ppxscal/embedding_network huggingface dataset:
Architectural support for efficient utilization of interconnection network resources
Authors: Timothy Mark Pinkston
Venue:  (2002)

Efficient and reliable communication is essential for achieving high performance in networked computing environments. Limited network resources bring about unavoidable competition among in-flight packets, resulting in network congestion and, possibly, deadlock. The effectiveness of deadlock handling mechanisms in a network often determines the upper bound in the throughput and utilization that the network can deliver. Much research has been conducted to improve network performance by efficiently handling deadlock anomalies. However, the existence of multiple message types and associated inter-message dependencies at network end nodes may cause message-dependent deadlocks in networks that are designed to be free of routing deadlock. Most methods currently used for dealing with message-dependent deadlock require more system resources than are necessary and/or do not use system resources efficiently. This may have an adverse effect on system performance if resources are scarce. To provide useful insight into the severity of message-dependent deadlocks, this work characterizes the frequency of such deadlocks in multiprocessor/multicomputer systems. It then proposes a handling technique based on progressive deadlock recovery and evaluates its performance. Results show that message-dependent deadlocks occur very infrequently under typical circumstances. The proposed technique relaxes restrictions on the use of network resources considerably, allowing the routing of packets and the handling of message-dependent deadlocks to be much more efficient. One of the drawbacks of recovery-based deadlock handling techniques is that networks might suffer from significant performance degradation when they are deeply saturated. There has been a body of research done on solving this problem by preventing networks from being overloaded with packets. However, none of these provide an efficient way of accelerating the movement of packets involved in congestion onward to their destinations. This dissertation proposes a new mechanism for the detection and resolution of network congestion and deadlocks. The proposed mechanism is based on increasing the scheduling priority of packets involved in congestion and providing necessary resources for those packets to make forward progress.
A Race-Free Bandwidth Reservation Protocol for QoS Routing in Mobile Ad Hoc Networks
Authors: Imad Jawhar, Jie Wu
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9 (2004)

Routing protocols are an essential part of the ef.cient design of mobile ad hoc networks (MANETs). Existing routing protocols such as DSR, AODV, and TORA are based on a best effort strategy [18][19]. However, in order for MANETs to be practical for more demanding real time applications such as multimedia, providing a certain needed level of quality of service becomes an essential component in the communication protocol design [2] [11] [21] [22]. QoS routing protocols provide the capability of .nding a path between two nodes which satisfies the application layer's minimum bandwidth requirements. Previous papers addressed this issue for different communication environments such as TDMA (Time Division Multiple Access) [7] [8] [12] [13] and CDMA (Code Division Multiple Access)-over-TDMA [3] [14] [15]. While most of these models are generally more practical and less expensive, they impose on the designer the constraint of the hidden terminal and exposed terminal problems. The paper by Liao and Tseng [12] addressed these issues and provided a TDMA-based bandwidth reservation protocol for QoS routing in MANETs. However, this protocol does not account for the race condition which can become more significant with increased node mobility, network density and higher traffic loads. This race condition is also a limitation of other QoS routing protocols [7] [8]. This paper addresses this issue and provides a protocol which enables the network to cope with this and other related problems such as parallel reservation. We also provide increased optimizations which signi.cantly enhance the throughput and efficiency of the QoS routing protocol.
Does Fit Matter? The Impact of Fit on Collaboration Technology Effectiveness over Time
Authors: Robert M. Fuller, Alan R. Dennis
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 1 - Volume 1 (2004)

This research examines how different levels of task-technology fit can impact collaboration technology effectiveness and efficiency over time. The results of a longitudinal experiment indicate that initially, teams using poor-fitting collaboration technology had lower effectiveness and efficiency, satisfaction, and perceptions of fit than teams using fitting collaboration technology. Over time, however, poor-fit teams improved while fit teams remained consistent, thereby eliminating the initial differences in measured outcomes between poor-fit and fit teams. The results suggest that task-technology fit may be more relevant as a predictor of effectiveness and efficiency in contexts where the task and the collaboration technology are less malleable.
Web File Transmission by Object Packaging - Performance Comparison with HTTP 1.0 and HTTP 1.1 Persistent Connection
Authors: Hiroshi Fujinoki, Murugesan Sanjay, Chintan Shah
Venue: Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks (2003)

Recently, the largest concern for corporate owners of webservers is how to minimize the response time. In order tominimize the response time, a new efficient file transmissiontechnique for World-Wide-Web, called web file transmission byObject Packaging, is proposed. The prototype design andpreliminary performance evaluation of Object Packaging havebeen presented in the 27th Conference on Local ComputerNetworks. In this paper, the performance of Object Packagingis compared to HTTP 1.0 and HTTP 1.1 Persistent Connectionin terms of the server and client response time and CPUworkload by experiment method. It is found that ObjectPackaging reduces the response time and CPU workload at theserver by up to 92.0 and 91.1% from HTTP 1.0 and 64.5 and82.4% from HTTP 1.1 Persistent Connection, respectively.From the results of the experiments, it is found that ObjectPackaging will be an efficient technique to minimize theresponse time in transferring web files. The results of theexperiments also suggest the significance of disk I/O overheadfor web servers in high speed networks.
Parallel and distributed simulation
Authors: Farshad Moradi, Rassul Ayani
Venue: Applied system simulation: methodologies and applications (2003)

Parallel simulation is used to execute a single simulation program on a parallel computer. This simulation methodology is often used to reduce the execution time of such simulation programs. In distributed simulation (DS), the simulation program is run on computer devices that are located on different geographical locations. Some of the potential benefits of DS are interoperability, reuse, and scalability. The Distributed Interactive Simulation (DIS) and High Level Architecture (HLA) are the two IEEE standards that are used within distributed simulation community. One of the main parts of the HLA is the Runtime Infrastructure (RTI). RTI is a collection of software that provides common services required by multiple simulation systems. In this chapter, we review various parallel and distributed simulation techniques. We also discuss some of the services provided by the HLA-RTI, including data distribution management (DDM), object and ownership management (OWM).
Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm
Authors: Dao-Qiang Zhang, Song-Can Chen
Venue: Neural Processing Letters (2003)

There is a trend in recent machine learning community to construct a nonlinear version of a linear algorithm using the 'kernel method', e.g. Support Vector Machines (SVMs), kernel principal component analysis, kernel fisher discriminant analysis and the recent kernel clustering algorithms. In unsupervised clustering algorithms using kernel method, typically, a nonlinear mapping is used first to map the data into a potentially much higher feature space, where clustering is then performed. A drawback of these kernel clustering algorithms is thatthe clustering prototypes lie in high dimensional feature space and hence lack clear and intuitive descriptions unless using additional projection approximation from the feature to the data space as done in the existing literatures. In this paper, a novel clustering algorithm using the 'kernel method' based on the classical fuzzy clustering algorithm (FCM) is proposed and called as kernel fuzzy c-means algorithm (KFCM). KFCM adopts a new kernel-induced metric in the data space to replace the original Euclidean norm metric in FCM and the clustered prototypes still lie in the data space so that the clustering results can be reformulated and interpreted in the original space. Our analysis shows that KFCM is robust to noise and outliers and also tolerates unequal sized clusters. And finally this property is utilized to cluster incomplete data. Experiments on two artificial and one real datasets show that KFCM hasbetter clustering performance and more robust than several modifications of FCM for incomplete data clustering.
Algorithm 829: Software for generation of classes of test functions with known local and global minima for global optimization
Authors: Marco Gaviano, Dmitri E. Kvasov, Daniela Lera, Yaroslav D. Sergeyev
Venue: ACM Transactions on Mathematical Software (TOMS) (2003)

A procedure for generating non-differentiable, continuously differentiable, and twice continuously differentiable classes of test functions for multiextremal multidimensional box-constrained global optimization is presented. Each test class consists of 100 functions. Test functions are generated by defining a convex quadratic function systematically distorted by polynomials in order to introduce local minima. To determine a class, the user defines the following parameters: (i) problem dimension, (ii) number of local minima, (iii) value of the global minimum, (iv) radius of the attraction region of the global minimizer, (v) distance from the global minimizer to the vertex of the quadratic function. Then, all other necessary parameters are generated randomly for all 100 functions of the class. Full information about each test function including locations and values of all local minima is supplied to the user. Partial derivatives are also generated where possible.
How computer games affect CS (and other) students' school performance
Authors: John G. Messerly
Venue: Communications of the ACM (2004)

Compulsive game playing, especially of the role-playing variety, risks failing grades and withdrawal of financial support from tuition-paying parents.
Modelling business processes and enterprise activities at the knowledge level
Authors: Robert De Souza, Zhao Zhen Ying, Liu Chao Yang
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (1998)

As manufacturing systems become more sophisticated and complicated, effective managers know how they play a crucial role in managing an enterprise and managers know how to deal with their dynamics and uncertainty. In this article, a formalism based on the computer-integrated manufacturing open-system architecture (CIMOSA) reference model is presented to specify the business processes and enterprise activities at the knowledge level. The formalism uses an integration of multiple types of knowledge, including precise, muddy, and random symbolic and numerical knowledge to systematically represent enterprise behavior and functionality. To support the modelling process, a prototype is developed and an example for a maintenance activity is presented to demonstrate the effectiveness of the proposed method.
On Random Intersection Graphs: The Subgraph Problem
Authors: Michał Karoński, Edward R. Scheinerman, Karen B. Singer-Cohen
Venue: Combinatorics, Probability and Computing (1999)

A new model of random graphs &ndash; random intersection graphs &ndash; is introduced. In this model, vertices are assigned random subsets of a given set. Two vertices are adjacent provided their assigned sets intersect. We explore the evolution of random intersection graphs by studying thresholds for the appearance and disappearance of small induced subgraphs. An application to gate matrix circuit design is presented.
Introducing non-functional requirements in UML
Authors: Guadalupe Salazar-Zárate, Pere Botella, Ajantha Dahanayake
Venue: UML and the unified process (2003)

This chapter introduces an approach concerned with the non-functional features of software systems. The specific objectives of the research focus on the possibility of developing mechanisms to capture non-functional information in the development of software systems in a similar manner to its counterpart, the functional information. Particularly, the research described in this chapter focuses on the possible extension of the Unified Modeling Language (UML) (Booch et al., 1998). In order to get an initial specification of some non-functional requirements, the Software Quality Standard ISO/ IEC 9126 (International Standard, 1991) is used. The language NoFun (Botella et al., 2001) is the basis used to achieve some organization about the nonfunctional concepts used in this approach.
Space-time linear constellation precoded systems
Authors: Georgios B. Giannakis
Venue:  (2003)

Establishing reliable communication links over wireless channels must cope with challenges such as multipath fading, bandwidth, and power limitations. Diversity techniques have emerged as an effective means to combat multipath fading effects, and have been widely adopted by many current or developing wireless communication standards, including 3-G systems and 4-G prototypes. Linear constellation precoding is a bandwidth- and power-efficient tool in enabling diversity transmissions over single-antenna and multi-antenna fading channels. We present in this thesis a comprehensive study on constructions and applications of linear constellation precoders (LCPs). From the design perspective, we first present analytical constructions of real LCPs (RLCPs) and complex LCPs (CLCPs) over quadrature amplitude modulation (QAM), pulse amplitude modulation (PAM), and phase-shift keying (PSK) constellations. We show that our RLCPs and CLCPs can always achieve maximum diversity gain. We derive coding gains for RLCPs and CLCPs over constellations carved from the square lattice and the hexagonal lattice, which include any size of QAM, PAM, 3-PSK, and 6-PSK. We also prove the optimality of our constructions for many cases of practical interest. From the application perspective, we develop two space-time (ST) linear constellation precoded schemes with different design objectives in quasi-static fading scenarios. We finally design linear constellation precoded orthogonal frequency division multiplexing (OFDM) transmission schemes for frequency-selective fading channels.
Critical event prediction for proactive management in large-scale computer clusters
Authors: R. K. Sahoo, A. J. Oliner, I. Rish, M. Gupta, J. E. Moreira, S. Ma, R. Vilalta, A. Sivasubramaniam
Venue: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (2003)

As the complexity of distributed computing systems increases, systems management tasks require significantly higher levels of automation; examples include diagnosis and prediction based on real-time streams of computer events, setting alarms, and performing continuous monitoring. The core of autonomic computing, a recently proposed initiative towards next-generation IT-systems capable of 'self-healing', is the ability to analyze data in real-time and to predict potential problems. The goal is to avoid catastrophic failures through prompt execution of remedial actions.This paper describes an attempt to build a proactive prediction and control system for large clusters. We collected event logs containing various system reliability, availability and serviceability (RAS) events, and system activity reports (SARs) from a 350-node cluster system for a period of one year. The 'raw' system health measurements contain a great deal of redundant event data, which is either repetitive in nature or misaligned with respect to time. We applied a filtering technique and modeled the data into a set of primary and derived variables. These variables used probabilistic networks for establishing event correlations through prediction algorithms. We also evaluated the role of time-series methods, rule-based classification algorithms and Bayesian network models in event prediction.Based on historical data, our results suggest that it is feasible to predict system performance parameters (SARs) with a high degree of accuracy using time-series models. Rule-based classification techniques can be used to extract machine-event signatures to predict critical events with up to 70% accuracy.
Dependability Analysis Using a Fault Injection Tool Based on Synthesizability of HDL Models
Authors: Hamid R. Zarandi, Seyed Ghassem Miremadi, Alireza Ejlali
Venue: Proceedings of the 18th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2003)

This paper presents a fault injection tool, called SINJECT that supports several synthesizable and non-synthesizable fault models for dependability analysis of digital systems modeled by popular HDLs. The tool provides injection of transient and permanent faults into the Verilog as well as VHDL models of a digital circuit to study the fault behavior, fault propagation and fault coverage. Moreover, using specific simulators, the SINJECT provides a mixed-mode fault injection, i.e., fault injection into both Verilog and VHDL parts of a model, to achieve high description reality by Verilog and high capability modeling by VHDL. To demonstrate the tool, two case studies are evaluated: 1) an arithmetic processor with a non-synthesizable Verilog model, called ARP and 2) a VHDL model of 32-bit processor with a synthesizable ALU, called DP32. The results show that depending on the fault injection points in the ARP, the effects of faults were significantly different, while in the case of DP32, the fault coverage varied between 51 to 56 percent of total fault injected.
A framework for e-learning technology
Authors: Jerome Eric Luczaj
Venue:  (2003)

This research uses state-of-the-art methodologies to improve in-classroom learning and post-classroom computer-based review and instruction. In particular, it brings into focus the issue of matching teacher's goals and course objectives with students' learning and expectations through a framework, called Classroom and Student Achievement Assessment Framework (CaSA). Too often, connections between program objectives, instruction and student learning are based upon supposition, made in retrospect with vague recollection of the events. Institutions and instructors need information about student behavior that is both timely and timed in order to identify activities that reflect student learning and understanding, gain a better understanding of when student learning occurs and optimize institutional and instructor-based efforts that promote student learning. An artifact of this research, CaSA is an internet-based, client-server system that will augment the classroom session by allowing the students to annotate instructional streams for personalized review, take notes, and provide real-time feedback to the instructor via a networked computer. The system collects student and instructor activities into a timed sequence both in the classroom and when students review class instructional streams. By unobtrusively recording these activities as timed, synchronized events, CaSA creates a data trail that links final outcomes to specific student and instructor activities. This rich collection of activity data can be mined to gain a better understanding of when and how learning occurs and what can be done to improve it. This research demonstrates an automated, internet-based, activity collection framework that will capture student classroom activity, sequence this activity into event trails, associate these trails to learning units and connect these events to learning outcome assessment.
A heuristic method for large-scale multi-facility location problems
Authors: Yuri Levin, Adi Ben-Israel
Venue: Computers and Operations Research (2004)

A heuristic method for solving large-scale multi-facility location problems is presented. The method is analogous to Cooper's method (SIAM Rev. 6 (1964) 37), using the authors' single facility location method (Comput. Optim. Appl. 21 (2002) 213) as a parallel subroutine, and reassigning customers to facilities using the heuristic of nearest center reclassification. Numerical results are reported.
Area and performance optimizations in path-based scheduling
Authors: Reinaldo A. Bergamaschi, Raul Camposano, Michael Payer
Venue: Proceedings of the conference on European design automation (1991)

This paper describes the area and performance optimizations implemented in the As-Fast-As-Possible (AFAP) scheduling algorithm. The AFAP scheduling algorithm is a path-based technique that finds the minimum number of control steps for all possible sequences of operations in the control-flow graph, under given constraints. Area requirements for functional units, such as their number and type, are translated into constraints which are then met exactly. The number of registers is also minimized. The performance optimizations included in this paper are concerned mainly with the scheduling of loops.
Telling humans and computers apart automatically
Authors: Luis von Ahn, Manuel Blum, John Langford
Venue: Communications of the ACM (2004)

How lazy cryptographers do AI.
Occurrence and substring heuristics for &#x03B4;-matching
Authors: Maxime Crochemore, Costas S. Iliopoulos, Thierry Lecroq, Yoan J. Pinzon, Wojciech Plandowski, Wojciech Rytter
Venue: Fundamenta Informaticae (2002)

We consider a version of pattern matching useful in processing large musical data: δ-matching, which consists in finding matches which are δ-approximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance between two symbols a, b is measured as |a - b|. We also consider (δ, γ)-matching, where γ is a bound on the total sum of the differences. We first consider "occurrence heuristics" by adapting exact string matching algorithms to the two notions of approximate string matching. The resulting algorithms are efficient in practice. Then we consider "substring heuristics". We present δ-matching algorithms fast on the average providing that the pattern is "non-flat" and the alphabet interval is large. The pattern is "flat" if its structure does not vary substantially. The algorithms, named δ- BM1, δ-BM2 and δ-BM3 can be thought as members of the generalized Boyer-Moore family of algorithms. The algorithms are fast on average. This is the first paper on the subject, previously only "occurrence heuristics" have been considered Our substring heuristics are much stronger and refer to larger parts of texts (not only to single positions). We use δ-versions of suffix tries and subword graphs. Surprisingly, in the context of δ-matching subword graphs appear to be superior compared with compact suffix trees.