A monitoring sensor management system for grid environments

Tierney, Brian; Crowley, B.; Gunter, Dan; Holding, M.; Lee, Jason R.; Thompson, Megan M.

doi:10.1109/hpdc.2000.868639

Cited by 70 publications

(42 citation statements)

References 14 publications

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“…We define the event similarly to the definition presented by Terenziani et al [12] and Tierney et al [13] as time-stamped information about the state of a server or an application and its relevant system metrics, such as availability, CPU utilization, disk utilization and security auditing to industry standards. The contents of every event should be characterized by the meaningful details, such as host name, source name, event type (on Windows) or event severity (in Unix environments), event id and the event message.…”

Section: Events and Thresholdsmentioning

confidence: 99%

Tools for Distributed Systems Monitoring

Kufel

2016

Foundations of Computing and Decision Sciences

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Abstract. The management of distributed systems infrastructure requires dedicated set of tools. The one tool that helps visualize current operational state of all systems and notify when failure occurs is available within monitoring solution. This paper provides an overview of monitoring approaches for gathering data from distributed systems and what are the major factors to consider when choosing a monitoring solution. Finally we discuss the tools currently available on the market.

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Section: Events and Thresholdsmentioning

confidence: 99%

Tools for Distributed Systems Monitoring

Kufel

2016

Foundations of Computing and Decision Sciences

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“…Many Grid monitoring systems have been implemented based on this architecture. Java Agents for Monitoring and Management (JAMM) [6] is a wide-area GMA-like system that was developed at Lawrence Berkeley National Laboratory. This system uses sensors to collect and publish computer host information.…”

Section: Related Workmentioning

confidence: 99%

Light-weight service-oriented grid application toolkit

Kwon

Choi

Cho

2006

Proceedings of the 2006 ACM Symposium on Applied Computing

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With the growing requirement of computational power and hardware resources, Grid has become the major role in several researches and business areas. With the advanced capabilities of mobile, lightweight, and thin devices, Grid computing has, recently, migrated to pervasive and utility computing. To address these problems, we designed and implemented an agent-based lightweight Grid application toolkit, which is called MAGE (Mobile Agent-based Grid Environment). It consists of several hierarchical layers with dynamically controllable agents for archiving isolation of dependency among communication, message interpretation, and actual jobs. Because an agent represents a service in MAGE, each element of application can be replaced with a new task without intervention of other tasks. In this paper, we will describe the design issues and advantages in using our system.

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“…For some purposes the data must be consumed at a high rate [ 25]. When the data is used to improve the performance of an application at run-time, low perturbation is important [ 22,26]. To meet the needs of different monitors the system should be flexible, and extensible.…”

Section: Monitoringmentioning

confidence: 99%

“…Other interesting approaches are: performance analysis tools [ 16,27], NetLogger [ 27], firmware based distributed shared virtual memory (DSVM) system monitor for the SHRIMP multicomputer [ 15], network performance monitoring tools [ 11,18], Infopipes [ 6], Gscope [ 12], Prism debugger for MPI [ 23], JAMM monitoring sensor management system [ 26], Network Weather Service [ 32], other monitoring systems include [ 11,22,27,32], configurable monitoring systems include [ 11,22,27,32].…”

Section: Related Workmentioning

confidence: 99%

Experiences parallelizing, configuring, monitoring, and visualizing applications for clusters and multi-clusters

Anshus

Bjørndalen

Bongo

2004

Advances in Parallel Computing

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To make it simpler to experiment with the impact different configurations can have on the performance of a parallel cluter application, we developed the PATHS system. The PATHS system use a "wrapper" to provide a level of indirection to the actual run-time location of data making the data available from wherever threads or processes are located. A wrapper specify where data is located, how to get there, and which protocols to use. Wrappers are also used to add or modify methods accessing data. Wrappers are specified dynamically. A "path" is comprised of one or more wrappers. Sections of a path can be shared among two or more paths.By reconfiguring the LAM-MPI Allreduce operation we achieved a performance gain of 1.52, 1.79, and 1.98 on respectively two, four and eight-way clusters. We also measured the performance of the unmodified Allreduce operation when using two clusters interconnected by a WAN link with 30-50ms roundtrip latency. Configurations which resulted in multiple messages being sent across the WAN did not add any significant performance penalty to the unmodified Allreduce operation for packet sizes up to 4KB. For larger packet sizes the Allreduce operation rapidly detoriated performancewise.To log and visualize the performance data we developed EventSpace, a configurable data collecting, management and observation system used for monitoring low-level synchronization and communication behavior of parallel applications on clusters and multi-clusters. Event collectors detect events, create virtual events by recording timestamped data about the events, and then store the virtual events to a virtual event space. Event scopes provide different views of the application, by combining and pre-processing the extracted virtual events. Online monitors are implemented as consumers using one or more event scopes. Event collectors, event scopes, and the virtual event space can be configured and mapped to the available resources to improve monitoring performance or reduce perturbation. Experiments demonstrate that a wind-tunnel application instrumented with event collectors, has insignificant slowdown due to data collection, and that monitors can reconfigure event scopes to trade-off between monitoring performance and perturbation. The visual views we generated allowed us to detect anomalous communication behavior, and detect load balance problems.

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A monitoring sensor management system for grid environments

Abstract: Abstract

Cited by 70 publications

References 14 publications

Tools for Distributed Systems Monitoring

Tools for Distributed Systems Monitoring

Light-weight service-oriented grid application toolkit

Experiences parallelizing, configuring, monitoring, and visualizing applications for clusters and multi-clusters

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