waashk/dblp huggingface dataset:
profit-based on-demand broadcast scheduling of real-time multi-item requests. on-demand broadcast is a widely accepted approach for dynamic and scalable wireless information dissemination systems. with the proliferation of real-time applications, minimizing the deadline miss ratio in scheduling multi-item requests becomes an emergent task in the current architecture. in this paper, we propose a profit-based scheduling algorithm, called pvc, which utilizes two new concepts "profit" of a data item and "opportunity cost" of a request. note that, to the best of our knowledge, it is also the first time to introduce opportunity cost, which is derived from economics, into on-demand scheduling. finally, the simulation results show the great improvement in comparison with traditional algorithms. on average, pvc has more than 5% advantage in terms of deadline miss ratio than the best of others.
proving consistency of vdm models using hol. although consistency of formal models is crucial, consistency proofs should not be a large burden to the user. hence, it is important to have access to efficient proof support which is able to automate a large part of the consistency proofs. we have developed a tool that automatically translates a large subset of vdm and its associated proof obligations, which ensure model consistency, to the theorem prover hol. in addition, powerful tactics have been constructed to discard most of the proof obligations automatically. the application of our approach to four case studies shows that a high degree of automation can be achieved.
a study on interestingness measures for associative classifiers. associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. support and confidence are the de-facto "interestingness measures" used for discovering relevant association rules. the support-confidence framework has also been used in most, if not all, associative classifiers. although support and confidence are appropriate measures for building a strong model in many cases, they are still not the ideal measures and other measures could be better suited. there are many other rule interestingness measures already used in machine learning, data mining and statistics. this work focuses on using 53 different objective measures for associative classification rules. a wide range of uci datasets are used to study the impact of different "inter-estingness measures" on different phases of associative classifiers based on the number of rules generated and the accuracy obtained. the results show that there are interesting-ness measures that can significantly reduce the number of rules for almost all datasets while the accuracy of the model is hardly jeopardized or even improved. however, no single measure can be introduced as an obvious winner.
combining independent model transformations. model transformation is one of the key principles of model driven engineering. many approaches have been proposed to design and realize them. however, for all the approaches, model transformations are considered as single entities that can only be chained if their input and output metamodels are compatible. this approach has the major drawback to focus on the satisfaction of the compliance property when building a transformation chain. in this paper we propose a mechanism for combining independent model transformations which jointly work towards a common objective but do not initially handle compatible metamodels. our proposal is independent of any model transformation approach. it has been validated using gaspard, an environment dedicated to code generation for embedded systems.
software transactional memory for implicitly parallel functional language. during the last decade, software transactional memory (stm) gained wide popularity in many areas of parallel computing. in this paper, we introduce lisp-derived language equipped with automatic parallel execution and mutations based on software transactional memory. the novel idea is that we do not incorporate transactions as a language construct but rather use them as a mean of runtime environment to run each computation in a consistent memory and thus provide correct results. stm enables us to efficiently manage concurrent object updates and resolve collisions. in this paper, we describe a variant of deferred lockless stm mechanism with direct updates that enables us to use mutations with minimal costs.
recomap: an interactive and adaptive map-based recommender. with the growing availability of geo-referenced information on the web, the problem of spatial information overload has attracted interest both in the commercial and academic world. in order to tackle this issue, personalisation techniques can be used to tailor spatial contents based upon user interests. recomap, the system described in this paper, deducts user interests by monitoring user interaction and context to provide personalised spatial recommendations. after an overview of existing recommendation systems within the geospatial domain, the novel approach adopted by recomap to produce such recommendations is described. a case study related to a university campus setting is used to outline an application of this technique. details of the implementation and initial testing of this prototype are provided.
towards interactionflows for smart products. nowadays, the interaction between a product and the user is described using different methods than for product to product communication. this makes it difficult to replace users and products mutually to create really dynamical environments, capable of reducing the amount of interactions, if possible. to advance the design of interactive smart environments, we introduce a concept for describing productinitiated interaction with users and demonstrate, how they can be applied in practice. this allows to combine both, automated procedures and interaction with the user, to a new concept called interactionflows.
uplink scheduling algorithm with dynamic polling management in ieee 802.16 broadband wireless networks. scheduling algorithms is an important component in any communications network to satisfy the qos requirements. in this paper, a new scheduling algorithm for uplink traffic in ieee 802.16 networks is proposed. the proposed algorithm is applied directly to the bandwidth request queues of the base station (bs) and work along with the polling mechanism to control the periodicity of sending polling for the rtps and nrtps services. its evaluation by means of modeling and simulation showed satisfactory results.
publication and discovery of yasa web services. in this paper, we present new algorithms for matching web services described in yasa4wsdl (yasa for short). we have already defined yasa that overcomes some issues missing in wsdl or sawsdl. in this paper, we continue on our contribution and show how yasa web services are matched based on the specificities of yasa descriptions. our matching algorithm consists of three variants based on three different semantic matching degree aggregations. this algorithm was implemented in yasa-m, a new web service matchmaker. yasa-m is evaluated and compared to well known approaches for service matching. experiments show that yasa-m provides better results, in terms of precision, response time, and scalability, than a well known match-maker.
improving automatic music genre classification with hybrid content-based feature vectors. current research on the task of automatic music genre classification has been focusing on new classification approaches based on combining information from other sources than the music signal. the reason for this is that the use of content-based approaches, i.e. using features extracted directly from the audio signal, seems to have reached a glass ceiling. in this work we show that by using different types of content-based features together it is possible to substantially improve the classification accuracy. this is an interesting result as different types of content-based features aim, at a conceptual level, to capture the same type of information. in order to identify which types of content-based features are responsible for the predictive accuracy gain, we also used a feature selection (fs) approach based on a genetic algorithm (ga). the analysis of the results in two databases shows that the use of the ga for fs succeeds in selecting a representative subset without significant loss in accuracy. it also shows that all the different types of content-based features employed are important for the improvement of the accuracy in classifying music genres.
considerations on developing mobile applications based on the capuchin project. the development of applications for mobile devices is becoming increasingly popular, with manufacturers struggling to support different programming environments and embedding libraries on their devices. in this pursuit for a straight-forward development of mobile applications, java micro edition (jme) is a natural solution. although jme has innumerous benefits, it offers limited support for user interface (ui) development. on a different path, adobe's flash lite is tailored to develop rich ui for mobile applications. to bring together the advantages of both jme and flash lite, sony ericsson's capuchin project permits the creation of interactive mobile applications, using flash lite to implement the user interface and jme to implement application core. the use of flash lite and jme in a single application has rised design issues that must be dealt by software engineers, such as performance, maintainability and reusability of both flash lite and jme programming languages. to guide software engineers design mobile applications, this paper presents a development process for interactive mobile applications based on capuchin project. to validate it, a mobile application is developed based on this process, and relevant topics of the process are discussed.
sporadic server revisited. the sporadic server (ss) overcomes the major limitations of other resource reservation fixed priority based techniques, but it also presents some drawbacks, mainly related to an increased scheduling overhead and a not so efficient behavior during overrun situations. in this paper we introduce and prove the effectiveness of an improved ss with reduced overhead and fairer handling of server overrun situations. we also show how this can be efficiently exploited to provide temporal isolation in a multiprocessor platform, adapting already existing schedulability tests.
data generation in model-based testing. in this paper we show how context free grammars extended with limited state information can be used to enhance model-based testing. abstract models can be made more specific using the values generated by these grammars. the approach allows the association of data to the model without changing the model itself. we present two examples to illustrate the applicability of the framework. we also show how this approach is implemented in a real model-based testing tool.
aho-corasick like multiple subtree matching by pushdown automata. a simple yet efficient algorithm to find all occurrences of a set of subtrees in a subject tree is described. the presented algorithm is similar to the well-known aho-corasick string matching method -- instead of a deterministic finite automaton a deterministic pushdown automaton is used as the computation model for reading the subject tree in prefix notation.
network state consistency of virtual machine in live migration. the current virtual machine (vm) live migration research mainly focuses on transferring run-time memory state of vms, but neglects the consistency of the network state while migration. this paper designs an efficient and reliable virtual network (ervin) system, which applies several techniques: central information management distributed data transmission (cidd), layer-two network virtualization, store and replay. it guarantees that the established network connections do not interrupt during migration. the experiments show that ervin is efficient. the degradation time of network performance is only around 400 ms, which can almost be neglected.
haptic manipulation of rational parametric planar cubics using shape constraints. in this paper, we show how to deform a planar rational cubic based on a local interpolation constraint while retaining the qualitative shape of the curve. an impedance-type, parallel haptic device is used to signal changes of the number of inflection points, cusps and loops during the deformation. in this way, the user is provided with an intuitive and natural guidance throughout the curve's shape generation process in cad.
an aspect-oriented framework for operating system evolution. this paper presents an aspect-oriented framework which enables dynamically weaving aspects into operating system in order to adjust its functionalities during system operation. the framework is designed based on the notion of dynamic aspect weaving in aspect-oriented programming (aop) arena, which can achieve modulating, at runtime, the behavior of an existing program by injecting a piece of code (called advice in aop terminology) at selected location (called join point) of the program. it is useful in making program adaptable, especially for non-stopping systems of which, in general, going off-line for maintenance and undertaking system restart is either unacceptable or too expensive. the design of this framework includes a join point model and management functions on aspects. the join point model supports weaving multiple aspects to the same join point and the chained execution of advices of the same type. the management functions provide the creation, deployment, and runtime management of aspects, in addition to sequencing the execution of advices. an example implementation of this framework working on linux operating system is described in this paper, which demonstrates both the feasibility and the effectiveness of this framework.
empirical analysis of database server scalability using an n-tier benchmark with read-intensive workload. the performance evaluation of database servers in n-tier applications is a serious challenge due to requirements such as non-stationary complex workloads and global consistency management when replicating database servers. we conducted an experimental evaluation of database server scalability and bottleneck identification in n-tier applications using the rubbos benchmark. our experiments are comprised of a full scale-out mesh with up to nine database servers and three application servers. additionally, the fourtier system was run in a variety of configurations, including two database management systems (mysql and postgresql), two hardware node types (normal and low-cost), and two database replication techniques (c-jdbc and mysql cluster). in this paper we present the analysis of results generated with a read-intensive interaction pattern (browse-only workload) in the client emulator. these empirical data can be divided into two kinds. first, for a relatively small number of servers, we find simple hardware resource bottlenecks. consequently, system throughput increases with an increasing number of database (and application) servers. second, when sufficient hardware resources are available, non-obvious database related bottlenecks have been found that limit system throughput. while the first kind of bottlenecks shows that there are similarities between database and application/web server scalability, the second kind of bottlenecks shows that database servers have significantly higher sophistication and complexity that require in-depth evaluation and analysis.
mmsrp: multi-wavelength markov-based split reservation protocol for dwdm optical networks. during wavelength reservation in wavelength division multiplexed (wdm) optical networks, often multiple connection requests unknowingly compete for the same wavelength, even when other free wavelengths are available, resulting in a collision. the markov model used in markov based reservation protocol (mbrp), is very effective to reduce such conflicts by intelligently guessing a wavelength in advance. even then a connection request may be blocked because of the vulnerable period between wavelength probing and actual reservation. to minimize the effect of such vulnerability, splitting the probe process to fork out a partial reservation from an intermediate node is an efficient solution. in markov-selection split reservation protocol (msrp), the above two strategies are combined, but only one wavelength is guessed during probing. if the attempt with this single wavelength fails, the connection request is blocked. to take care of this limitation, we propose here a new scheme called multi-wavelength msrp (mmsrp), where a set of wavelengths (instead of one) is selected by markov model and continuously updated for possible future use. in case of failure, during reservation in the backward direction, it retries to reserve the next best wavelength through another splitting at the failure point. thus, mmsrp handles multiple wavelengths sequentially through multiple splitting. simulation results show that the blocking probability in mmsrp decreases considerably (~25% over msrp and ~50% over mbrp in some cases) as the number of wavelengths increases. compared to msrp, though the average setup time is marginally higher in mmsrp, it appears quite promising for delay-tolerant applications, where blocking is very crucial, in dense wdm networks.
matchbox: combined meta-model matching for semi-automatic mapping generation. data integration is a well-known challenge offering a common view on heterogeneous data, e. g. to ensure consistency or tool interoperability. to implement this integration mde proposes to apply model transformations. a model transformation requires meta-model matching, i. e. the task of discovering semantic correspondences between elements. recently, semi-automatic matching has been proposed to support transformation development by mapping generation. however, current meta-model matching approaches concentrate on a fixed non-configurable set of matching algorithms and often miss a thorough evaluation, thus no estimate concerning their quality can be made. we tackle these issues by proposing matchbox, an approach using a configurable combination of matchers in a common framework. thereby, we adapt and extend established schema matching techniques for the purpose of meta-model matching. additionally, we present a benchmark for meta-model matching consisting of 23 real-world model transformations and mappings. this benchmark is used to comprehensively evaluate matchbox. the results obtained lead to conclusions regarding our approach and the effectiveness of meta-model matching.
summarizing observational client-side data to reveal web usage patterns. client-side event logs may reveal patterns of usage of web pages. nevertheless, extracting useful and novel information from this voluminous data set is a challenge for evaluation tools, since a few minutes simple task may result in a sequence of hundreds of events. this work contributes with a technique to process these logs and build a web page's usage graph summarizing statistical information of the web page usage concerning one or more sessions. this graph reveals patterns of real usage data, which human-computer interaction specialists may find useful for inspecting accessibility and usability issues. moreover, web usage miners can reuse the usage graph to apply other techniques to discover other patterns or rules.
towards quality-aware development and evolution of enterprise information systems. information systems have been used to support business processes for a long time. consequently, there has been an ongoing trend towards connecting and integrating the isolated it solutions of enterprises into coherent systems in order to support the seamless execution of business processes electronically. due to the often business critical nature of the processes such systems need to adhere to service level agreements that guarantee quality aspects such as a specific throughput or availability for a given process. however, a key weakness of existing development approaches for information systems is that they mostly focus on functional aspects of system development and lack an integrated view between different stakeholders and views in development, e.g. between business process management and software architecture. in this paper we introduce a novel approach for universal und uniform modeling of non-functional system properties that bridges the four areas of business and use case modeling as well as architecture and component design. by means of an example process, we first identify the key weaknesses of existing development methodologies and then derive the challenges for an improved approach. after that we describe the central aspects of our envisaged composition approach for non-functional requirements and how it might be supported by a novel breed of case tools in the future.
on the incoherencies in web browser access control policies. web browsers' access control policies have evolved piecemeal in an ad-hoc fashion with the introduction of new browser features. this has resulted in numerous incoherencies. in this paper, we analyze three major access control flaws in today's browsers: (1) principal labeling is different for different resources, raising problems when resources interplay, (2) runtime changes to principal identities are handled inconsistently, and (3)browsers mismanage resources belonging to the user principal. we show that such mishandling of principals leads to many access control incoherencies, presenting hurdles for web developers to construct secure web applications. a unique contribution of this paper is to identify the compatibility cost of removing these unsafe browser features. to do this, we have built webanalyzer, a crawler-based framework for measuring real-world usage of browser features, and used it to study the top 100,000 popular web sites ranked by alexa. our methodology and results serve as a guideline for browser designers to balance security and backward compatibility. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player
inspector gadget: automated extraction of proprietary gadgets from malware binaries. unfortunately, malicious software is still an unsolved problem and a major threat on the internet. an important component in the fight against malicious software is the analysis of malware samples: only if an analyst understands the behavior of a given sample, she can design appropriate countermeasures. manual approaches are frequently used to analyze certain key algorithms, such as downloading of encoded updates, or generating new dns domains for command and control purposes. in this paper, we present a novel approach to automatically extract, from a given binary executable, the algorithm related to a certain activity of the sample. we isolate and extract these instructions and generate a so-called gadget, i.e., a stand-alone component that encapsulates a specific behavior. we make sure that a gadget can autonomously perform a specific task by including all relevant code and data into the gadget such that it can be executed in a self-contained fashion. gadgets are useful entities in analyzing malicious software: in particular, they are valuable for practitioners, as understanding a certain activity that is embedded in a binary sample (e.g., the update function) is still largely a manual and complex task. our evaluation with several real-world samples demonstrates that our approach is versatile and useful in practice. the acm portal is published by the association for computing machinery. copyright © 2010 acm, inc. terms of usage privacy policy code of ethics contact us useful downloads: adobe acrobat quicktime windows media player real player