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THE REPLICA LOCATION SERVICE The Globus Project and the DataGrid Project

THE REPLICA LOCATION SERVICE The Globus Project and the DataGrid Project. Replication in Data Grids. Large data sets are frequently replicated to: Reduce access latency Maintain local control over necessary data Improve reliability and load balancing.

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THE REPLICA LOCATION SERVICE The Globus Project and the DataGrid Project

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  1. THE REPLICA LOCATION SERVICEThe Globus Project and the DataGrid Project Replication in Data Grids • Large data sets are frequently replicated to: • Reduce access latency • Maintain local control over necessary data • Improve reliability and load balancing A Replica Location Service is a distributed registry service that records the locations of data copies and allows discovery of replicas The Replica Location Service Architecture Five Components of the RLS Architecture Framework • Consistent state maintained in Local Replica Catalogs (LRCs) • Mappings between logical names (LFNs) and target names • Collective state with relaxed consistency in Replica Location Indices (RLIs) • Each RLI contains mappings from LFNs to LRCs • Variety of index structures can be created by varying number of RLIs, • redundancy and partitioning • Soft state maintenance of RLI state • LRCs send state information to RLIs using soft state protocols • Information in RLIs times out and must be periodically refreshed • Optionalcompression of soft state updates • Prototype implements Bloom filter compression • Membership service • Keeps track of LRCs and RLIs and their soft state update patterns • Prototype implements static configuration for RLS The RLS Implementation RLS Components Implementation Features • Two types of soft state updates from LRCs to RLIs • Complete list of logical names registered in LRC • Bloom filter summaries of LRC • Bloom filter advantages • Reduce size of soft state updates • Reduce associated memory and network requirements • Sending updates is faster and scales better with size of LRC • User-defined attributes • May be associated with logical or target names • Partitioning • Divide LRC soft state updates among RLI index nodes using pattern matching of logical names • Redundancy • Send soft state updates to multiple RLIs • Front-End Server • Multi-threaded • Supports GSI Authentication • Common implementation for LRC and RLI • Back-end Server • mySQL Relational Database • Holds logical name to target name mappings • Client APIs: C and Java The RLS SC2002 Testbed RLS Designers and Developers RLS Sponsors and Testbed Participants • Globus Project: • www.globus.org/rls • Shishir Bharathi, Ann Chervenak, Ewa Deelman, Ian Foster, • Carl Kesselman, Matei Ripeanu, Bob Schwartzkopf, Mei-Hui Su • DataGrid Project: • http://cern.ch/grid-data-management • Leanne Guy, Peter Kunszt, Heinz Stockinger, Kurt Stockinger

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