DRMonitor is a system for monitoring usage of computing resources of networked heterogeneous (Linux and Windows NT's derived) personal computers. DRMonitor is aimed to serve resource-monitoring applications and to...
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ISBN:
(纸本)0769518753
DRMonitor is a system for monitoring usage of computing resources of networked heterogeneous (Linux and Windows NT's derived) personal computers. DRMonitor is aimed to serve resource-monitoring applications and to assist load-balancing policies by providing performance and load data about each monitored machine included in the system. through a reduced set of primitives, applications can periodically receive updated information about system usage. the paper describes available primitives, discusses some internal aspects of the monitoring system, and presents monitoring results of a classroom with 10 personal computers.
In this paper we describe the architecture of PerfMC, a Performance Monitoring system for Clusters of Workstations (CoW);a prototype implementation of the architecture is also presented. PerJMC is driven by an XML con...
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ISBN:
(纸本)0769518753
In this paper we describe the architecture of PerfMC, a Performance Monitoring system for Clusters of Workstations (CoW);a prototype implementation of the architecture is also presented. PerJMC is driven by an XML configuration file, and uses the Simple network Management Protocol (SNMP) to collect statistics from each networked equipment. the collected data are maintained on the local disk of the monitoring station in a compact format, and various graphical and statistical analyses can be performed off-line. the monitoring tool embeds an HTTP server which is able to generate various types of graphs from the collected data. Moreover the HTTP server can generate arbitrary XML pages by dynamically applying XSLT stylesheets to an internal XML representation of the cluster's status. the heavy use of XML-based technologies differentiates the proposed approach to traditional monitoring tools.
the paper presents an approach to detection of attacks against Internet-of-things networks and devices which can be used in critical infrastructures. It is based on use of machine learning and big data processing. Fea...
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ISBN:
(纸本)9781728116440
the paper presents an approach to detection of attacks against Internet-of-things networks and devices which can be used in critical infrastructures. It is based on use of machine learning and big data processing. Feature of the offered approach is using the method of reduction of output data sets and application of various algorithms of machine learning based on distributed data processing. the paper compares the speed and accuracy of attack detection on the basis of machine learning algorithms in the local and distributed modes.
the paper proposes a new approach to multicriteria optimization of the structure of secure information interaction in distributed computing systems. A distinguishing feature of the approach is the use of the sequentia...
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ISBN:
(纸本)9781728165820
the paper proposes a new approach to multicriteria optimization of the structure of secure information interaction in distributed computing systems. A distinguishing feature of the approach is the use of the sequential concessions method. this approach provides the acceptable flexibility in comparing the system construction variants by taking into account not only the priority of the system according to efficiency indicators, but also the relationships of the indicators. the mathematical basis of the proposed method is considered. the procedure of implementation of the proposed method for ensuring security of information interaction in a distributed hierarchical automated control system is demonstrated, and its experimental assessment is given.
the paper presents a Coarse-Grained Multicomputer algorithm that solves the Longest Common Subsequence Problem. this algorithm can be implemented in the CGM with P processors in O(N-2/P) in time and O(P) communication...
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ISBN:
(纸本)0769518753
the paper presents a Coarse-Grained Multicomputer algorithm that solves the Longest Common Subsequence Problem. this algorithm can be implemented in the CGM with P processors in O(N-2/P) in time and O(P) communication steps. It is the first CGM algorithm for this problem. We present also experimental results showing that the CGM algorithm is very efficient.
In this paper we present the integration of database and remote accessibility in a distributed surveillance system. We focus on the flexibility and scalability of the system, as well as the design and implementation p...
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ISBN:
(纸本)0769518753
In this paper we present the integration of database and remote accessibility in a distributed surveillance system. We focus on the flexibility and scalability of the system, as well as the design and implementation possibilities of readily available free software components. What is more, we discuss the main issues encountered during the development stage and propose feasible solutions for them.
Load distribution is an essential factor to parallel efficiency of numerical simulations that are based on spatial grids, especially on clusters of symmetric multiprocessors (SMPs). this paper presents a method of map...
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ISBN:
(纸本)0769518753
Load distribution is an essential factor to parallel efficiency of numerical simulations that are based on spatial grids, especially on clusters of symmetric multiprocessors (SMPs). this paper presents a method of mapping spatial grid nodes to processors that combines two load balancing methodologies, graph partitioning and graph matching, to achieve maximum parallel efficiency on SMP clusters. the method has been successfully applied to load distribution in a parallel Computational Fluid Dynamics (CFD) simulation. Test runs on a PC cluster prove the effectiveness of our method.
this paper is about support for the exchange of information and knowledge among researchers. We introduce the concepts of open archives and grey literature, which provide valuable sources for researchers who work alon...
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ISBN:
(纸本)0769518753
this paper is about support for the exchange of information and knowledge among researchers. We introduce the concepts of open archives and grey literature, which provide valuable sources for researchers who work alone. We analyse how users exchange information and knowledge and introduce communities to more adequately reflect the nature of human information and knowledge exchange. Finally, we present the functionality and implementation of the CYCLADES environment-a distributed and open collaborative virtual archive environment based on open archives, providing several services supporting individual researchers as well as communities of researchers.
Computing potential is wasted and idle not only when applications are executed, but also when a user navigates by Internet. To take advantage of this, an architecture named Parasite has been designed in order to use d...
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ISBN:
(纸本)0769518753
Computing potential is wasted and idle not only when applications are executed, but also when a user navigates by Internet. To take advantage of this, an architecture named Parasite has been designed in order to use distributed and networked resources, without disturbing local computation. this is the working principle of certain global computing projects, but our development introduces new ideas with respect to user intervention, the distributed programming paradigm or the resident software on each user's computer. the project is based on developing software technologies and infrastructures in order to facilitate Web-baseddistributed computing. this paper outlines the most recent advances in the project, as well as discussing the architecture developed and an experimental framework that would validate this infrastructure.
this research is about selection of deep neural network models for anomaly detection in Internet of things network traffic. We are experimentally evaluating deep neural network models using the same software, hardware...
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ISBN:
(纸本)9781665414555
this research is about selection of deep neural network models for anomaly detection in Internet of things network traffic. We are experimentally evaluating deep neural network models using the same software, hardware and the same subsets of the UNSW-NB 15 dataset for training and testing. the assessment results are quality metrics of anomaly detection and the time spent on training models.
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