice shows that the application of the data mining in network instructional platform of "Modern Educational Technology" which pays attention to the difference between learners, provides different resources and interactive strategy from curriculum resources recommended and assisting teachers to make decision, promotes each student's full development.

This paper presents a report on the experimental study of the impact of false minutiae on the performance of fingerprint matching systems. A 3-tier algorithm comprising of pre-processing, minutiae extraction and post-processing stages formed the backbone of the experiments. The pre-processing stage enhanced the fingerprint image, the minutiae extraction stage used the minutiae properties to detect and extract true and false minutiae points while the post-processing stage eliminated the false minutiae points. The experiments were performed on the four datasets in each of the three standard fingerprint databases; namely FVC2000, FVC2002 and FVC2004. The completion times for the minutiae extraction and the post-processing algorithms on each dataset were measured. A standard fingerprint matching algorithm was also implemented for verifying the impact of false minutiae points on FAR, FRR and the matching speed. Analysis of the obtained results revealed that for reliable and optimal performance of fingerprint matching systems, false minutiae points must be eliminated as much as possible from their operations.

XQuery is a language for querying XML data which is widely used on the Internet. In XQuery, user can define recursive functions for querying and processing XML data. XML twig pattern query is considered as core operation for querying XML data which has been studied intensively in recent years. More powerful recursive queries can be achieved via combining user-defined recursive function and twig pattern query. This paper proposes recursive twig pattern query (RTPQ) to extend traditional twig pattern query with recursion and an effective holistic twig matching algorithm for RTPQ. With the help of RTPQ, recursive function call can access its result instead of evaluating local twig pattern queries in each calling. Results of experiments show that this approach can improve query efficiency and eliminate redundant intermediate results.

Clustering is one of the main tasks used in pattern recognition and classification. Out of many methods that have been reported till date the most widely used methods are based on likelihood approach of mixture model. Among different mixture models, Expectation Maximization for Gaussian Mixture is most exploited and trusted algorithm for data clustering. However, it has some short comings such as initial parameters are to be given a-priori, convergence speed is slow and the results obtained are highly dependent upon the initial parameters. Many variations have been carried out in implementing EM algorithm but still there is ample scope for improvement. The proposed algorithm tries to overcome these shortcomings and provide more robust and efficient version of clustering algorithm. An improvement related to cluster partitioning is proposed in the existing algorithm resulting some advantages. The robustness and efficacy of the algorithm is demonstrated qualitatively as well as quantitatively with the help of some experiments.

Community detection is widely applied in many fields and k-clique community detection is one important detection method. There are many works on k-clique community detection. However, the work on analyzing the structure of k-clique community is rare. In this paper, we first give the definition of k-clique community tree and closed l-s-clique community, which could be used as the index of analyzing k-clique community. Then we give the definition of l-s-clique community pivot to describe the members playing the bridging roles in k-clique community. We analyze the properties of l-s-clique community and propose KCliqueTree algorithm based on the properties. This algorithm could efficiently generate k-clique community tree whose leaf nodes represent closed l-s-clique community. We also propose LSBridge algorithm to search l-s-clique community pivot. At last, we conduct case study on DBLP (Digital Bibliography & Library Project) dataset, which shows the availability of our definitions and algorithms.

In this paper we discuss about a target tracking algorithm based on Mean Shift and Kalman Filter, which is suitable for high speed moving target tracking. The basic Mean Shift algorithm is described in this paper as well. Although basic Mean Shift algorithm can realize target tracking without arguments or searching all the areas effectively, it has shortcomings which can limit its effectiveness under some conditions such as the target covered by something when moving or the target moving with high speed. In order to make Mean Shift target tracking algorithm satisfies the practical application, such as high speed moving target tracking, we analysis the lack of basic Mean Shift algorithm, then we design a target tracking algorithm which combine an improved Mean Shift target tracking algorithm with Kalman Filter(IMKTT). In the fourth section of the paper, we apply the algorithm to a monitoring system of Shanghai University. The result shows that the algorithm designed in this paper can effectively track high speed moving target, such as a car.

The principal role of Data warehouses in making strategy decisions makes its quality crucial for organizations. Quality of data models for data warehouse has significant effect on the quality of data warehouse. Therefore, we need methods, models and tools to have quantitative and objective measurement of quality of data models for data warehouses. Lack of a set of defined measures made us to define a set of metrics that can be used to measure the complexity, understandability, believability, usability, accessibility, data currency and modifiability which are in turn defined as quality characteristics for data warehouse systems. The proposed metrics may act as objective indicators of the quality of data warehouse models and also help the developers to select quality data model among various semantically equivalent models. The other advantage of these metrics is that they are available during early phase of software development life cycle.

Cloud computing is considered as a novel pattern of information management and computing services, taken as another revolution in the information industry. This paper introduces the overall planning, function structure, security, and resource integration of the cloud-computing campus information center (C3IC) with practice. And an information resource integration model and a load baseline algorithm based on radial basis function are also proposed and discussed, to produce some rewarding experiences for C3IC’s construction with very strong practicability. With the C3IC, the units in digital campus can be provided with computing-resources rent service in virtualization. Finally, based on the analysis of the latest research work on the C3IC, the significance is discussed and outlined.

As for the lack of the constraint on operations in traditional real-time collaborative environment, the paper introduces to adopt right allocation technique to support the document management of the shared document of different work groups. The paper gives formal definition of the Tree Document Model supporting role management, describes the configuration process of the roles, defines the formats of the right operations, proposes conflict detection and resolution strategies for Apply/Apply, Apply/Delete and Apply/Update conflicts. Besides, the paper improves the address space transformation strategy to guarantee the correct execution of the right operations in the distributed sites. Efficiency analysis of the improved algorithm is given and the application of this strategy in the Co-AutoCAD system proves the validity of the whole strategy.