Open-Source ANSS Quake Monitoring System Software

ANSS stands for the Advanced National Seismic System of the U.S.A., and ANSS Quake Monitoring System (AQMS) is the earthquake management system (EMS) that most of its member regional seismic networks (RSNs) use. AQMS is based on Earthworm, but instead of storing files on disk, it uses a relational database with replication capability to store pick, amplitude, waveform, and event parameters. The replicated database and other features of AQMS make it a fully redundant system. A graphical user interface written in Java, Jiggle, is used to review automatically generated picks and event solutions, relocate events, and recalculate magnitudes. Add‐on mechanisms to produce various postearthquake products such as ShakeMaps and focal mechanisms are available as well. It provides a configurable automatic alarming and notification system. The Pacific Northwest Seismic Network, one of the Tier 1 ANSS RSNs, has modified AQMS to be compatible with a freely available, capable, open‐source database system, PostgreSQL, and is running this version successfully in production. The AQMS Software Working Group has moved the software from a subversion repository server hosted at the California Institute of Technology to a public repository at gitlab.com. The drawback of AQMS as a whole is that it is complex to fully configure and comprehend. Nevertheless, the fact that it is very capable, documented, and now free to use, might make it an attractive EMS choice for many seismic networks

Scalable Database Access Technologies for ATLAS Distributed Computing

ATLAS event data processing requires access to non-event data (detector conditions, calibrations, etc.) stored in relational databases. The database-resident data are crucial for the event data reconstruction processing steps and often required for user analysis. A main focus of ATLAS database operations is on the worldwide distribution of the Conditions DB data, which are necessary for every ATLAS data processing job. Since Conditions DB access is critical for operations with real data, we have developed the system where a different technology can be used as a redundant backup. Redundant database operations infrastructure fully satisfies the requirements of ATLAS reprocessing, which has been proven on a scale of one billion database queries during two reprocessing campaigns of 0.5 PB of single-beam and cosmics data on the Grid. To collect experience and provide input for a best choice of technologies, several promising options for efficient database access in user analysis were evaluated successfully. We present ATLAS experience with scalable database access technologies and describe our approach for prevention of database access bottlenecks in a Grid computing environment.Comment: 6 pages, 7 figures. To be published in the proceedings of DPF-2009, Detroit, MI, July 2009, eConf C09072

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

WIDE - A Distributed Architecture for Workflow Management

This paper presents the distributed architecture of the WIDE workflow management system. We show how distribution and scalability are obtained by the use of a distributed object model, a client/server architecture, and a distributed workflow server architecture. Specific attention is paid to the extended transaction support and active rule support subarchitectures

Query management in a sensor environment

Traditional sensor network deployments consisted of fixed infrastructures and were relatively small in size. More and more, we see the deployment of ad-hoc sensor networks with heterogeneous devices on a larger scale, posing new challenges for device management and query processing. In this paper, we present our design and prototype implementation of XSense, an architecture supporting metadata and query services for an underlying large scale dynamic P2P sensor network. We cluster sensor devices into manageable groupings to optimise the query process and automatically locate appropriate clusters based on keyword abstraction from queries. We present experimental analysis to show the benefits of our approach and demonstrate improved query performance and scalability