ppxscal/embedding_network huggingface dataset:
Automated Learning of Workload Measures for Load Balancing on a Distributed System
Authors: Pankaj Mehra, Benjamin W. Wah
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 03 (1993)

Load-balancing systems use workload indices to dynamically schedule jobs. We present a novel method of automatically learning such indices. Our approach uses comparator neural networks, one per site, which learn to predict the relative speedup of an incoming job using only the resource-utilization patterns observed prior to the job's arrival. Our load indices combine information from the key resources of contention: CPU, disk, network, and memory.
Teaching technology in an online, distance education environment
Authors: M. S. Cohen
Venue: Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01 (2001)

There are numerous challenges inherent in teaching technology classes. These challenges are further exacerbated when teaching in an online distance education environment. A number of practical techniques used by the authors to facilitate teaching in this environment are discussed. Special tools and techniques such as bulletin boards, email, course syllabus, web pages, calendars, whiteboards, creation of a course CD, synchronous and asynchronous communication, and technology setups are examined in relation to their pedagogical relevance in the online environment. Organizational efforts such as effective planning, setting the tone, building communication, and evaluation and feedback are also discussed. This paper discusses the authors' attempts to meet the challenges. The primary goal is to establish an effective online learning community to facilitate learning.
Reconfigurable Branch Processing Strategy in Super-scalar Microprocessors
Authors: Terence M. Potter, Hsiao-Chen Chung, Chuan-lin Wu
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 01 (1993)

In this paper, we develop a model for measuring branch performance on super-scalar processors. This model takes the form of CP I equations for different branch processing strategies. This model is the basis for a proposed design wherein the branch processing strategy in a processor can be reconfigured for optimal performance over a varying application load. There are nine parameters which are required to describe performance of a given branch processing method -four are dependent primarily on the processor architecture, two depend on the application program, and three depend primarily on the branch instance. The highest performance branch prediction algorithm can be determined by a combination of application profiling and runtime statistic gathering
Interactive network management visualization with SVG and AJAX
Authors: Athanasios Douitsis, Dimitrios Kalogeras
Venue: Proceedings of the 20th conference on Large Installation System Administration (2006)

The area of visualization has always been one of the most attractive sections of network management technology. Successful management tools must not only fulfill objective management needs but also be aesthetically appealing. Consequently, the seemingly mundane task of presenting information to the user has become almost a true art. The application proposed in this paper is a vehicle for the presentation of network management data using interactive graphs. By using the Scalable Vector Graphics markup language (SVG) and Asynchronous Javascript and XML (AJAX), it strives to aid the rapid development of visually impressive management applications that are accessible through the use of a web browser. These highly interactive and versatile applications can respond to user actions and present data which is organized into layers and is retrieved and refreshed on demand. The data of these layers is generated by network management tools that plug in to the application through the use of a modular framework.
Application development powered by rapid, on-demand service composition
Authors: Maja Vukovic, Evangelos Kotsovinos, Peter Robinson
Venue: Proceedings of the IEEE International Conference on Service-Oriented Computing and Applications (2007)

Context aware application design models are often based on embedding contextual dependencies - in the form of if-then rules to specify how applications should react to context changes. In this paper we argue that such approaches are impractical and increase the complexity of context aware applications, due to the large variety of possibly even unanticipated context types and their values. We present the design and implementation of a framework for building context aware applications on-demand, as dynamically composed sequences of calls to services. Our system employs goal-oriented inferencing for assembling composite services, monitors their execution, adapts applications to deal with contextual changes, and enables failure recovery mechanisms that minimise application disruption. By means of experimental evaluation in a realistic infotainment application, we demonstrate that the framework provides an effective, efficient, and scalable solution.
How good is your predictor? Expanding confidence intervals to define probability densities on adaptive parameters
Authors: M. Dzwonczyk
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

A method is proposed to measure the performance of linear predictors as they track non-stationary stochastic processes. Classical linear regression techniques are combined with a novel use of instantaneous error to define the likelihood that the coefficients of a linear predictor adequately capture a system's state. The resultant probability measure serves as a metric of predictor performance: a probability near unity indicates that the predictor is performing well, while a probability near zero indicates the state of the system is poorly captured by the coefficients. The approach is extended to trace coefficients, weighted by these probabilities, as they move about in a space of possible states. The probability measure provides an instantaneous confidence measure of the route that the system proceeds upon within that space: a likelihood roadmap of the state of the system through time. Specifically, the method is applied to the important problem of predicting the vibration signature of rotorcraft gearboxes as they mechanically fail. Actual data from US Navy drivetrain teststands are used to validate the method and underlying assumptions.
Technology-assisted instruction applied to cooperative learning: the SHIECC project
Authors: S. Labidi
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

This work is part of the SHIECC Project, whose aim is to design and implement a computer-supported collaborative learning environment applied to courses in engineering. The authors focus here on the conceptual model of the system; the present their agent-based architecture and propose new cooperative learning strategies to be applied within the cooperative learning sessions of SHIECC.
Dynamical systems: stability and simulability
Authors: Mathieu Hoyrup
Venue: Mathematical Structures in Computer Science (2007)

Computers are used extensively to simulate continuous dynamical systems. However, different conceptual and mathematical structures underlie discrete machines and continuous dynamics, so the question arises as to the ability of the computer to simulate or, more generally, to check the properties of a continuous system. We discuss and compare two notions of stability for a continuous dynamical system, viz. shadowing and robustness, and relate them to both the practical and theoretical computability of the system. We first discuss what we can learn from the stability of a system, using a finite-precision machine. We then show, following the work in Collins (2005), that shadowing fails but robustness succeeds in ensuring the checkability of a reachability property.
VLSI implementation of a reversible variable length encoder/decoder
Authors: M. Novell
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

Variable length codes (VLCs) are known for their efficient compression, but are susceptible to noisy environments due to synchronization losses that can occur from bit error propagation. The interest in reversible variable length codes (RVLCs) has come about due to the growing need for wireless exchange of compressed image and video signals over noisy channels and the ability for RVLCs to provide greater error robustness than their non-reversible counterparts (VLCs). With the current ITU H.263+ and ISO MPEG-4 standards already using RVLCs, low power implementations of the RVLC are essential in providing error robustness in real-time systems, while minimizing power consumption. This paper presents the first published VLSI architectures of a low power reversible variable length encoder and decoder. Results show power consumption of less than 1 mW for both encoder and decoder, with an additional 65% increase in area for the decoder over that of a conventional VLD design.
Pseudorandomness for Approximate Counting and Sampling
Authors: Ronen Shaltiel, Christopher Umans
Venue: Computational Complexity (2006)

We study computational procedures that use both randomness and nondeterminism. The goal of this paper is to derandomize such procedures under the weakest possible assumptions.Our main technical contribution allows one to "boost" a given hardness assumption: We show that if there is a problem in EXP that cannot be computed by poly-size nondeterministic circuits then there is one which cannot be computed by poly-size circuits that make non-adaptive NP oracle queries. This in particular shows that the various assumptions used over the last few years by several authors to derandomize Arthur-Merlin games (i.e., show AM = NP) are in fact all equivalent.We also define two new primitives that we regard as the natural pseudorandom objects associated with approximate counting and sampling of NP-witnesses. We use the "boosting" theorem and hashing techniques to construct these primitives using an assumption that is no stronger than that used to derandomize AM.We observe that Cai's proof that $$\rm S^{P}_{2} \subseteq ZPP^{NP}$$ and the learning algorithm of Bshouty et al. can be seen as reductions to sampling that are not probabilistic. As a consequence they can be derandomized under an assumption which is weaker than the assumption that was previously known to suffice.
On the stability of the multi-queue multi-server processor sharing with limited service
Authors: Andreas Brandt, Manfred Brandt
Venue: Queueing Systems: Theory and Applications (2007)

We consider a multi-queue multi-server system with n servers (processors) and m queues. At the system there arrives a stationary and ergodic stream of m different types of requests with service requirements which are served according to the following k-limited head of the line processor sharing discipline: The first k requests at the head of the m queues are served in processor sharing by the n processors, where each request may receive at most the capacity of one processor. By means of sample path analysis and Loynes' monotonicity method, a stationary and ergodic state process is constructed, and a necessary as well as a sufficient condition for the stability of the m separate queues are given, which are tight within the class of all stationary ergodic inputs. These conditions lead to tight necessary and sufficient conditions for the whole system, also in case of permanent customers, generalizing an earlier result by the authors for the case of n=k=1.
Subband image coding using block-zero tree coding and vector quantization
Authors: K. Rose
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

The need for developing effective coding techniques for various multimedia services is increasing in order to meet the demand for image and video data. In this paper, a block-zero tree coding (BZTC) algorithm is proposed for multilayer coding and progressive transmission of images. The BZTC algorithm is constructed as an embedded coding so that the encoding and decoding process can be terminated at any point and allowing reasonable image quality. Some features of our BZTC algorithm are (1) prediction of the significance of blocks across scale, (2) state transition rules for representing the significance block map, and (3) block coding by vector quantization using a multiband codebook consisting of several subcodebooks dedicated for each band at a given threshold.
A Hybrid Approach to Sentence Alignment Using Genetic Algorithm
Authors: Mrityunjay Gautam, R. M. K. Sinha
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

Sentence alignment in bilingual corpora has been an active research topic in the Machine Translation research groups. There have been multiple works in the past to align sentences in bilingual corpus in English and Euro-pean languages and some Asian languages like Chinese and Japanese. This work introduces a novel approach for sentence alignment in bilingual corpora using lexical and statistical information about the language pair using genetic algorithm. The only lexical information used in this work is a restricted form of bilingual dictionary (incom-plete). The algorithm works based on the weighted sum of a set of statistical parameters and the parameter denoting degree of dictionary match. No other lexical information like part of speech tagging, chunking, n-gram statistics etc has been used in this work. Our approach has been tested for structurally dissimilar language pair of English-Hindi and is shown to yield a high performance even under noisy conditions. We compare our results with that of Microsoft alignment tool on the same corpus and we find our results to be superior.
Edge Vector Based Mode Decision for H.264/AVC Intra Prediction
Authors: Chern-Loon Lim, Kim-Han Thung, P. Raveendran
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

H.264/AVC exploits temporal and spatial redundancies to obtain higher coding gain. This comes with a cost of higher complexity encoder and higher computational time, which makes it difficult for real-time applications. In this paper, we present a fast intra-prediction mode selection method for H.264/AVC based on local edge information. Prior to intra prediction process, edge vectors of every pixel in a 4x4 block are totaled up to determine the edge direction. Based on the edge direction information, one directional mode is chosen and compared with the DC mode to choose the best mode with least rate distortion cost. Experimental results show that the proposed method reduces the computation complexity while it gives an almost similar visual quality of the reconstructed frame as compared to the one obtained by using exhaustive prediction method. The proposed method also outperforms Feng Pan's method [5] in computational time and number of bits generated.
Audio-visual speech processing: progress and challenges
Authors: Gerasimos Potamianos
Venue: Proceedings of the HCSNet workshop on Use of vision in human-computer interaction - Volume 56 (2006)

This keynote focuses on using visual channel information to improve automatic speech processing for human computer interaction. Two main issues are discussed: the extraction and representation of visual speech, as well as its fusion with traditional acoustic information. The talk mostly considers applying these techniques to automatic speech recognition, however additional areas of interest are also mentioned, for example audio-visual speech detection, enhancement, and synthesis, as well as speaker recognition. The state-of-the-art and remaining challenges in these areas are also discussed.
Concurrent Error Detection Methods for Asynchronous Burst-Mode Machines
Authors: Sobeeh Almukhaizim, Yiorgos Makris
Venue: IEEE Transactions on Computers (2007)

Asynchronous controllers exhibit various characteristics that limit the effectiveness and applicability of the Concurrent Error Detection (CED) methods developed for their synchronous counterparts. Asynchronous Burst-Mode Machines (ABMMs), for example, do not have a global clock to synchronize the ABMM with the additional circuitry that is typically used by synchronous CED methods (for example, duplication). Therefore, performing effective CED in ABMMs requires a synchronization method that will appropriately enable the checker (for example, comparator) in order to avoid false alarms. Also, ABMMs contain redundant logic, which guarantees the hazard-free operation required for correct interaction between the circuit and its environment. Redundant logic, however, allows some single event transients to manifest themselves only as hazards but not as logic discrepancies. Therefore, performing effective CED in ABMMs requires the ability to detect hazards with which synchronous CED methods are not concerned. In this work, we first devise hardware solutions for performing checking synchronization and hazard detection. We then demonstrate how these solutions enable the development of three complete CED methods for ABMMs. The first method (Duplication-based CED) is an adaptation of the well-known duplication method within the context of ABMMs. The second method (Transition-Triggered CED) is a variation of duplication wherein the implementation cost is reduced by allowing hazards in the duplicate circuit. In contrast to these two methods, which are nonintrusive, the third method (Berger code-based CED) is intrusive since it requires reencoding of the ABMM with check symbols based on the Berger code. Although this intrusiveness may slightly impact performance, Berger code-based CED incurs the lowest area overhead among the three methods, as indicated through experimental results.
Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database
Authors: Jens Niehaus, Christian Igel, Wolfgang Banzhaf
Venue: Evolutionary Computation (2007)

In this paper we describe the genetic programming system GGP operating on graphs and introduce the notion of graph isomorphisms to explain how they influence the dynamics of GP. It is shown empirically how fitness databases can improve the performance of GP and how mapping graphs to a canonical form can increase these improvements by saving considerable evaluation time.
Effectiveness of a Dynamic Load Balancing Library for Scientific Applications
Authors: Rohit Chaube, Ricolindo L. Carino, Ioana Banicescu
Venue: Proceedings of the Sixth International Symposium on Parallel and Distributed Computing (2007)

The design of a general-purpose dynamic load balancing library for a vast variety of parallel applications is a very challenging task. The library has to address potentially unpredictable load imbalance in the application, to interface with the data structures native to the application and to achieve significant performance improvement and scalability. In this paper we look into the design and sample results of a new dynamic load balancing library called LB Migrate, targeted for large scientific applications with parallel loops as a major source of concurrency. The applicatons must supply the library a routine that encapsulates the computations for a chunk of loop iterates, and the data for the computations must be stored in an array of arbitary type. We demonstrate the effectiveness of the library on two real applications - the profiling of an automatic quadrature routine problem and for a simulation of a hybrid model for image denoising. The experimental results indicate that the library achieves up to 60 % performance improvement for these applications.
Theory and implementation of adaptive algorithms for rejecting disturbances having multiple sinusoidal components
Authors: Marc Bodson
Venue:  (2006)

This dissertation is concerned about adaptive algorithms for rejecting disturbances having multiple sinusoidal components. A discrete-time adaptive algorithm is proposed to reject such disturbances in the case where the frequencies are unknown and possibly time-varying. A reference sensor is not assumed to be available. The stability of the algorithm is analyzed using averaging theory, and the design of the parameters is based on the linearized averaged system. While the algorithm is first designed for rejecting periodic disturbances with one sinusoidal component, it is also extended to deal with cases where the disturbance has multiple sinusoidal components. A frequency separation method is proposed to prevent the frequency estimates from converging to the same value. The dissertation also considers the problem of rejecting disturbances with two sinusoidal components in the case where the frequencies are unknown and closely spaced. A natural approach consists in canceling the components using two separate adaptive algorithms combined in a single scheme. However, experiments in active noise control applications have shown that convergence using such an approach could be very slow. The alternative approach of this dissertation consists in representing the disturbance signal as a single sinusoid with time-varying magnitude and phase. The theoretical basis and the limitations of such a representation are first discussed. Then, an adaptive disturbance rejection algorithm is proposed and the resulting nonlinear system is analyzed using some approximations. Active noise control experiments demonstrate that the proposed algorithm has better convergence properties than an algorithm designed to cancel the two frequency components separately. In some cases, however, the cost is a small residual error on the output signal. The last problem considered in this dissertation is the rejection of sinusoidal disturbances with known but rapidly varying frequencies. The dissertation shows that a large class of adaptive algorithms for disturbance cancellation yields control systems that are equivalent to linear compensators implementing the internal model principle. The fact had been known to be true for periodic disturbances with fixed frequency. However, the dissertation shows that the result can be extended to disturbances of time-varying frequency (i.e., frequency-modulated signals), regardless of the rate of variation of the frequency. In particular, several adaptive controllers are shown to be equivalent to linear time-varying compensators, with a pseudo-gradient algorithm being equivalent to a polytopic linear parameter varying compensator. The equivalence provides an opportunity to apply knowledge gained either in adaptive control or in robust linear control to the other field.
Exogeneous Management in Autonomic Service Compositions
Authors: Alan Colman
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

This paper proposes that software architectures that support autonomic service-oriented computing need to have an exogenous management structure. Exogenous management regards autonomicity as a property of relationships between elements, rather than a property of the elements themselves. We explain the concept of exogenous management, and show how a number of desirable attributes that support autonomicity flow from this approach. These attributes include self-management; separability; recursive composition; and grounding through the monitoring of interactions. We will show how these attributes help enhance the adaptability and control the complexity of context-aware compositions of services. We then discuss how this exogenous approach to management has been implemented in the ROAD (Role-oriented Adaptive Design) programming framework. This framework is extended by software developers to create service compositions whose level of autonomicity can be incrementally modified at runtime.