Abstract:Along with the transition of application scenario and the increase of its own complexity, software needs the capability of actively adapting itself to the changes in its environment, which means that it needs to adjust its behavior in response to those changes. The realization of software self-adaptation is closely related to many academic fields such as software monitoring, context-aware computing, decision and control theory, software evolution and maintenance, and etc. It is a great challenge to construct this kind of software systematically in software engineering practice. From the perspective of the construction and implementation of self-adaptive software, this paper reviews the existing research and practices based on the "sensing-decision-execution" basic self-adaptation cycle. This study presents the concept of software self-adaptation and a taxonomy of the characteristics of sensing, decision and execution activities, summary those most focused enabling techniques for constructing adaptive software, analyze a set of typical research projects, and then describe the future research trend in the field of constructing adaptive software.

Abstract:The software product line is one of the most effective strategies for reuse of large-scale software and rapid development of new software products with good quality levels. The variability modeling technique used to describe the commonality and variability of software product families is one of the most important techniques in software product line. Variability modeling plays an important role in the product line domain engineering and product line application engineering. However, it is difficult for modelers and engineers to choose one or more suitable modeling techniques from various variability modeling techniques. A systematic literature review of the variability modeling techniques in software product line reported from 1990s to 2011 is carried out. In this systematic review, the existing variability modeling techniques are analyzed and compared to help engineers and/or researchers to select the most suitable variability modeling techniques. Finally, the research trend of variability modeling technique is given, and the prospects for future research and suggestions for possible extensions are also discussed.

Abstract:Testing is one of the primary methods for Web service quality control. Test automation is necessary to enhance test productivity and quality while reducing test effort. Test data generation is a critical issue of automated testing. The paper proposes a method called interface semantic contract (ISC) for modeling services' exposed functionalities using ontology and rule language. Algorithms are developed to generate input partitions and test data based on ISC. Case studies are exercised to illustrate the proposed approach. The results show that compared with conventional random testing, the proposed approach can enhance test coverage by 50% with the same number of test cases, and reduce test effort by 90% to reach the same test coverage.

Abstract:Studies of static complex networks have brought significant progress in revealing the mechanism for forming and evolving of social networks, information networks, and biological networks. However, many real word networks change with time and this type of networks is the so called dynamic networks. This paper focuses on dynamic networks to study the related pattern mining method and its applications in biological and social networks. First, the study analyzes the topological properties of the dynamic networks. Then we make a comparison and analysis to the algorithms and models for variety of pattern mining in dynamic networks. Specifically, we analyze the dynamics properties of biological and social networks. Based on this property, we study the biological networks related pattern mining problems, such as dynamic function module, pattern evolution and complex diseases associated pattern, the dynamic pattern in social network. Finally, some key problems and challenges in biological and social network are highlighted, as well as the future research directions.

Abstract:Community discovery is an important task in mining complex networks, and has important theoretical and application value in the terrorist organization identification, protein function prediction, public opinion analysis, etc. However, existing metrics used to measure quality of network communities are data dependent and have coupling relations, and the community discovery algorithms based on optimizing just one metric have a lot of limitations. To address the issues, the task to discover network communities is formalized as a multi-objective optimization problem. An algorithm, MOCD-PSO, is used to discover network communities based on multi-objective particle swarm optimization, which constructs objective function with modularity Q, MinMaxCut and silhouette. The experimental results show that the proposed algorithm has good convergence and can find Pareto optimal network communities with relatively well uniform and dispersive distribution. In addition, compared with the classical algorithms based on single objective optimization (GN, GA-Net) and multi-objective optimization (MOGA-Net,SCAH-MOHSA), the proposed algorithm requires no input parameters and can discover the higher-quality community structure in networks.

Abstract:This paper addresses an NP-hard layout optimization problem with a high computational complexity: the two-dimensional rectangle packing area minimization problem (RPAMP), which is a core issue of floorplanning problem in the very-large-scale integration (VLSI) design. First, by dynamically designing the two dimensions of the large rectangular frame, the study reduces the solving of a RPAMP to the solving of a series of two-dimensional rectangle packing decision problems (RPDP). Then, based on a best-fit-degree approach for the RPDP, the designs a least-damage-first algorithm for the RPDP, which further takes the consideration of the current placement's impact on global compaction and of its negative effect on local space's integrity. Next, by combining the method of dynamically designing two dimensions of the rectangular frame, a final dynamic reduction algorithm is proposed for solving the RPAMP. Experiments were on 15 RPAMP instances (including the well-known MCNC instances and GSRC instances). Computational results show that the proposed algorithm refreshed the current best solutions on nine instances. At the same time it also matchs the current best records on two other instances. The obtained average filling rate is 98.50%, which improved the current best results reported in the literature by 0.85%.

Abstract:The automatic domain-specific term extraction is an important task in natural language processing, which can be adoptedin domain-specific ontology construction, vertical search, text classification, class-based language model etc. A Web page contains lots of noises and irrelevantcontents, therefore, extracting domain-specific terms from original pages becomes a challenging task. Different from previous works, which rely on the original text of Web pages, this study focuses on anchor text and query log history of pages. This strategy would avoid the trouble of information extraction from the original Web pageand therefore improves the term extraction performance. In this paper, a novel term extraction algorithmis based onanalysis into Web resource and user behaviors. Different Web resources including body of the page data, anchor text of the page and the information of user query data were employed to extract the domain-specific terms and their performances were compared.The result based on scale of the network datademonstratesthe resources of anchor text and the way user query data can obtain a better effect.

Abstract:On the way forward to real time in the process of particle-filtering-based human hand tracking, one of the main obstacles is to generate a great deal of particles which are derived from high dimensionality of human hand model. Aimed at reducing the particle number, a new particle filtering approach is put forward in this paper. First, the operator's cognitive psychology features in the process of human-computer interaction are analyzed and studied and a general dynamic motion model is constituted. Second, some basic features of the dynamic motion model are studied and mathematically described. Third, a zonetime model of the moving human hand is proposed, and furthermore, the features in time-space of a hand gesture state are discussed. Based upon the abovementioned job, a new concept, microstructure of state variable, is presented, upon which the novel hand gesture tracking algorithm is put forward. Finally, experiments are implemented including some comparison experiments, and the algorithm is also compared with some referenced algorithms. The main contribution is that the study describes and models hand gesture behaviors and connect them with freehand tracking. The experimental results show that just using a small quantity of particles, compared with the referenced algorithms, the algorithm can obtain satisfactory results.

Abstract:A cooperative replica prefetching mechanism is a new replication strategy aiming to reduce the data access latency in grid by the means of replicating implicit high-value files (IHVFs). The key of this new mechanism is the exploration and location of IHVFs. Locating the IHVFs quickly can improve the performance of the mechanism. This paper employs the DHT (distributed hash table) technology to organize grid nodes to quickly locate the file correlation information which is essential for the query of IHVFs. Considering the specific query pattern, a PTree-based storage structure and corresponding query mechanism for file correlation information are proposed to improve the IHVF query efficiency. Simulation results based on real grid workloads have confirmed the effectiveness and high efficiency of the proposed methods.

Abstract:Reducing the network overhead generated during the search is important in the study of unstructured P2P network. Flooding and random walks are simple and easily implemented. However, a large number of redundant messages generated in the search process are the main reason of producing excessive network overhead. An effective limited search mechanism RFSA (restricted forward search algorithm) is proposed. The search path and redundant search path are defined. As the query messages reaching the node are received by introducing the local messages index caching mechanism, the repeat messages forwarding are eliminated. Using the real-time search path information carried in the search process, the neighbor notes that do not appear in the search path are selected to forward the query messages. Theoretically, the number of messages and network overhead generated by the RFSA. In the simulation, comparative analysis of the limited search mechanism and non-limited mechanism flooding and random walk algorithm is done in the network overhead, query hit rate, search coverage rate, and the number of redundant messages, etc. The results show that this method reduces the generation of a great number of redundant messages, and cuts down the network overload.

Abstract:In wireless sensor networks, nodes commonly have limited energy and communication ability. Desiging efficient protocols and algorithms to complete various tasks efficiently with limited resources has become a challenge in wireless sensor networks. Considering the receiver capacity and mixed traffic in wireless sensor networks, this paper investigate the utility fair flow control problem with joint power and receiver capacity constraints. Since conventional dual decomposition algorithms often have drawbacks such as slow convergence, difficult adjustment of stepsize and large communication overhead, this paper proposes an event-triggered distributed algorithm for the flow control problem studied in this paper. Both theoretical analysis and simulation results show that the average broadcast period of sensor nodes when using event triggered distributed algorithm is longer than that of dual decomposition. Compared with the dual decomposition algorithm, this event triggered distributed algorithm reduces the amount of information exchange among nodes, decreases the communication overhead in wireless sensor networks greatly. The simulation results also show that the event triggered distributed algorithm has a much faster convergence than the dual decomposition algorithm and the former has better scalability to the network size. Additionally, compared with the conventional rate fair flow control mechanism, the utility fair flow control model can better cater for the networks scene with a mix of elastic and inelastic traffic.

Abstract:A simple and efficient active statistics counter architecture named DALCA (direct addressing layered counter array) is presented for high speed network traffic analysis and management. The novelty of DALCA is that the counter vector is split up into multiple layers, and all layers except the first one are organized as multi-level hash tables. This makes DALCA efficient in both from the space and time perspective. DALCA has similar space efficiency and significantly higher time efficiency compared with BRICK;the state-of- the-art active statistics counter architecture. The performance of DALCA is evaluated using real world backbone network traffic traces. Simulation results show that the memory bandwidth demand of DALCA is about 1/10 and 1/6 that of BRICK during query and update operations respectively.

Abstract:The accurate packet loss measurement of application traffic has been challenging, since the frequently-used active monitoring approaches that use probe packets cannot capture the packet loss experienced by the traffic of individual user applications. Moreover, measurement and estimation of packet loss characteristics are challenging due to the relatively rare occurrence and typically short duration of packet loss episodes. Because it is often impossible to measure the entire data passing across a network, the most widely used method of measurement works by injecting probe packets. In order to overcome these shortcomings, this paper based on the analysis of MPEG4 video structural features and RTP encapsulation strategy, a novel packet loss probing technique, packet loss measurement based on User_Data (PLBU), is proposed. The PLBU complete packets loss measurement by using User_Data field of MPEG-4 video. This does not affect the normal video playback and dose not need to inject new probing stream, which makes it, less intrusive. NIST Net and Planetlab experiments verify the effectiveness of this method, and show that PLBU estimates packet loss more accurately, and with less measurement overhead than other existing technique such as BADABING.

Abstract:This paper proposes a particle filter based target localization (PFTL) algorithm, and a sampling aware tracking cluster formation (SAC) scheme for organizing the sensor nodes, which maximizes the coverage area of target's trajectory in each cluster. The key idea of PFTL is to represent the possible locations of mobile target with a number of weighted particles, and to estimate the particles for computing the position of the object when the range measurements are available at next sampling time step. The motivation behind PFTL is that if the sink is willing to tolerate a small error, regarding the position of the target, the in-network communication can be greatly decreased, as well as the consumed energy, which is the most precious resource in wireless sensor networks. To balance the computation and communication overhead of network, this study designed a node scheduling scheme SAC, which dynamically clusters the sensors aimed at minimizing the times of tracking data hand-offs, so as to save the energy expenditure. Extensive simulations are conducted to verify the proposed methodologies, and the results reveal that PFTL and SAC not only reduce the localization error, but also efficiently extend the network lifetime.

Abstract:According to the strict demands of timeliness and reliability during military aeronautical communications, and the question of whether propagation delay could not be ignored, a media access control protocol based on Turbo coding, burst technology, asynchronous frequency hopping and priority differentiation (PFH MAC) is proposed. It realizes differential service by providing different queuing strategies and accessing network authority for the high and low priority packets. All of the protocol performance expressions are deduced by Markov model, queuing theory, combination theory and discrete Laplase transformation. The simulation results verify that this theoretical analysis is accurate and the differential service is effective.

Abstract:An optimal allocation approach of servers for improving the performance of P2P networks is proposed in this paper. The approach is to allocate a limited number of servers over the P2P networks to satisfy as many peers as possible, by using a constrained optimization algorithm. In considering that the polar space is more suitable to express length-related constraints, such as those in this approach, a heuristic algorithm based on the polar coordinator mapping is proposed to deal with the optimization problem of the server allocation. Compared with the existing heuristic algorithms that are based on penalty functions, this algorithm can effectively reduce the search space, and the performance is better especially in a high dimensional search space. The experiment results show that our server allocation approach can satisfy more peers' requirement and effectively improve the performance of P2P networks.

Abstract:In traditional cryptographic model, it is assumed that the communication end points and computing environments of a cryptosystem are trusted. But this model becomes increasingly frailer with the development of the attack method. In the white-box attack model, the adversary can get not only access to the same resources as in the traditional cryptographic model but also total visibility of the internal implementation of the cryptosystem and full control over its execution environment, so it has the higher level of secure significance. The white-box SMS4 implementation, which was proposed in 2009, is aimed at protecting SMS4 operated in the white box context against key exposure. In this paper, based on the review of previous research, we propose an efficient attack and explain in detail how to extract the round key embedded in such a white box SMS4 implementation, with worst time complexity 2⁴⁷. As a result, we show that the white-box method is unreliable and provide reference for the secure white-box implementation.