High-availability LH* schemes with mirroring

Litwin, Witold; Neimat, Marie-Anne

doi:10.1109/coopis.1996.555011

Cited by 17 publications

(10 citation statements)

References 9 publications

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“…On the other side, scalability, high speed of operation and fault tolerance are important advantages of SDDS [8,7,10,11]. Storing an object-oriented database in SDDS should increase performance of OODBMS and make OODB applications scalable.…”

Section: Motivationmentioning

confidence: 99%

Scalable Store of Java Objects Using Range Partitioning

Bedla

Sapiecha

2012

Advances in Software Engineering Techniques

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Abstract. Scalable Store of Objects (SSO) should allow for storing and maintaining a huge number of objects distributed over many nodes of a network. RP*N is a structure which belongs to a family of order-preserving, Range Partitioning Scalable Distributed Data Structures (RP* SDDS). The architectures of SDDS were designed to store records. Different structures of objects and complicated dependences between objects are the cause that a new architecture for RP* is needed. The paper describes a new object-oriented version of RP*N architecture and its implementation for Java objects. This version can be used in a fast and scalable store of Java objects. Performance of the implementation is evaluated and compared with serialization of objects on a disk and storing objects as a main-memory collection.

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Section: Motivationmentioning

confidence: 99%

Scalable Store of Java Objects Using Range Partitioning

Bedla

Sapiecha

2012

Advances in Software Engineering Techniques

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“…Liner Hashing and it variants [9], [10], [11], and [12] adopt scalable distributed data structure. This method does not take into account the differences between disks and so does not support heterogeneous disks.…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of a Random Data-Placement System with High Scalability, Reliability and Performance

Liu

Xue

Wang

et al. 2006

Computational Science – ICCS 2006

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Abstract. As storage system scales to thousands of disks, data distribution, load balance and the support for heterogeneous disks become increasingly important. In this paper, we present a new data-placement method named Weighted Interval Algorithm (WIA) for heterogeneous disks. Through it is not optimal in some circumstances, the difference between WIA and the optimal algorithm is trivial. Combined with replication, WIA can nearly balance access load and space utilization and improve reliability simultaneously. For the first time, we implement a data-placement system with high scalability, reliability and performance. The experimental results show that WIA reduces the average response time by 14.8% and decreases coefficient of relative load from 78.09% to 47.46% while the difference of the ratio of space utilization between disks is not more than 0.79%.

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“…Born out of dynamic hashing [105,106], linear hashing [107,113] is one of the most common family of SDDS. Litwin, in particularly, has proposed many extensions to the basic linear hashing approach, including variants featuring grouping [115], mirroring [116], security [117], scalable availability [114], ReedSolomon codes [121], and a variant tuned for switched multicomputers [90].…”

Section: Scalable Object Locationmentioning

confidence: 99%

“…Several schemes have been proposed for the LH * family of SDDS, including mirroring [116], bit-level striping with parity [117], data with scalable parity [114], and ReedSolomon encoding [121].…”

Section: Redundant Encoding For Reliabilitymentioning

confidence: 99%