5687277
A self-adaptive scheduling algorithm of on-demand broadcasts
In mobile wireless systems data on air can be accessed by a large number of mobile users. Many of these applications such as wireless internets and traffic information systems are pull-based, that is, they respond to on-demand user requests. In this paper, we study the scheduling problems of on-demand broadcast environments. Traditionally, the response time of the requests has been used as a performance measure. In this paper we consider the performance as the average cost of request composed of three kinds of costs—access time cost, tuning time cost, and cost of handling failure request. Our main contribution is a self-adaptive scheduling algorithm named LDFC, which computes the delay cost of data item as the priority for broadcast. It performs well compared with some previous algorithms in this context.
1921065
Partitioning loops with variable dependence distances
A new technique to parallelize loops with variable distance vectors is presented. The method extends previous methods in two ways. First, the present method makes it possible for array subscripts to be any linear combination of all loop indices. The solutions to the linear dependence equations established from such array subscripts are characterized by a pseudo distance matrix (PDM). Second, it allows us to exploit loop parallelism from the PDM by applying unimodular and partitioning transformations that preserve the lexicographical order of the dependent iterations. The algorithms to derive the PDM, to find a suitable loop transformation and to generate parallel code are described, showing that it is possible to parallelize a wider range of loops automatically.
9459993
From goals to aspects: discovering aspects from requirements goal models
Aspect-oriented programming (AOP) has been attracting much attention in the software engineering community by advocating that programs should be structured according to programmer concerns, such as "efficient use of memory". However, like other programming paradigms in their early days, AOP hasn't addressed yet earlier phases of software development. In particular, it is still an open question how one identifies aspects early on in the software development process. This work proposes an answer to this question. Specifically, we show that aspects can be discovered during goal-oriented requirements analysis. Our proposal includes a systematic process for discovering aspects from relationships between functional and nonfunctional goals. We illustrate the proposed process with a case study adapted from the literature.
1353091
A Lightweight Approach to Semantic Web Service Synthesis
Web service technologies are becoming a new paradigm for distributed computing. With increasing number of web services available on the internet, there is an urgent need for information brokers that can autonomously integrate web services on behalf of a user. To this end, we propose web service specification, which defines what the service is but not how the service is implemented, and service synthesizer, which can dynamically synthesize the implementation of the specification from existing web services over the web.
2820577
Localizing XML Documents through XSLT
Existing efforts on XML internationalization and localization have been focusing on the contents of XML documents instead of on the meta presentations such as tags and attributes. Although XML standard allows the use of unicode throughout a document including the meta level presentations, most tags and attributes of XML documents are still defined in English, which makes it difficult for native people to use. This paper presents a pure XSLT stylesheet to completely translate and localize XML documents into different natural languages. Furthermore, we also describe how this technique can be applied to translation problems in programming (e.g. C and Java) or documentation (e.g. LaTeX) languages when the program or the document can be converted to and from XML documents.
11507388
JPT: A Java Parallelization Tool
PVM is a succesfull programming environment for distributed computing in the languages C and Fortran. Recently several implementations of PVM for Java have been added, making PVM programming accessible to the Java community. 
 
With PVM for Java however, the user still needs to partition the problem, calculate the data partitioning and program the message passing and synchronization. In this paper, JPT is introduced, a parallelization tool which generates PVM code from a serial Java program. JPT automatically detects parallel loops and generates master and slave PVM programs.
45980845
Optimal adaptive bandwidth monitoring for QoS based retrieval
Network aware multimedia delivery applications guarantee QoS parameters like media object transmission time limit by actively monitoring the available bandwidth of the network and adapting the object to a target size that can be transmitted within a given time limit. A critical problem is how to obtain an accurate enough estimation of available bandwidth while not wasting too much time in bandwidth testing. We present an algorithm to determine the optimal amount of bandwidth testing, given a probabilistic confidence level for network-aware multimedia retrieval. Our implementation and experiments show that the algorithm finds out the optimal amount of bandwidth testing effectively with minimum computation overhead.
53223698
Validating the result of a Quantified Boolean Formula (QBF) solver: theory and practice
2412157
Optimal adaptive bandwidth monitoring for QoS based retrieval
Network aware multimedia delivery applications are a class of applications that provide certain level of quality of service (QoS) guarantees to end users while not assuming underlying network resource reservations. These applications guarantee QoS parameters like media object transmission time limit by actively monitoring the available bandwidth of the network and adapting the object to a target size that can be transmitted within a given time limit. A critical problem is how to obtain an accurate enough estimation of available bandwidth while not wasting too much time in bandwidth testing. In this paper, we present an algorithm to determine optimal amount of bandwidth testing given a probabilistic confidence level for network-aware multimedia object retrieval applications. The model treats the bandwidth testing as sampling from an actual bandwidth population. It uses statistical estimation method to quantify the benefit of each new bandwidth-testing sample, which is used to determine the optimal amount of bandwidth testing by balancing the benefit with the cost of each sample. Our implementation and experiments shows the algorithm determines the optimal amount of bandwidth testing effectively with minimum computation overhead.
12790826
SICTA: a 0.693 contention tree algorithm using successive interference cancellation
Contention tree algorithms have provable stability properties, and are known to achieve stable throughput as high as 0.487 for the infinite population Poisson model. A common feature in all these random access protocols is that collided packets at the receive-node are always discarded. In this paper, we derive a novel tree algorithm (TA) that we naturally term SICTA because it relies on successive interference cancellation to resolve collided packets. Performance metrics including throughput and delay are analyzed to establish that SICTA outperforms existing contention tree algorithms reaching 0.693 in stable throughput.
1542177
Out-of-core tensor approximation of multi-dimensional matrices of visual data
Tensor approximation is necessary to obtain compact multilinear models for multi-dimensional visual datasets. Traditionally, each multi-dimensional data item is represented as a vector. Such a scheme flattens the data and partially destroys the internal structures established throughout the multiple dimensions. In this paper, we retain the original dimensionality of the data items to more effectively exploit existing spatial redundancy and allow more efficient computation. Since the size of visual datasets can easily exceed the memory capacity of a single machine, we also present an out-of-core algorithm for higher-order tensor approximation. The basic idea is to partition a tensor into smaller blocks and perform tensor-related operations blockwise. We have successfully applied our techniques to three graphics-related data-driven models, including 6D bidirectional texture functions, 7D dynamic BTFs and 4D volume simulation sequences. Experimental results indicate that our techniques can not only process out-of-core data, but also achieve higher compression ratios and quality than previous methods.