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The x-Kernel: An Architecture for Implementing Network Protocols

by Norman C. Hutchinson, Larry L. Peterson - IEEE Transactions on Software Engineering , 1991
"... This paper describes a new operating system kernel, called the x-kernel, that provides an explicit architecture for constructing and composing network protocols. Our experience implementing and evaluating several protocols in the x-kernel shows that this architecture is both general enough to acc ..."
Abstract - Cited by 662 (21 self) - Add to MetaCart
This paper describes a new operating system kernel, called the x-kernel, that provides an explicit architecture for constructing and composing network protocols. Our experience implementing and evaluating several protocols in the x-kernel shows that this architecture is both general enough

Exokernel: An Operating System Architecture for Application-Level Resource Management

by Dawson R. Engler, M. Frans Kaashoek, James O’toole , 1995
"... We describe an operating system architecture that securely multiplexes machine resources while permitting an unprecedented degree of application-specific customization of traditional operating system abstractions. By abstracting physical hardware resources, traditional operating systems have signifi ..."
Abstract - Cited by 732 (24 self) - Add to MetaCart
Aegis operations are 10–100 times faster than Ultrix,a mature monolithic UNIX operating system. ExOS implements processes, virtual memory, and inter-process communication abstractions entirely within a library. Measurements show that ExOS’s application-level virtual memory and IPC primitives are 5

Approximate Signal Processing

by S. Hamid Nawab, Alan V. Oppenheim, Anantha P. Chandrakasan, Joseph M. Winograd, Jeffrey T. Ludwig , 1997
"... It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing these tra ..."
Abstract - Cited by 538 (2 self) - Add to MetaCart
It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing

MapReduce: Simplified data processing on large clusters.

by Jeffrey Dean , Sanjay Ghemawat - In Proceedings of the Sixth Symposium on Operating System Design and Implementation (OSDI-04), , 2004
"... Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of ..."
Abstract - Cited by 3439 (3 self) - Add to MetaCart
Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details

A Maximum Entropy approach to Natural Language Processing

by Adam L. Berger, Stephen A. Della Pietra , Vincent J. Della Pietra - COMPUTATIONAL LINGUISTICS , 1996
"... The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper we des ..."
Abstract - Cited by 1366 (5 self) - Add to MetaCart
describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.

TelegraphCQ: Continuous Dataflow Processing for an Uncertan World

by Sirish Chandrasekaran, Owen Cooper, Amol Deshpande, Michael J. Franklin, Joseph M. Hellerstein, Wei Hong, Sailesh Krishnamurthy, Sam Madden, Vijayshankar Raman, Fred Reiss, Mehul Shah , 2003
"... Increasingly pervasive networks are leading towards a world where data is constantly in motion. In such a world, conventional techniques for query processing, which were developed under the assumption of a far more static and predictable computational environment, will not be sufficient. Instead, qu ..."
Abstract - Cited by 514 (23 self) - Add to MetaCart
Increasingly pervasive networks are leading towards a world where data is constantly in motion. In such a world, conventional techniques for query processing, which were developed under the assumption of a far more static and predictable computational environment, will not be sufficient. Instead

The process group approach to reliable distributed computing

by Kenneth P. Birman - Communications of the ACM , 1993
"... The difficulty of developing reliable distributed softwme is an impediment to applying distributed computing technology in many settings. Expeti _ with the Isis system suggests that a structured approach based on virtually synchronous _ groups yields systems that are substantially easier to develop, ..."
Abstract - Cited by 572 (19 self) - Add to MetaCart
distributed system to follow directly from the reliability of its con-stituents, but this is not always the case. The mechanisms used to structure a distributed system and to implement cooperation between components play a vital role in determining how reliable the system will be. Many contemporary

Pregel: A system for large-scale graph processing

by Grzegorz Malewicz, Matthew H. Austern, Aart J. C. Bik, James C. Dehnert, Ilan Horn, Naty Leiser, Grzegorz Czajkowski - IN SIGMOD , 2010
"... Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs—in some cases billions of vertices, trillions of edges—poses challenges to their efficient processing. In this paper we present a computational model ..."
Abstract - Cited by 496 (0 self) - Add to MetaCart
Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs—in some cases billions of vertices, trillions of edges—poses challenges to their efficient processing. In this paper we present a computational

Pig Latin: A Not-So-Foreign Language for Data Processing

by Christopher Olston, Benjamin Reed, Utkarsh Srivastava, Ravi Kumar, Andrew Tomkins
"... There is a growing need for ad-hoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively e ..."
Abstract - Cited by 607 (13 self) - Add to MetaCart
expensive at this scale. Besides, many of the people who analyze this data are entrenched procedural programmers, who find the declarative, SQL style to be unnatural. The success of the more procedural map-reduce programming model, and its associated scalable implementations on commodity hardware

An Overview of Workflow Management: From Process Modeling to Workflow Automation Infrastructure

by Diimitrios Georgakopoulos, Mark Hornick, Amit Sheth - DISTRIBUTED AND PARALLEL DATABASES , 1995
"... Today’s business enterprises must deal with global competition, reduce the cost of doing business, and rapidly develop new services and products. To address these requirements enterprises must constantly reconsider and optimize the way they do business and change their information systems and appl ..."
Abstract - Cited by 670 (26 self) - Add to MetaCart
and applications to support evolving business processes. Workflow technology facilitates these by providing methodologies and software to support (i) business process modeling to capture business processes as workflow specifications, (ii) business process reengineering to optimize specified processes, and (iii
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