476. Distributional Features for Text Categorization.

Abstract :-

Text categorization is the task of assigning predefined categories to natural language text. With the widely used ‘bag of words’ representation, previous researches usually assign a word with values such that whether this word appears in the document concerned or how frequently this word appears. Although these values are useful for text categorization, they have not fully expressed the abundant information contained in the document. This paper explores the effect of other types of values, which express the distribution of a word in the document. These novel values assigned to a word are called distributional features, which include the compactness of the appearances of the word and the position of the first appearance of the word. The proposed distributional features are exploited by a tfidf style equation and different features are combined using ensemble learning techniques. Experiments show that the distributional features are useful for text categorization. In contrast to using the traditional term frequency values solely, including the distributional features requires only a little additional cost, while the categorization performance can be significantly improved. Further analysis shows that the distributional features are especially useful when documents are long and the writing style is casual.

477.A Survey of Uncertain Data Algorithms and Applications.

Abstract :-

In recent years, a number of indirect data collection methodologies have led to the proliferation of uncertain data. Such databases are much more complex because of the additional challenges of representing the probabilistic information. In this paper, we provide a survey of uncertain data mining and management applications. We will explore the various models utilized for uncertain data representation. In the field of uncertain data management, we will examine traditional database management methods such as join processing, query processing, selectivity estimation, OLAP queries, and indexing. In the field of uncertain data mining, we will examine traditional mining problems such as frequent pattern mining, outlier detection, classification, and clustering. We discuss different methodologies to process and mine uncertain data in a variety of forms..

478. Provably Secure Steganography.

Abstract :-

Steganography is the problem of hiding secret messages in “innocent-looking” public communication so that the presence of the secret messages cannot be detected. This paper introduces a cryptographic formalization of steganographic security in terms of computational indistinguishability from a channel, an indexed family of probability distributions on cover messages. We use cryptographic and complexity-theoretic proof techniques to show that the existence of one-way functions and the ability to sample from the channel are necessary conditions for secure Steganography. We then construct a steganographic protocol, based on rejection sampling from the channel that is provably secure and has nearly optimal bandwidth under these conditions. This is the first known example of a general provably secure steganographic protocol. We also give the first formalization of “robust” Steganography, where an adversary attempts to remove any hidden messages without unduly disrupting the cover channel. We give a necessary condition on the amount of disruption the adversary is allowed in terms of a worst case measure of mutual information. We give a construction that is provably secure and computationally efficient and has nearly optimal bandwidth, assuming repeatable access to the channel distribution.

479. Efficient Software-Based Encoding and Decoding of BCH Codes.

Abstract :-

Error correction software for Bose-Chaudhuri-Hochquenghem (BCH) codes is optimized for general purpose processors that do not equip hardware for Galois field arithmetic. The developed software applies parallelization with a table lookup method to reduce the number of iterations, and maximum parallelization under a cache size limitation is sought for a high throughput implementation. Since this method minimizes the number of lookup tables for encoding and decoding processes, a large parallel factor can be chosen for a given cache size.The naive word length of a general purpose CPU is used as a whole by employing the developed mask elimination method. The tradeoff of the algorithm complexity and the regularity is examined for several syndrome generation methods, which leads to a simple error detection scheme that reuses the encoder and a simplified syndrome generation method requiring only a small number of Galois field multiplications. The parallel factor for Chien search is increased much by transforming the error locator polynomial so that it contains symmetric exponents of positive and negative signs. The experimental results demonstrate that the developed software cannot only provide sufficient throughput for real-time error correction of NAND flash memory in embedded systems but also enhance the reliability of file systems in general purpose computers.

479. Collusive Piracy Prevention in P2P Content Delivery Networks.

Abstract :-

Collusive piracy is the main source of intellectual property violations within the boundary of a P2P network. Paid clients (colluders) may illegally share copyrighted content files with unpaid clients (pirates). Such online piracy has hindered the use of open P2P networks for commercial content delivery. We propose a proactive content poisoning scheme to stop colluders and pirates from alleged copyright infringements in P2P file sharing. The basic idea is to detect pirates timely with identity-based signatures and time stamped tokens. The scheme stops collusive piracy without hurting legitimate P2P clients by targeting poisoning on detected violators, exclusively. We developed a new peer authorization protocol (PAP) to distinguish pirates from legitimate clients. Detected pirates will receive poisoned chunks in their repeated attempts. Pirates are thus severely penalized with no chance to download successfully in tolerable time. Based on simulation results, we find 99.9 percent prevention rate in Gnutella, KaZaA, and Freenet. We achieved 85- 98 percent prevention rate on eMule, eDonkey, Morpheus, etc. The scheme is shown less effective in protecting some poison-resilient networks like BitTorrent and Azureus. Our work opens up the low-cost P2P technology for copyrighted content delivery. The advantage lies mainly in minimum delivery cost, higher content availability, and copyright compliance in exploring P2P network resources.

 

480. A High-Speed Compressor for Double-Precision Floating-Point Data.

Abstract :-

Many scientific programs exchange large quantities of double-precision data between processing nodes and with mass storage devices. Data compression can reduce the number of bytes that need to be transferred and stored. However, data compression is only likely to be employed in high-end computing environments if it does not impede the throughput. This paper describes and evaluates FPC, a fast lossless compression algorithm for linear streams of 64-bit floating-point data. FPC works well on hard-to-compress scientific data sets and meets the throughput demands of high-performance systems. A comparison with five lossless compression schemes, BZIP2, DFCM, FSD, GZIP, and PLMI, on 4 architectures and 13 data sets shows that FPC compresses and decompresses one to two orders of magnitude faster than the other algorithms at the same geometric-mean compression ratio. Moreover, FPC provides a guaranteed throughput as long as the prediction tables fit into the L1 data cache. For example, on a 1.6-GHz Itanium 2 server, the throughput is 670 Mbytes/s regardless of what data are being compressed.

481.Progressive Parametric Query Optimization.

Abstract :-

Commercial applications usually rely on precompiled parameterized procedures to interact with a database. Unfortunately, executing a procedure with a set of parameters different from those used at compilation time may be arbitrarily suboptimal. Parametric query optimization (PQO) attempts to solve this problem by exhaustively determining the optimal plans at each point of the parameter space at compile time. However, PQO is likely not cost-effective if the query is executed infrequently or if it is executed with values only within a subset of the parameter space. In this paper, we propose instead to progressively explore the parameter space and build a parametric plan during several executions of the same query. We introduce algorithms that, as parametric plans are populated, are able to frequently bypass the optimizer but still execute optimal or near-optimal plans.

482. Identification of Move Method Refactoring Opportunities.

Abstract :-

Placement of attributes/methods within classes in an object-oriented system is usually guided by conceptual criteria and aided by appropriate metrics. Moving state and behavior between classes can help reduce coupling and increase cohesion, but it is nontrivial to identify where such refactorings should be applied. In this paper, we propose a methodology for the identification of Move
Method refactoring opportunities that constitute a way for solving many common Feature Envy bad smells. An algorithm that employs the notion of distance between system entities attributes/methods) and classes extracts a list of behavior-preserving refactorings based on the examination of a set of preconditions. In practice, a software system may exhibit such problems in many different places. Therefore, our approach measures the effect of all refactoring suggestions based on a novel Entity Placement metric that quantifies how well entities have been placed in system classes. The proposed methodology can be regarded as a semi-automatic approach since the designer will eventually decide whether a suggested refactoring should be applied or not based on conceptual or other design quality criteria. The evaluation of the proposed approach has been performed considering qualitative, metric, conceptual, and efficiency aspects of the suggested refactorings in a number of open-source projects.
.

483. Replacing Associative Load Queues A Timing-Centric Approach.

Abstract :-

One of the main challenges of modern processor design is the implementation of a scalable and efficient mechanism to detect memory access order violations as a result of out-of-order execution. Traditional age-ordered associative load queues are complex, inefficient, and power hungry. In this paper, we introduce two new dependence checking schemes with different design tradeoffs, but both explicitly rely on timing information as a primary instrument to rule out dependence violation. Our timing-centric designs operate at a fraction of the energy cost of an associative LQ and achieve the same functionality with an insignificant performance impact on average. Studies with parallel benchmarks also show that they are equally effective and efficient in a chip-multiprocessor environment.

484. Delay-Constrained Multicast Routing Using the Noisy Chaotic Neural Networks.

Abstract :-

We present a method to compute the delay-constrained multicast routing tree by employing chaotic neural networks. The experimental result shows that the noisy chaotic neural network (NCNN) provides an optimal solution more often compared to the transiently chaotic neural network (TCNN) and the Hopfield neural network (HNN). Furthermore, compared with the bounded shortest multicast algorithm (BSMA), the NCNN is able to find multicast trees with lower cost..

 

485. A Flexible Software-Based Framework for Online Detection of Hardware Defects.

Abstract :-

This work proposes a new, software-based, defect detection and diagnosis technique. We introduce a novel set of instructions, called Access-Control Extensions (ACE), that can access and control the microprocessor’s internal state. Special firmware periodically suspends microprocessor execution and uses the ACE instructions to run directed tests on the hardware. When a hardware defect is present, these tests can diagnose and locate it, and then activate system repair through resource reconfiguration. The software nature of our framework makes it flexible: testing techniques can be modified/upgraded in the field to trade-off performance with reliability without requiring any change to the hardware. We describe and evaluate different execution models for using the ACE framework. We also describe how the proposed ACE framework can be extended and utilized to improve the quality of post-silicon debugging and manufacturing testing of modern processors. We evaluated our technique on a commercial chipmultiprocessor based on Sun’s Niagara and found that it can provide very high coverage, with 99.22 percent of all silicon defects detected. Moreover, our results show that the average performance overhead of software-based testing is only 5.5 percent. Based on
a detailed register transfer level (RTL) implementation of our technique, we find its area and power consumption overheads to be modest, with a 5.8 percent increase in total chip area and a 4 percent increase in the chip’s overall power consumption
.

486. Atomicity Analysis of Service Composition across Organizations.

Abstract :-

Atomicity is a highly desirable property for achieving application consistency in service compositions. To achieve atomicity, a service composition should satisfy the atomicity sphere, a structural criterion for the backend processes of involved services. Existing analysis techniques for the atomicity sphere generally assume complete knowledge of all involved backend processes. Such an assumption is invalid when some service providers do not release all details of their backend processes to service consumers outside
the organizations. To address this problem, we propose a process algebraic framework to publish atomicity-equivalent public views from the backend processes. These public views extract relevant task properties and reveal only partial process details that service providers need to expose. Our framework enables the analysis of the atomicity sphere for service compositions using these public views instead of their backend processes. This allows service consumers to choose suitable services such that their composition satisfies the atomicity sphere without disclosing the details of their backend processes. Based on the theoretical result, we present
algorithms to construct atomicity-equivalent public views and to analyze the atomicity sphere for a service composition. Two case studies from the supply chain and insurance domains are given to evaluate our proposal and demonstrate the applicability of our approach.

489. Complexities of Graph-Based Representations for Elementary Functions.

Abstract :-

This paper analyzes complexities of decision diagrams for elementary functions such as polynomial, trigonometric,logarithmic, square root, and reciprocal functions. These real functions are converted into integer-valued functions by using fixed-point representation. This paper presents the numbers of nodes in decision diagrams representing the integer-valued functions. First, complexities of decision diagrams for polynomial functions are analyzed, since elementary functions can be approximated by polynomial functions. A theoretical analysis shows that binary moment diagrams (BMDs) have low complexity for polynomial functions. Second, this paper analyzes complexity of edge-valued binary decision diagrams (EVBDDs) for monotone functions, since many common elementary functions are monotone. It introduces a new class of integer functions, Mp-monotone increasing function, and derives an upper bound on the number of nodes in an EVBDD for the Mp-monotone increasing function. A theoretical analysis shows that EVBDDs have low complexity for Mp-monotone increasing functions. This paper also presents the exact number of nodes in the
smallest EVBDD for the n-bit multiplier function, and a variable order for the smallest EVBDD.

490. Constructing Minimum Connected Dominating Sets with Bounded Diameters in Wireless Networks.

Abstract :-

Connected Dominating Sets (CDSs) can serve as virtual backbones for wireless networks. A smaller virtual backbone incurs less maintenance overhead. Unfortunately, computing a minimum size CDS is NP-hard, and thus most researchers in this area concentrate on how to construct smaller CDSs. However, people neglected other important metrics of network, such as diameter and average hop distances between two communication parties. In this paper, we investigate the problem of constructing quality CDS in terms of size, diameter, and Average Backbone Path Length (ABPL). We present two centralized algorithms having constant performance ratios for its size and diameter of the constructed CDS. Especially, the size of CDS computed by the second algorithm is no more than 6.906 times of its optimal solution. Furthermore, we give its distributed version, which not only can be implemented in real situation easily but also considers energy to extend network lifetime. In our simulation, we show that in average the distributed algorithm not only generates a CDS with smaller diameter and ABPL than related work but also suppresses its size well. We also show that it is more energy efficient than others in prolonging network lifetime.

491. Content Outsourcing via Generalized Communities.

Abstract :-

Content distribution networks (CDNs) balance costs and quality in services related to content delivery. Devising an efficient content outsourcing policy is crucial since, based on such policies, CDN providers can provide client-tailored content, improve performance, and result in significant economical gains. Earlier content outsourcing approaches may often prove ineffective since they drive prefetching decisions by assuming knowledge of content popularity statistics, which are not always available and are extremely
volatile. This work addresses this issue, by proposing a novel self-adaptive technique under a CDN framework on which outsourced content is identified with no a priori knowledge of (earlier) request statistics. This is employed by using a structure-based approach identifying coherent clusters of “correlated” Web server content objects, the so-called Web page communities. These communities are the core outsourcing unit, and in this paper, a detailed simulation experimentation has shown that the proposed technique is robust and
effective in reducing user-perceived latency as compared with competing approaches, i.e., two communities-based approaches, Web caching, and non-CDN.

492. Difficulty-Aware Hybrid Search in P2P Networks.

Abstract :-

By combining an unstructured protocol with a DHT-based global index, hybrid peer-to-peer (P2P) improves search efficiency in terms of query recall and response time. The major challenge in hybrid search is how to estimate the number of peers that can answer a given query. Existing approaches assume that such a number can be directly obtained by computing item popularity. In this work, we show that such an assumption is not always valid, and previous designs cannot distinguish whether items related to a query are distributed in many peers or are in a few peers. To address this issue, we propose QRank, a difficulty-aware hybrid search, which ranks queries by weighting keywords based on term frequency. Using rank values, QRank selects proper search strategies for queries. We conduct comprehensive trace-driven simulations to evaluate this design. Results show that QRank significantly improves the search quality as well as reducing system traffic cost compared with existing approaches.

493. Flexible Rollback Recovery in Dynamic Heterogeneous Grid Computing.

Abstract :-

Large applications executing on Grid or cluster architectures consisting of hundreds or thousands of computational nodes create problems with respect to reliability. The source of the problems are node failures and the need for dynamic configuration over extensive runtime. This paper presents two fault-tolerance mechanisms called Theft-Induced Checkpointing and Systematic Event Logging. These are transparent protocols capable of overcoming problems associated with both benign faults, i.e., crash faults, and node or subnet volatility. Specifically, the protocols base the state of the execution on a dataflow graph, allowing for efficient recovery in dynamic heterogeneous systems as well as multithreaded applications. By allowing recovery even under different numbers of processors, the approaches are especially suitable for applications with a need for adaptive or reactionary configuration control. The low-cost protocols offer the capability of controlling or bounding the overhead. A formal cost model is presented, followed by an
experimental evaluation. It is shown that the overhead of the protocol is very small, and the maximum work lost by a crashed process is small and bounded.

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