The advances in microelectronic engineering have rendered massively distributed computing networks practical and affordable, This paper describes one application of this distributed computing paradigm to the analysis ...
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The advances in microelectronic engineering have rendered massively distributed computing networks practical and affordable, This paper describes one application of this distributed computing paradigm to the analysis and design of microwave circuits, A distributed computing network, constructed in the form of a neural network, is developed to automate the operations typically performed on a normalized Smith chart. Examples showing the use of this computing network for impedance matching and stabilizing are provided.
Edge intelligence and, by extension, any distributed computing continuum system will bring to our future society a plethora of new and useful applications, which will certainly revolutionize our way of living. Neverth...
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Edge intelligence and, by extension, any distributed computing continuum system will bring to our future society a plethora of new and useful applications, which will certainly revolutionize our way of living. Nevertheless, managing these systems challenges all previously developed technologies for Internet-distributed systems. In this regard, this article presents a set of techniques and concepts that can help manage these systems;these are framed in the main paradigm for autonomic computing, the well-known monitor-analyze-plan-execute over shared knowledge, or MAPE-K. All in all, this article aims at unveiling research opportunities for these new systems, encouraging the community to work together toward new technologies to make edge intelligence a reality.
Atomistic simulations of protein folding have the potential to be a great complement to experimental studies, but have been severely limited by the time scales accessible with current computer hardware and algorithms....
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Atomistic simulations of protein folding have the potential to be a great complement to experimental studies, but have been severely limited by the time scales accessible with current computer hardware and algorithms. By employing a worldwide distributed computing network of tens of thousands of PCs and algorithms designed to efficiently utilize this new many-processor, highly heterogeneous, loosely coupled distributed computing paradigm, we have been able to simulate hundreds of microseconds of atomistic molecular dynamics. This has allowed us to directly simulate the folding mechanism and to accurately predict the folding rate of several fast-folding proteins and polymers, including a nonbiological helix, polypeptide alpha-helices, a beta-hairpin, and a three-helix bundle protein from the villin headpiece. Our results demonstrate that one can reach the time scales needed to simulate fast folding using distributed computing, and that potential sets used to describe interatomic interactions are sufficiently accurate to reach the folded state with experimentally validated rates, at least for small proteins. (C) 2002 Wiley Periodicals, Inc.
This paper proposes a suitable distributed computing model as the basis for building a network management system. Author has been studying a distributed reactive model, called Meta for this purpose at Cornell Universi...
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This paper proposes a suitable distributed computing model as the basis for building a network management system. Author has been studying a distributed reactive model, called Meta for this purpose at Cornell University. Effectiveness using Meta is to provide high level program interface for developing network management system, and programmers can achieve network management system with coding small amount of programs. It also realizes easy additions and modifications for network management application programs. To confirm the effectiveness of the proposal, the author has utilized Meta to implement an experimental network management system. The experimental system provides high level interfaces for monitoring and controlling network components. It also supports reliable communication over distributed nodes. Preliminary evaluation of the system shows that critical network management applications are provided within an appropriate response time for all applications provided by SNMP, with small development cost and easy system modification.
Before a conventional application is converted into a distributed one (typically a costly process), it is prudent to estimate the improvement in run time that will be achieved, Previous research has tended to ignore c...
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Before a conventional application is converted into a distributed one (typically a costly process), it is prudent to estimate the improvement in run time that will be achieved, Previous research has tended to ignore communications delays in order to facilitate analysis, However, such models lead to optimistic predictions and may be grossly inaccurate for problems involving fine-grained parallelism, In this paper, we consider distributed computation on a token ring local area network, We obtain exact analytical results for the mean speedup, both for small n and for asymptotically large It. For large n, we show that under very general conditions speedup tends to a limiting value with increasing numbers of processors;i.e., there is a ''communications speedup limit'' that cannot be exceeded regardless of the number of processors, Because the token ring represents a limiting case for the effects of communications delays, results obtained thus provide an upper bound for speedup on Ethernets and other bus-type networks, Analytical results were verified by simulation. (C) 1997 Academic Press.
Artificial intelligence and big data technology are important technical means to improve quantitative understanding of natural phenomena in Earth sciences. Large-scale spatial data provides a basic geospatial backgrou...
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Artificial intelligence and big data technology are important technical means to improve quantitative understanding of natural phenomena in Earth sciences. Large-scale spatial data provides a basic geospatial background for geoscience research. An effective and efficient distributed computing frame for spatial data is an indispensable infrastructure. It is still a challenge for disk-based distributed computing framework to analyze and process large-scale data efficiently. Such a challenge has driven the rapid development of various memory-based distributed computing platforms such as Spark, Plink, Apex, and more. Now, it is urgent to develop an efficient platform-independent distributed computing framework with a unique focus on large-scale spatial data. This paper provides a memory-based distributed computing framework named GeoBeam. It abstracts all the operations of spatial data into spatial pipeline, collection and transforms. Finally, they are encapsulated as feature dataset and feature store interfaces in GIS to shield the details of the underlying distributed operations. Experimental results show that GeoBeam can support efficient range query and processing of large-scale spatial data on Spark cluster and Flink cluster. GeoBeam provides an effective cross-platform distributed computing solution for fast processing of large-scale spatial data.
While the reliability of distributed-computing systems (DCSs) has been widely studied under the assumption that computing elements (CEs) fail independently, the impact of correlated failures of CEs on the reliability ...
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While the reliability of distributed-computing systems (DCSs) has been widely studied under the assumption that computing elements (CEs) fail independently, the impact of correlated failures of CEs on the reliability remains an open question. Here, the problem of modeling and assessing the impact of stochastic, correlated failures on the service reliability of applications running on DCSs is tackled. The service reliability is modeled using an integrated analytical and Monte-Carlo (MC) approach. The analytical component of the model comprises a generalization of a previously developed model for reliability of non-Markovian DCSs to a setting where specific patterns of simultaneous failures in CEs are allowed. The analytical model is complemented by a MC-based procedure to draw correlated-failure patterns using the recently reported concept of probabilistic shared risk groups (PSRGs). The reliability model is further utilized to develop and optimize a novel class of dynamic task reallocation (DTR) policies that maximize the reliability of DCSs in the presence of correlated failures. Theoretical predictions, MC simulations, and results from an emulation testbed show that the reliability can be improved when DTR policies correctly account for correlated failures. The impact of correlated failures of CEs on the reliability and the key dependence of DTR policies on the type of correlated failures are also investigated.
In the competitive electric power market allowing open access transmission environment, the knowledge of available transfer capability (ATC) is very important for optimum utilization of existing transmission facility....
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In the competitive electric power market allowing open access transmission environment, the knowledge of available transfer capability (ATC) is very important for optimum utilization of existing transmission facility. ATC information conveys how much power can be transmitted through the power network over and above already committed usage without violation of system security limits. This paper presents a Levenberg-Marquardt algorithm neural network (LMANN)-based approach for fast and accurate estimation of system ATC. System ATC has been estimated for both varying load condition as well as for single line outage contingency condition by employing distributed computing. Principal component analysis (PCA) has been applied for effective input feature selection. Contingency clusters are formed such that each cluster contains almost similar ATC values. For each contingency clusters separate LMANNs have been developed. All the proposed LMANNs have been trained and tested under distributed computing environment and a considerable speed up in the training is obtained. The proposed approach has been examined on 75-bus Indian power system and IEEE 300-bus system and found significantly efficient.
Emerging Internet uses-including peer-to-peer and grid computing-provide both a glimpse of and the impetus for evolving the Internet into a distributed computing platform of unprecedented scale. Taking a longer view, ...
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Emerging Internet uses-including peer-to-peer and grid computing-provide both a glimpse of and the impetus for evolving the Internet into a distributed computing platform of unprecedented scale. Taking a longer view, the authors consider what would be needed to make the Internet an application-hosting platform: a networked, distributed counterpart of the hosting environment traditional operating systems provide to applications within a single node. The foundation of their proposed approach is to disaggregate and virtualize individual system resources as services that can be described, discovered, and dynamically configured at runtime to execute an application.
Starting in the late 1950s, researchers have been performing progressively more sensitive searches for radio signals from extraterrestrial civilizations, but each search has been limited by the technologies available ...
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Starting in the late 1950s, researchers have been performing progressively more sensitive searches for radio signals from extraterrestrial civilizations, but each search has been limited by the technologies available at the time. As radio frequency technologies have became more efficient and computers have become faster, the searches have grown larger and more sensitive, The SETI@home project, managed by a group of researchers at the Space Sciences Laboratory of the University of California, Berkeley, is the first attempt to use large-scale distributed computing to perform a sensitive search for radio signals from extraterrestrial civilizations
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