Analysis and case study on multi-dimensional scalability of the Internet architecture

This paper presents the definition of multi-dimensional scalability of the Internet architecture, and puts forward a mathematical method to evaluate Internet scalability based on a variety of constraints. Then, the method is employed to study the Internet scalability problem in performance, scale and service scalability. Based on the examples, theoretical analysis and experimental simulation are conducted to address the scalability issue. The results show that the proposed definition and evaluation method of multi-dimensional Internet scalability can effectively evaluate the scalability of the Internet in every aspect, thus providing rational suggestions and methods for evaluation of the next generation Internet architecture.     

Iterative selection algorithm for service composition in distributed environments

In service oriented architecture （SOA）, service composition is a promising way to create new services. However, some technical challenges are hindering the application of service composition. One of the greatest challenges for composite service provider is to select a set of services to instantiate composite service with end- to-end quality of service （QoS） assurance across different autonomous networks and business regions. This paper presents an iterative service selection algorithm for quality driven service composition. The algorithm runs on a peer-to-peer （P2P） service execution environment--distributed intelligent service execution （DISE）, which provides scalable QoS registry, dynamic service selection and service execution services. The most significant feature of our iterative service selection algorithm is that it can work on a centralized QoS registry as well as cross decentralized ones. Network status is an optional factor in our QoS model and selection algorithm. The algorithm iteratively selects services following service execution order, so it can be applied either before service execution or at service run-time without any modification. We test our algorithm with a series of experiments on DISE. Experimental results illustrated its excellent selection and outstanding performance.     

A survey on virtual reality

Virtual reality (VR) is a scientific method and technology created during the exploration of the nature by human beings to understand, simulate, and better adapt and use the nature. Based on the analysis on the whole process of VR, this paper presents different categories of VR problems and a type of theoretical expression, and abstracts three kinds of scientific and technical problems in VR field. On the basis of foresaid content, this paper also studies current major research objectives, research results and development trend of VR in the aspects of VR modeling method, VR representation technology, human-machine interaction and devices, VR development suites and supporting infrastructure, as well as VR applications. Finally, several theoretical and technical problems that need to be further studied and solved are addressed. Supported by the National Basic Research Program of China (Grant No. 2009CB320805), the National Natural Science Foundation of China (Grant Nos. 60533070, 60503066), and the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z333, 2006AA01Z311)     

Texture synthesis via the matching compatibility between patches

A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods. Supported by the National Basic Research Program of China (Grant No. 2009CB320802), the National Natural Science Foundation of China (Grant Nos. 60773026, 60833007), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z306, 2008AA01Z301), and the Research Grant of University of Macau     

Modeling plants with sensor data

Sensor data, typically images and laser data, are essential to modeling real plants. However, due to the complex geometry of the plants, the measurement data are generally limited, thereby bringing great difficulties in classifying and constructing plant organs, comprising leaves and branches. The paper presents an approach to modeling plants with the sensor data by detecting reliable sharp features, i.e. the leaf apexes of the plants with leaves and the branch tips of the plants without leaves, on volumes recovered from the raw data. The extracted features provide good estimations of correct positions of the organs. Thereafter, the leaves are reconstructed separately by simply fitting and optimizing a generic leaf model. One advantage of the method is that it involves limited manual intervention. For plants without leaves, we develop an efficient strategy for decomposition-based skeletonization by using the tip features to reconstruct the 3D models from noisy laser data. Experiments show that the sharp feature detection algorithm is effective, and the proposed plant modeling approach is competent in constructing realistic models with sensor data. Supported in part by the National Basic Research Program of China (Grant No. 2004CB318000), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2006AA01Z302, 2007AA01Z336), Key Grant Project of Chinese Ministry of Education (Grant No. 103001)     

A Trust-Based Approach to Estimating the Confidence of the Software System in Open Environments

Emerging with open environments, the software paradigms, such as open resource coalition and Internetware, present several novel characteristics including user-centric, non-central control, and continual evolution. The goal of obtaining high confidence on such systems is more di?cult to achieve. The general developer-oriented metrics and testing-based methods which are adopted in the traditional measurement for high confidence software seem to be infeasible in the new situation. Firstly, the software develo...     

LoI: Efficient relevance evaluation and filtering for distributed simulation

In large-scale distributed simulation, thousands of objects keep moving and interacting in a virtual environment, which produces a mass of messages. High level architecture (HLA) is the prevailing standard for modeling and simulation. It specifies two publish-subscribe mechanisms for message filtering: class-based and value-based. However, the two mechanisms can only judge whether a message is relevant to a subscriber or not. Lacking of the ability to evaluate the relevance, all relevant messages are delivered with the same priority even when congestion occurs. It significantly limits the scalability and performance of distributed simulation. Aiming to solve the relevance evaluation problem, speed up message filtering, and filter more unnecessary messages, a new relevance evaluation mechanism Layer of Interest (LoI) was proposed by this paper. LoI defines a relevance classifier based on the impact of spatial distance on receiving attributes and attribute values. An adaptive publish-subscribe scheme was built on the basis of LoI. This scheme can abandon most irrelevant messages directly. Run-time infrastructure (RTI) can also apply congestion control by reducing the frequency of sending or receiving object messages based on each objects’ LoI. The experiment results verify the efficiency of message filtering and RTI congestion control. Supported by the National Basic Research Program of China (Grant No. 2009CB320805), the National Natural Science Foundation of China (Grant No. 60603084), and the National High-Tech Research & Development Program of China (Grant No. 2006AA01Z331)     

Towards Next Generation Internet Management: CNGI-CERNET2 Experiences

Manageability is an important feature of next generation Internet;management and monitoring of IPv6-based networks are proving a big challenge.While leveraging current IPv4-based SNMP management scheme to IPv6 networks' management need is necessary,it is more urgent to coin a new network management architecture to accommodate the scalability and extensibility requirements of next generation Internet management.The paper proposes a novel network management architecture,IMN(Internet Management Network),whi...     

Recent advances on virtual human synthesis

Virtual human is a digital representation of the geometric and behavioral property of human beings in the virtual environment generated by computer. The research goal of virtual human synthesis is to generate realistic human bodymodels and natural human motion behavior. This paper introduces the development of the related researches on these two topics, and some progresses on example based human modeling and motion synthesis, and their applications in Chinese sign language teaching, computeraided sports training and public safety problem studying. Finally, some hot research topics in virtual human synthesis are presented. Supported partially by the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z336, 2007AA01Z320), and the National Natural Science Foundation of China (Grant No. 60533070)     

SKY: efficient peer-to-peer networks based on distributed Kautz graphs

Many proposed P2P networks are based on traditional interconnection topologies. Given a static topology, the maintenance mechanism for node join/departure is critical to designing an efficient P2P network. Kautz graphs have many good properties such as constant degree, low congestion and optimal diameter. Due to the complexity in topology maintenance, however, to date there have been no effective P2P networks that are proposed based on Kautz graphs with base > 2. To address this problem, this paper presents the “distributed Kautz (D-Kautz) graphs”, which adapt Kautz graphs to the characteristics of P2P networks. Using the D-Kautz graphs we further propose SKY, the first effective P2P network based on Kautz graphs with arbitrary base. The effectiveness of SKY is demonstrated through analysis and simulations. Supported partially by the National Natural Science Foundation of China (Grant Nos. 60673167 and 60703072), the Hunan Provincial Natural Science Foundation of China (Grant No. 08JJ3125), and the National Basic Research Program of China (973) (Grant No. 2005CB321801)     

Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.     

Perfect forward secure identity-based authenticated key agreement protocol in the escrow mode

The majority of existing escrowable identity-based key agreement protocols only provide partial forward secrecy. Such protocols are, arguably, not suitable for many real-word applications, as the latter tends to require a stronger sense of forward secrecy—perfect forward secrecy. In this paper, we propose an efficient perfect forward-secure identity-based key agreement protocol in the escrow mode. We prove the security of our protocol in the random oracle model, assuming the intractability of the Gap Biline...     

IETF softwire unicast and multicast framework for IPv6 transition

IPv6 protocol plays an important role in the next generation of Internet （NGI）. It is expected that the elegant coexistence of IPv4 and IPv6 is the key point of IPv6 transition. To solve the transition problem, we propose a mesh unicast framework and a multicast framework in this paper. We describe two reference models for the mesh unicast framework, and put forward two potential solutions for the multicast framework. A Linux-based prototype is implemented for IPv4 over IPv6 scenario and a test bed is deployed with 8 nodes on CERNET2. The deployment demon- strates the advantages of the framework.     

New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay

This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay. By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay. Two numerical examples show the effectiveness of the obtained results. Supported by the National Natural Science Foundation of China (Grant Nos. 60534010, 60728307, 60774048, 60774093), the Program for Cheung Kong Scholars and Innovative Research Groups of China (Grant No. 60521003) and the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z183), China Postdoctoral Sciencer Foundation (Grant No. 20080431150), and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200801451096)     

Estimating differential quantities from point cloud based on a linear fitting of normal vectors

Estimation of differential geometric properties on a discrete surface is a fundamental work in computer graphics and computer vision. In this paper, we present an accurate and robust method for estimating differential quantities from unorganized point cloud. The principal curvatures and principal directions at each point are computed with the help of partial derivatives of the unit normal vector at that point, where the normal derivatives are estimated by fitting a linear function to each component of the normal vectors in a neighborhood. This method takes into account the normal information of all neighboring points and computes curvatures directly from the variation of unit normal vectors, which improves the accuracy and robustness of curvature estimation on irregular sampled noisy data. The main advantage of our approach is that the estimation of curvatures at a point does not rely on the accuracy of the normal vector at that point, and the normal vectors can be refined in the process of curvature estimation. Compared with the state of the art methods for estimating curvatures and Darboux frames on both synthetic and real point clouds, the approach is shown to be more accurate and robust for noisy and unorganized point cloud data. Supported in part by the National Natural Science Foundation of China (Grant Nos. 60672148, 60872120), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z301, 2008AA01Z301), and Beijing Municipal Natural Science Foundation (Grant No. 4062033)     

Robust linear receivers for STBC systems with unknown co-channel interference

Focusing on space-time block code (STBC) systems with unknown co-channel interference, an oblique projection-based robust linear receiver is proposed in this paper. Based on the oblique projection, the desired signal subspace and interference-plus-noise subspace are first identified from the received signal. Then the matched filter receiver is used to decode the STBC encoded signals in the desired signal subspace. Simulation results show that the proposed linear receiver obtains significant performance improvement over conventional Capon-type receivers under finite sample-size situations and in the presence of channel estimation errors. Supported partially by the National Natural Science Foundation of China (Grant Nos. 60572046, 60502022, 60772095), and the National High-Tech Research & Development Program of China (Grant No. 2006AA01Z220)     

Runtime Monitoring CompositeWeb Services Through Stateful Aspect Extension

The execution of composite Web services with WS-BPEL relies on externally autonomous Web services. This implies the need to constantly monitor the running behavior of the involved parties. Moreover, monitoring the execution of composite Web services for particular patterns is critical to enhance the reliability of the processes. In this paper, we propose an aspect-oriented framework as a solution to provide monitoring and recovery support for composite Web services. In particular, this framework includes 1) a stateful aspect based template, where history-based pointcut specifies patterns of interest cannot be violated within a range, while advice specifies the associated recovery action; 2) a tool support for runtime monitoring and recovery based on aspect-oriented execution environment. Our experiments indicate that the proposed monitoring approach incurs minimal overhead and is efficient. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60673112, 90718033, the National Basic Research 973 Program of China under Grant No. 2009CB320704, and the High-Tech Research and Development 863 Program of China under Grand Nos. 2006AA01Z19B, 2007AA010301.     

Verifying functions in online stock trading systems

Temporal colored Petri nets, an extension of temporal Petri nets, are introduced in this paper. It can distinguish the personality of individuals (tokens), describe clearly the causal and temporal relationships betwee nevents in concurrent systems, and represent elegantly certain fundamental properties of concurrent systems, such as eventuality and fairness. The use of this method is illustrated with an example of modeling and formal verification of an online stock trading system. The functional correctness of the modeled system is formally verified based on the temporal colored Petri net model and temporal assertions. Also, some main properties of the system are analyzed. It has been demonstrated sufficiently that temporal colored Petri nets can verify efficiently some time-related properties of concurrent systems, and provide both the power of dynamic representation graphically and the function of logical inference formally. Finally. future work is described.     

QoS Requirement Generation and Algorithm Selection for Composite Service Based on Reference Vector

Under SOA (Service-Oriented Architecture), composite service is formed by aggregating multiple component services together in a given workflow. One key criterion of this research topic is QoS composition. Most work on service composition mainly focuses on the algorithms about how to compose services according to assumed QoS, without considering where the required QoS comes from and the selection of user preferred composition algorithm among those with different computational cost and di?erent selection resu...