Results 1 - 10 of 1,425

Globus: A Metacomputing Infrastructure Toolkit

by Ian Foster, Carl Kesselman - International Journal of Supercomputer Applications , 1996
"... Emerging high-performance applications require the ability to exploit diverse, geographically distributed resources. These applications use high-speed networks to integrate supercomputers, large databases, archival storage devices, advanced visualization devices, and/or scientific instruments to for ..."
Abstract - Cited by 1929 (51 self) - Add to MetaCart
Emerging high-performance applications require the ability to exploit diverse, geographically distributed resources. These applications use high-speed networks to integrate supercomputers, large databases, archival storage devices, advanced visualization devices, and/or scientific instruments

GPS-Less Low Cost Outdoor Localization for Very Small Devices.

by Nirupama Bulusu , John Heidemann , Deborah Estrin - IEEE Personal Communications Magazine, , 2000
"... Abstract-Instrumenting the physical world through large networks of wireless sensor nodes, particularly for applications like environmental monitoring of water and soil, requires that these nodes be very small, light, untethered and unobtrusive. The problem of localization, i.e., determining where ..."
Abstract - Cited by 1000 (27 self) - Add to MetaCart
in these networks. In this paper, we review localization techniques and evaluate the effectiveness of a very simple connectivity-metric method for localization in outdoor environments that makes use of the inherent radio-frequency (RF) communications capabilities of these devices. A fixed number of reference points

Robust Classification for Imprecise Environments

by Foster Provost, Tom Fawcett , 1989
"... In real-world environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We present a method for the comparison of classifier performance that is robust to imprecise class distributions and misclas ..."
Abstract - Cited by 341 (15 self) - Add to MetaCart
In real-world environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We present a method for the comparison of classifier performance that is robust to imprecise class distributions

Pinpoint: Problem Determination in Large, Dynamic Internet Services

by Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armando Fox, O Fox, Eric Brewer - In Proc. 2002 Intl. Conf. on Dependable Systems and Networks , 2002
"... Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today's large, distributed, and dynamic application environments such as e-commerce systems. In this paper, we present a dynamic analysis methodology that automates problem ..."
Abstract - Cited by 298 (11 self) - Add to MetaCart
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today's large, distributed, and dynamic application environments such as e-commerce systems. In this paper, we present a dynamic analysis methodology that automates

Probability product kernels

by Tony Jebara, Risi Kondor, Andrew Howard, Kristin Bennett, Nicolò Cesa-bianchi - Journal of Machine Learning Research , 2004
"... The advantages of discriminative learning algorithms and kernel machines are combined with generative modeling using a novel kernel between distributions. In the probability product kernel, data points in the input space are mapped to distributions over the sample space and a general inner product i ..."
Abstract - Cited by 180 (9 self) - Add to MetaCart
The advantages of discriminative learning algorithms and kernel machines are combined with generative modeling using a novel kernel between distributions. In the probability product kernel, data points in the input space are mapped to distributions over the sample space and a general inner product

Learning from imbalanced data

by Haibo He, Edwardo A. Garcia - IEEE Trans. on Knowledge and Data Engineering , 2009
"... Abstract—With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding of knowledge discovery and analysis from raw data to support decision-m ..."
Abstract - Cited by 260 (6 self) - Add to MetaCart
important research directions for learning from imbalanced data. Index Terms—Imbalanced learning, classification, sampling methods, cost-sensitive learning, kernel-based learning, active learning, assessment metrics. Ç

Distributed Process Groups in the V Kernel

by David R. Cheriton, Willy Zwaenepoel - ACM Transactions on Computer Systems , 1985
"... The V kernel supports an abstraction of processes, with operations for interprocess communication, process management, and memory management. This abstraction is used as a software base for constructing distributed systems. As a distributed kernel, the V kernel makes intermachine bound-aries largely ..."
Abstract - Cited by 119 (6 self) - Add to MetaCart
The V kernel supports an abstraction of processes, with operations for interprocess communication, process management, and memory management. This abstraction is used as a software base for constructing distributed systems. As a distributed kernel, the V kernel makes intermachine bound

Real-Time Mach: Towards a Predictable Real-Time System

by Hideyuki Tokuda, Tatsuo Nakajima, Prithvi Rao
"... Distributed real-time systems play a very important role in our modern society. They are used in aircraft control, communication systems, military command and control systems, factory automation, and robotics. However, satisfying the rigid timing requirements of various real-time activities in distr ..."
Abstract - Cited by 212 (29 self) - Add to MetaCart
in distributed real-time systems often requires ad hoc methods to tune the system's runtime behavior The objective of Real-Time Mach is to develop a real-time version of the Mach kernel which provides users with a predictable and reliable distributed real-time computing environment. In this paper

Power management in energy harvesting sensor networks

by Aman Kansal, Jason Hsu, Sadaf Zahedi, Mani B. Srivastava - Networked and Embedded Systems Laboratory, UCLA , 2006
"... Power management is an important concern in sensor networks, because a tethered energy in-frastructure is usually not available and an obvious concern is to use the available battery energy efficiently. However, in some of the sensor networking applications, an additional facility is available to am ..."
Abstract - Cited by 232 (3 self) - Add to MetaCart
source. Another issue that becomes important in networked systems with multiple harvesting nodes is that different nodes may have different harvesting opportunity. In a distributed application, the same end-user performance may be achieved using different workload allocations, and resultant energy

Kernel

by P. Heinzlreiter, D. Kranzlmüller, H. Rosmanith, J. Volkert, Prof Dr, Peter Sloot
"... Abstract. The paper addresses the development and use of Grid middleware and the use of distributed resources for interactive visualisation of simulated data within a dedicated problem-solving environment. We developed an agent-oriented architecture, the Interactive Simulation System Conductor (ISS) ..."
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Abstract. The paper addresses the development and use of Grid middleware and the use of distributed resources for interactive visualisation of simulated data within a dedicated problem-solving environment. We developed an agent-oriented architecture, the Interactive Simulation System Conductor (ISS
Results 1 - 10 of 1,425