Abstract:In the field of over-subscribed planning (OSP), goal utility dependencies are more useful than a single goal utility used to improve the plan quality, if goals are not independent. However, existing description models do not follow the grammatical specification of standard planning domain description language (PDDL), so they cannot be used in other OSP planning systems yet. To solve this, this paper presents a new way of describing goal utility dependencies with derived predicate rules and goal preferences, both of which are essential elements of PDDL. The goal of the process is to transform GAI (general additive independence) models into these two elements, where a derived predicate rule is used to describe the explicitly triggering conditions of a goal sub-set. A preference is used to depict explicitly its utility or value and both are indispensable. This compilation mechanism can not only maintain the characteristic of ease-of-use and straightness of GAI models in describing utility dependencies, but can also expend the ability of handling utility dependencies for general OSP planning systems. Also, this paper proves the semantic conservation in the compilation process. Experimental results in some OSP benchmark domains show that the algorithm is feasible and useful for improving the plan quality. It is the first time to describe goal utility dependency with PDDL elements in order to overcome the limitations of existing models.

Abstract:Community structure is one of the most important topological properties in complex networks. The network clustering problem (NCP) refers to the detection of network community structures, and many practical problems can be modeled as NCPs. So far, lots of network clustering algorithms have been proposed. However, further improvements in the clustering accuracy, especially when discovering reasonable community structure without prior knowledge, still constitute an open problem. Building on Markov random walks, the paper addresses this problem with a novel ant colony optimization strategy, named as RWACO, which improves prior results on the NCPs and does not require knowledge of the number of communities present on a given network. The framework of ant colony optimization is taken as the basic framework in the RWACO algorithm. In each iteration, a Markov random walk model is taken as heuristic rule. All of the ants’ local solutions are aggregated to a global one through clustering ensemble, which then will be used to update a pheromone matrix. The strategy relies on the progressive strengthening of within-community links and the weakening of between-community links. Gradually, this converges to a solution where the underlying community structure of the complex network will become clearly visible. The performance of algorithm RWACO was tested against a set of benchmark computer-generated networks, and as well on real-world network data sets. Experimental results confirm the validity and improvements of this approach.

Abstract:There are two properties of incomplete: the incomplete of model definition and causality. With the condition of incomplete model definition, the method of constraint between online observation and the off-line model are proposed to process disordered and undefined events to obtain practical trajectory. Contrast to no being diagnosed by a complete model, this method expands the applicative scope and breaks the model limitation. On condition of causality incomplete, the usage of causal diagram to connect components is proposed. This method solves the halfway diagnostic problem caused by setting models separately, meanwhile enhancing accuracy. It has been tested that the diagnostic way under those two conditions brings out expected results according to certain incomplete models. It also reformulates model partially and improves the model maturity.

Abstract:Tagging is one of the most important ways to categorize or indexing information at the age of Web 2.0. To handle the disadvantages of tagging systems such as inconsistentcies, redundancy and incompleteness, tag recommendation methods improve the quality of tags by providing candidate tags. In order to further improve the quality of tag recommendations, a tag recommendation method is proposed which bases on a combined analysis of the relations of objects in a tagging system and the content of resources. An LDA based generative tagging system model TSM/Forc that models object relation and resource content in a combined way is introduced, together with a probabilistic based tag recommendation method and a Gibbs sampling based model parameter estimation approach. Experiment results show that the proposed method could provide more accurate recommendations than the latest methods.

Abstract:Service discovery is a critical stage of the development for Internet-scale software produced through service composition. Presently, development efficiency of composite service is confined by a low degree of automation and accuracy of service discovery. This paper propose the AutoDisc (automatic service discovery framework based on business process similarity) schema to improve development efficiency through two aspects. One is to improve the efficiency of discovery by automatic recommendation. The other is to improve the accuracy of service discovery by combining the structural and behavioral factors of services. Through the proposed approach, this paper automatically models the requirements of service discovery and recommends the most appropriate composite services to developers. Finally, the paper illustrates the effectiveness of AutoDisc with a set of experimental evaluations which show that AutoDisc can increase the development efficiency by 75.5% in the evaluating context.

Abstract:Software defect is an important indicator for measuring the adequacy of software testing. In order to improve the reliability and robustness of Web service composition based BPEL, this paper proposes a defect detecting method which combines the dead path into a path sensitive analysis. Dead path is a special semantic of BPEL, which has no execution information, but can connect two executed path segments. Using the abstract value of variable and its interval arithmetic, this method can identify an unreachable path and dead path, and also merge the conditions of property state at join points. A case study about uninitialized variable detecting which is related to dead path and executing path is given throughout the analysis, and verification is implemented to illustrate the effectiveness of this approach.

Abstract:Service-Oriented transaction processing is a key technology to ensure the correctness of interaction and collaboration among business processes. For cross-organizational multi-business processes, an approach of modeling and verification of multi-business transactions is proposed in this paper. In the modeling approach, an extended Pi-calculus was proposed to describe business transactions coordination via introducing transaction semantics based on the connection between the process interactions and transaction membrane activities. On the other hand, the model checker is employed for checking whether or not the multi-business transactions satisfy the given properties by equal value transformation of the finite state automaton. Finally, the experimental results have demonstrated that it is an important means of ensuring correctness during the design and implementation of multi-business processes.

Abstract:Dirty data brings new challenges for data management. Current methods of dirty data management are mainly data cleaning. Such methods have limitations when dealing with in applications. In some systems, dirty data has to be tolerated. Therefore, the management of databases with dirty data becomes an important issue. The crucial problem is to obtain query result with a clean degree satisfying clean requirement of applications from databases with dirty data. From the aspect of dirty data management, a data model for dirty databases is presented in this paper. This paper proposes the representation of dirty data, data operators for dirty data and the computation method of clean degree of tuples with support of data operation. The equivalent transformation rules for query expressions on dirty data and the preliminary implementation of the data model are also discussed in this paper.

Abstract:This paper studies the problem of computing q-skylines against probabilistic data streams. Compared with the existing methods, which only support the sliding window model, this method can support the more general n-of-N data stream model. This method of transforming q-skyline queries is used for the stabbing queries on an interval tree to support n-of-N model. The paper proposes an algorithm, named PnNM, to maintain the data structures, which is needed for supporting n-of-N model. The PnNM algorithm can efficiently handle the update of the candidate set of uncertain data objects and the updates of the intervals. An algorithm, named PnNCont, is also proposed to handle continuous q-skyline queries against n-of-N model. The theoretical analyses and extensive experiments demonstrate that this algorithms can be very efficient in handing q-skyline queries against probabilistic data streams under n-of-N model.

Abstract:As a promising technology for monitoring and tracing the vehicle flows and human activities, radio frequency identification (RFID) has received much attention in database community. k-nearest neighbor (k-NN) query over RFID monitored objects is one of the most important spatio-temporal queries used to support valuable information analysis. Different from the constraint-free space and constraint-based space, however, RFID monitoring scenario is usually merged into a semi-constraint space, which desires new data storage and distance evaluation strategies. Furthermore, the uncertainty of the monitored object locations challenges the query semantics and processing methods. In this paper, the concept of semi-constraint space is proposed, and the RFID-based semi-constraint space model is analyzed. Based on the semi-constraint space, three models and algorithms are proposed to estimate the probable k-NN results given a dynamic query point. Some special indexing techniques are adopted to speed the query. The experiment evaluates the efficiency and accuracy of the proposed algorithms and proves the effectiveness of relative methods.

Abstract:A novel containment scheme called DCLS is proposed to effectively process updates in dynamic XML data. DCLS generalizes the static containment scheme from integer order to vector order and thus completely avoids re-labeling when XML data updating. Moreover, DCLS is compact and efficient regardless of whether the documents are updated or not. On the one hand, DCLS uses integer-based static containment scheme for initial labeling, which yields compact size and excellent query efficiency for static documents. On the other hand, DCLS takes the integer as special vector, which not only deals with the case of document updating, but also achieves high query performance. Most importantly, DCLS can effectively avoid the rapid increase of labeling size for the case of skewed insertions. Experimental results confirm the benefits of this approach compared to previous dynamic containment schemes.

Abstract:The relationships between description logics and object-oriented data models are analyzed, and the paper aims at investigating the representation and reasoning of fuzzy object-oriented data (FOOD) models with description logics. The FOOD models are investigated, and the formal definition and semantics of FOOD models are proposed first. Then, aiming at the characteristics and reasoning requirement of FOOD models, the fuzzy description logic f-ALCIQ is recalled. In particular, the considers the FOOD model and the corresponding database instances simultaneously, and translate them into f-ALCIQ knowledge base at both terminological (TBox) and assertional (ABox) levels, respectively. Furthermore, based on the translated f-ALCIQ knowledge bases, the reasoning tasks of FOOD models (e.g., consistency, subsumption, and redundancy) may be reasoned through the reasoning mechanism of f-ALCIQ. Finally, a fuzzy description logic reasonerd based on f-ALCIQ called FRsQ is designed and implemented, so as the reasoning problems above may be reasoned automatically.

Abstract:To tackle control channel saturation and triple hidden terminal problems, this paper proposes RIM, a receiver-initiated multi-channel MAC protocol with duty cycling for WSNs. By adopting a receiver-initiated transmission scheme and probability-based random channel selection, RIM effectively alleviates, if not completely eliminates, control channel saturation and triple hidden terminal problems. In addition, RIM exploits a simple but reliable asynchronous broadcast scheme to solve the problem of broadcast data loss with reliable broadcast-intensive applications. More importantly, RIM is fully distributed with no requirements of time synchronization or multi-radio. Therefore, RIM is very easily implemented in resource-constrained sensor nodes. Via the theoretical analysis, the optimal duty cycle are obtained, respectively. The simulation and real testbed experimental results show that RIM achieves significant improvement in energy efficiency with increasing benefit when the number of channels and traffic loads increase, while maintaining higher throughput. Moreover, RIM exhibits a prominent ability to enhance its broadcast reliability.

Abstract:This paper proposes an efficient event delivery algorithm called distributed group mobility adaptive event delivery (GMED) for delay tolerant mobile sensor networks (DTMSN). GMED is designed to establish a group-based event delivery model by effectively finding and utilizing the groups generated by moving sensor nodes which then lead an improved performance: On one hand, Inter-Group delivery will be achieved by multi-replica delivery based on its delivery probability to the sink. On the other hand, Intra-Group delivery will be performed by single-replica delivery through established transmission paths because each node have stable neighbor sets inside group. Meanwhile, delivery prioritizing will be based on event priority in the queue. Furthermore, a redundant replica control mechanism is also introduced to optimize replica management and network overload. Simulation results have shown that GMED not only achieves a relatively long network lifetime, but also has a higher message delivery ratio at lower transmission overhead and delay than other DTMSN data delivering approaches.

Abstract:In P2P (peer-to-peer) streaming systems, server bandwidth consumption can be reduced by enhancing utilization ratio of nodes’ (users’) output (uplink) bandwidth capacity. With the ability of achieving maximum throughput of multicast, network coding has the potential to contribute to the enhancement. This article applies random linear network coding (RLNC) to P2P streaming system, and modeled transmission of P2P streaming. Greedy, rarest-first and random streaming algorithms are studied comparatively through streaming algorithm optimizations based on the framework of transmission model. Optimization results indicate that the random streaming algorithm that fetches data packets evenly and equally can utilize nodes’ output bandwidth more efficiently, which can reduce operating costs of service provider. Finally, by analyzing solutions of optimization model, guidelines are proposed as principles of streaming algorithm design for real P2P streaming systems.

Abstract:Network size is the fundamental information of the distributed applications. Network size estimation methods must feature both high accuracy and adequate robustness in order to adapt to a large environment with a high node churn. Considering the fact that the existing network size estimation methods mainly focus on single optimization objective and fail to ensure accuracy and robustness simultaneously, a network size estimation method based semantic attraction—SEBSA is proposed in this paper. As the semantic information in SEBSA, hash values are hashed in real intervals by the peers’ identifies. The peers with adjacent hash values in SEBSA periodically exchange hash neighbors to attract the most adjacent peers in a hash space quickly. Meanwhile, every peer computes the average spacing among hash values of the hash neighbors to estimate network size. Theoretic analysis and experimental results reveal that compared with existing size estimation methods, SEBSA can provide accurate size estimation information quickly even in continually fluctuating network environment.

Abstract:The Chinese wall model combines discretionary and mandatory aspects of access control. Hence it is widely used in commercial environments to prevent information flows from competing companies with conflicting of interests to the same consultant. However, the model gives strong constraints on both reads and writes, so it is too restrictive to be employed in a practical system. Especially for data leakage prevention (DLP), the applications not play to its advantages. This paper reconsiders the conflict of interest from the perspective of the data object and put forward the concept of aggressive conflict of interest relation. The new relation extends the constraints on two-way information flow to that of one-way flows. Based on this, the paper presents an aggressive Chinese wall model (ACWM) for initiative data leakage prevention and gives the formal description of the model as well as the related proof of the theorem. The final analysis shows that, ACWM achieves the same security goal as traditional Chinese wall models, and also provides more flexible constraints which are efficient for DLP.

Abstract:To solve problem that cannot be coded, which is inherent in the linear broadcast and linear dispersion, this paper proposes a new type of linear network code—the strict linear dispersion. A construction algorithm is proposed and it proves that the demanded finite field size is not higher than that of linear dispersion. Moreover, some special transition matrices are defined and the transition feasibility from linear dispersion to strict linear dispersion is proved. If combined with a special packetization strategy, the strict linear dispersion can present advantages over linear dispersion when applied in heterogeneous networks. It can also realize multi-rate transmission with a single network code session and provide convenience to the construction of network code on the extended network.

Abstract:Code obfuscation is currently one of the most viable methods for preventing reverse engineering attacks. Many kinds of code obfuscation transforms are widely used in software protection. However, there are still no sufficient theories to evaluate the effectiveness of obfuscation transform. In fact, few measurements are available that provide information about the capability of obfuscation to reduce attackers’ efficiency, and few existing theories, which draws upon complexity metrics from software engineering, are convincing. This paper uses a different way to evaluate the difficulty that attackers have in understanding and modifying obfuscated software through static analysis, dynamic debugging of reverse engineering, and then to abstract some metrics to quantify to what extent that code obfuscation is able to make attacks more difficult to be performed.

Abstract:The existing performance evaluation methods of worm attack strategies (defense strategies) are not considered defense strategies (attack strategies) change’s influence on attack strategies (defense strategies) and performance evaluation of defense strategies are ignoring the implementation cost. In view of this situation, a performance evaluation model based on static Bayesian game (PEM-SBG) is proposed, and the performance evaluation methods of worm attack and defense mechanisms are presented. The performance evaluation method of defense mechanisms is based on gray multiple attributes theory and considers several evaluation metrics about cost and utility, so the evaluation process is much more comprehensive. Finally, the paper uses simulation tools SSFNet to implement simulation experiments under different attack and defense scenarios and validate the method.

Abstract:The Ethernet passive optical networks (EPON) are high-speed solutions to the bottleneck problem of the broadband access network. To provide efficient and fair utilization of the EPON upstream bandwidth and support QoS requirements of different traffic classes, a dynamic bandwidth allocation algorithm based on gate threshold is proposed. The algorithm decides the data-receiving rate of the ONU (optical network unit), according to the ONU data-sending response rate and the gate threshold. It then, implements three methods to adapt and adjust the gate threshold, and analyzes these methods’ characteristic. Simulation experiments show the algorithm can decrease average packet delay and increase network throughput.