Abstract:A Web service business protocol is used to describe the external behavior of a service and plays an important role in the service discovery, composition, verification, runtime service trustworthy guarantee, and so on. Presently, some research has been done on discovering the Web service business protocol from the invocation logs. Most of these works focused on the control-flow of Web service business protocols that give a temporal constraint among the operations of Web service. However, the data constraints and the consistency between the data-flow and the control-flow are also important and have not received enough attention. This paper studies the Web service business protocol from the service invocation logs and focuses on mining the relations, or the constraints between the message values and service operations. This paper proposes a Petri-net based model, called Business Protocol Net (simply, BPN), to describe the behavior of a service. Based on this model, a mining framework is proposed to automatically generate the BPN model from message traces. Experimental results illustrate that the method is effective in discovering the Web service business protocol from invocation logs.

Abstract:With the growing number of alternative Web services in the open Web service environment, users have put forward new demands that bind the runtime of Web services, which requires as much short computation time as possible to satisfy user’s end-to-end QoS requirements service composition. Therefore, this paper proposes a Web service dynamic selection approach, based on the decomposition of global QoS constraints, WSDSA (Web service dynamic selection approach). The WSDSA uses as adaptive adjustment method (AAM), based on fuzzy logic and adaptive particle swarm optimization algorithm (APSO), to adaptively decompose global QoS constrains to local constraints with the user’s preferences, and then WSDSA can obtain the most appropriate composition service with local selection. Performance evaluations show WSDSA is very effective, and is able to reach optimal or near optimal results with a very low time cost, which satisfies the real time and dynamic service selection.

Abstract:Fault-Tolerant scheduling, an effective means of improving a system’s performance, plays a significant role in scheduling research. Despite the fact that fault-tolerant scheduling has been extensively proposed for real-time tasks on clusters, QoS (quality of service) requirements for some tasks have not been considered. This paper proposes a fault-tolerance scheduling algorithm FTQ (fault-tolerant QoS-based scheduling) for real-time tasks with QoS needs on heterogeneous clusters. FTQ adopts the primary/backup model and takes the timing constraints of tasks, QoS requirements of tasks, reliability of systems, and system resource utilization into account. FTQ can adjust the QoS levels of real-time tasks and the execution schemes of backup copies to improve system flexibility, reliability, schedulability, and resource utilization. The system reliability is quantitatively measured and combined into FTQ, which improves the system performance. Meanwhile, FTQ strives to advance the start time of primary copies and delay the start time of backup copies to make backup copies adopt passive execution scheme, or decrease overlapping sections of primary and backup copies as much as possible to improve resource utilization. FTQ adaptively adjusts the QoS levels of tasks and the execution schemes of backup copies to attain a higher flexibility. The overlapping technology of backup copies is employed. The latest start time of backup copies and its constraints are analyzed. Compared with NOFTQ and DYFARS, FTQ shows obvious superiority with a higher scheduling quality proven by a considerable number of simulated experiments.

Abstract:A key problem in software testing is having the right cost/benefit tradeoffs for the software that is being tested. Based on the 2-8 law of fault distribution in programs, the paper divides the test process in two stages for solving this problem. The first stage is to find the faults in software at minimum cost, and the second stage is to add some additional test cases for those faults found in the first stage to detect more potential faults in software. The paper lays emphasis on the realization of the first stage. According to the theories of both the deterministic finite state machine (DFSM) and set partition, a DFSM-based minimum test cost transition coverage criterion is presented in this paper, and the criterion’s sufficiency and necessary conditions are given. Moreover, two algorithms that realize the optimal transition coverage and the minimum test cost transition coverage are designed, and the effectiveness of the test set is also discussed. In the experiments, the method not only obtains a set of test cases with the minimal size and the shortest total length of all test cases, but also finds all faults in transitions of the DFSM.

Abstract:MPSoCs (multi-processor system-on-chips) are comprehensively applied in the embedded multimedia processing field. Multimedia MPSoCs often adopt the “host processor+multiple heterogeneous synergistic processor” architecture, which makes the trade-off between universality and flexibility. MPSoCs also take into consideration both performance and power-consumption, but challenges the method of performance optimization of System-on-Chip applications. This paper proposes an approach that improves the performance of application algorithms running on heterogeneous MPSoCs. The approach includes three stages: Application feature analysis, affine partitioning of kernel loops, and “application-architecture” mapping. It optimizes the multi-level parallelism and data locality of application algorithms to improve MPSoC performance. Experimental results show that the proposed approach can greatly improve the multimedia processing performance on heterogeneous MPSoCs.

Abstract:This paper presents a fundamentally different framework for uncovering the intricate properties of evolutionary networks. Contrary to static snapshots methods, this paper first traces the timelines of the networks. Then, based on extracted smooth segments from the timelines, a graph approximation algorithm is applied to capture the frequent characteristics of the network and reduce the noise of interactions. Moreover, by employing the relationship among multi-attributes, an innovative community detection algorithm is proposed for a detailed analysis on the approximate graphs. To track these dynamic communities, this paper also introduces a community correlation and evaluation method. Finally, by applying this novel framework to several real-world networks, this paper demonstrates the critical relationship between event and social evolution, and reveals meaningful properties in actual dynamic behaviors.

Abstract:Age is an important attribute of human beings. In recent years, automatic estimations of the user’s age have been becoming an active topic in pattern recognition, computer vision, voice recognition, human-computer interaction (HCI), etc. It can be widely used in many real applications such as forensics, e-business, security, and so on. In daily life, people can easily estimate the age of a person according to some visual and audio information (here mainly refers to face and voice) because humans’ faces and voices are important agents of their age. This paper introduces in detail the models, algorithms used in automatic age estimation based on visual and audio information, as well as their performance and characteristics. The possible future directions for the research in automatic age estimation are also discussed.

Abstract:The dynamic description logic DDL (dynamic description logic) provides a kind of action theory based on description logics. It is a useful representation of the dynamic application domains in the environment of the Semantic Web. In order to bring the representation capability of the branching temporal logic into the dynamic description logic, this paper treats the time slices of temporal logics as the executions of atomic actions, so that the temporal dimension and the dynamic dimension can be unified. Based on this idea, constructed over the description logic ALCQIO, a temporal dynamic description logic, named TD_ALCQIO, is presented. Tableau decision algorithm is provided for TD_ALCQIO. Both the termination and the correctness of this algorithm have been proved. The logic TD_ALCQIO not only inherits the representation capability provided by the dynamic description logic constructed over ALCQIO (attributive language with complements, qualified number restrictions, inverse roles and nominals), but it also has the ability to describe and reason about some temporal features such as the reachability property and the safety property of the whole dynamic application domains. Therefore, TD_ALCQIO provides further support for knowledge representation and reasoning in the environment of the Semantic Web.

Abstract:This paper presents a heuristic survey propagation algorithm for solving Quantified Boolean Formulae (QBF) problem. A QBF solver based on the algorithm is designed, namely HSPQBF (heuristic survey propagation algorithm for solving QBF). This solver is a QBF reasoning engine that incorporates Survey Propagation method for problem solving. Using the information obtained from the survey propagation procedure, HSPQBF can select a branch accurately. Furthermore, when handling the branches, HSPQBF uses efficient technology to solve QBF problems, such as unit propagation, conflict driven learning, and satisfiability directed at implication and learning. The experimental results also show that HSPQBF can solve both random and QBF benchmark problems efficiently, which validates the effect of using survey propagation in a QBF solving process.

Abstract:A majority of previous research done on Support Vector Data Description (SVDD), which is one of the excellent and applied widely to kernel methods, were directed toward efficient implementations and practical applications. However, very few research attempts have been directed toward studying the properties of SVDD solutions. In this work, the primal optimization of SVDD is first transformed into a convex constrained optimization problem, and the uniqueness of the centre of ball is proved while the non-uniqueness of the radius is investigated. This paper also investigates the property of the centre and radius from the perspective of the dual optimization problem, and suggests a method to calculate the radius. The results of this paper complete the SVDD theory, and contribute to further theoretical study and extensive applications.

Abstract:By making use of compressive mapping and isomorphic mapping in the kernel extension of graph embedding, this paper proves that the essence of kernel extension of graph embedding (KGE) is KPCA (kernel principal component analysis) plus all kinds of linear dimension reduction approaches interpreted in a linear extension of graph embedding (LGE). Based on the theory framework, a combined framework, which takes advantage of the discriminant feature in both null and non-null spaces, is developed. Furthermore, every kernel dimensionality reduction algorithm has its own corresponding combined algorithm. The experimental results from ORL, Yale, FERET and PIE face databases show that the proposed methods are better than the original methods in terms of recognition rate.

Abstract:In past years, the problem with nonlinear dimensionality reduction has aroused a great deal of interest in many research fields, including pattern analysis, machine learning, and data mining. However, the general manifold learning methods are not robust on the outliers. In the paper, an outlier detection method, based on reconstruction weights, is proposed. The proposed algorithm constructs local ‘strong’ neighborhoods on each sample point, and computes the reliability score of each sample point using local reconstruction weights, and then detects the outliers using the reliability scores. The advantages of the algorithm are that it has fast computation, low parameter, and low parameter sensitivity. Based on the proposed outlier detection method, the robust Isomap algorithm is proposed in this paper. Experimental results illustrate that the proposed algorithm can detect the outliers efficiently and make the manifold learning methods more robust on the outliers.

Abstract:This paper proposes MDA, a mobile distribution-aware data dissemination, based on Publish/Subscribe, for Vehicular Ad Hoc Networks (VANETs). To take advantage of VANETs’ self-organization and self-stabilization, this paper first establishes an appropriate Publish/Subscribe model in VANETs. Next, the subscribers’ distribution is predicted by calculating the delivery probabilities between vehicles and subscribers. Third, based on the predicted distribution, adjust notification token’s deployment and forwarding in the VANETs are used to achieve effective distribution of notification brokers (notification-token holder). Compared with existing solutions, a novel heuristic algorithm is applied to alter the notification broker distribution and to adapt to a real-time VANETs situation. Furthermore, MDA can also reduce an overall network load of VANET by controlling the occurrences in broadcasting. Simulation results based on a real city map and realistic traffic situations show that the MDA performs much better in terms of delivery and delay ratios and have a higher network load than other solutions.

Abstract:This paper makes three contributions. First, experiments have shown that simulation procedures used in existing localization algorithms for mobile sensor networks cannot output stable statistical data. This paper discusses the reasons for this and proposes a quantitative method to set up a simulation procedure that can output stable statistical data. Then, the paper evaluates and compares the accuracy of typical localization algorithms for mobile sensor networks in both obstacle-free and non-free environments. Results show that in environments with obstacles, many techniques that have been proposed, in the past, to improve localization accuracy in existing algorithms are useless and inversely decrease the algorithm’s accuracy. At last, this paper proposes several metrics that can be used by a single node to evaluate the accuracy of its location estimate. Results show that the “possible maximum localization error” metric, which was proposed in previous works, performs best by indicating the accuracy of location estimate for a single node.

Abstract:The position function is becoming more and more important for applications in WSNs, so a novel localization model, which is based fuzzy, is aimed at the localization problem. In this model, a space is divided into several small areas by some swatch nodes; every swatch node has its unique signal vector. An unknown node’s position can be calculated by computing the approach degree between the signals of the swatch and unknown nodes. This model adopts the RF signal to locate the unknown node. It cannot only avoid the overlapped error in a range-based localization model, but can also avoid the high complex. The experimental results in NS-2 show that this model performs well and is suitable for applications in WSNs.

Abstract:It is essential for wireless sensor networks (WSNs) to forward information collected by sensors to the sink quickly and efficiently through multi-hop relay. It is found that both duty cycle in the media access control (MAC) layer and the radio irregularity affect the efficiency of routing protocol greatly. Though traditional layered protocol has been proven to have the advantage of modularity, its whole performance cannot achieve its optimal performance since each layer works independently. Furthermore, most existing protocols that sacrifice time to improve energy-efficiency will bring unacceptable end-to-end delays to time-sensitive systems. This paper proposes a delay-constrained and energy-efficient cross-layer routing protocol (DECR), which takes into account related information of MAC and link layers when making routing decisions where the objective is to maximize the energy-efficiency of a node on the premise that end-to-end delay is restricted to the predefined upper bound. Both analysis and simulation results show that DECR performs well.

Abstract:Based on the characteristics of ad hoc security routing protocols (SRPs), the advantages and disadvantages of the strand space theory are analyzed. An analysis model for protocol attacks, which leads to a nonexistent route that is accepted by the protocol, is designed on the basis of the strand space model. Finally, this paper demonstrates the usefulness of this model in the case of a security ad hoc routing protocol: Extended SRP.

Abstract:This paper studies the xor branch numbers of diffusion structures, which uses the nonlinear transformations over the finite field GF(2). This paper gives the definition of the xor branch numbers of diffusion structures and the relations between it and the strength of a cipher against differential and linear cryptanalysis. Also, this paper has proven that the xor branch numbers of diffusion structures is about modulo 2ⁿ addition, and the modulo 2 addition is equal to that of the diffusion structure over the finite field GF(2), which 1 is substituted for the odd coefficient and 0 for the even coefficient and the modulo 2ⁿ addition for the modulo 2 addition. Consequently, this paper simplifies the computation problem of the xor branch numbers in this kind of nonlinear diffusion structure.

Abstract:Traditional identifier-based authorization models are limited to having different authorization paths that will cause the inconsistency in propagation of permission. In addition, unauthorized entities may acquire illegal permission by such an identifier-based authorization path. In order to solve these two problems, an attribute-based authorization delegation model (ABADM), suitable for multi-domain environments is presented. In the ABADM model, the delegation of authority and the propagation of permission are all based on the attribute sets of entities, which ensure that the entities on the same credential chain have the same permission. The model integrates attribute-permission assignation policies inside autonomic domains and the interdomain attributes mapping model. The algorithm for calculating the attribute sets and permissions of entities in the multi-domain environments is proposed. The usage of the ABADM model is illustrated through a common example.

Abstract:Network protocol reverse analysis is an important aspect of malware analysis. There are many different network protocols and every protocol contains different types of fields that result in various malware behaviors. Without the protocol syntax and filed semantics, analyzers cannot understand how malware interacts with the outside network. This paper presents a syntax and a behavior semantics analysis method of the network protocol. By monitoring the way malware parse the network data and by using different fields in a virtual execution environment, this method can identify protocol fields, extract protocol syntax and correlate each syntax with malware behaviors, accordingly. This paper designs and implements the prototype Prama (protocol reverse analyzer for malware analysis). Experimental results show that this method can correctly infer protocol syntax and tag fields with meaningful malware behaviors.

Abstract:Certificateless hybrid signcryption can handle messages of arbitrary length while the conventional certificateless signcryption cannot. This paper demonstrates that the attacks presented by Selvi, et al., do not hold, and proposes a new certificateless hybrid signcryption scheme, which outperforms all the existing schemes on both bandwidth usage and computation efficiency. Hence, this scheme is more suitable for the applications with a narrow bandwidth and limited computation resources such as ad hoc networks. This scheme has been proven to be secure in the random oracle model, under the bilinear Diffie-Hellman assumption.