Replication Techniques For Speeding Up Parallel Applications On Distributed Systems

• Main Authors: Henri E. Bal, M. Frans Kaashoek, Andrew S. Tanenbaum, Jack Jansen
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Published: 1992
• Subjects: Index terms; Amoeba; distributed systems; multicast; Orca; parallel programming; replication; shared data-object
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.1745

Traditional programming methods for loosely-coupled systems are based on message-passing. More recently, methods have emerged based for "virtually" sharing data. These methods simplify distributed programming, but are hard to implement efficiently, as loosely-coupled systems do not contain physical shared memory. We introduce a new model, the shared data-object model, that eases the implementation of parallel applications on loosely-coupled systems, but can still be implemented efficiently. In the shared data-object model, shared data are encapsulated in data objects, which are variables of userdefined abstract data types. To speed up access to shared data, data objects are replicated. This paper discusses the design choices involved in replicating objects and their effect on performance. We have implemented several options to determine which strategy is most efficient. Index terms: Amoeba, distributed systems, multicast, Orca, parallel programming, replication, shared data-object mod.