Vertical partitioning algorithms for database design
ACM Transactions on Database Systems (TODS)
Data allocation in distributed database systems
ACM Transactions on Database Systems (TODS)
Fragmenting Relations Horizontally Using a Knowledge-Based Approach
IEEE Transactions on Software Engineering
An adaptive data replication algorithm
ACM Transactions on Database Systems (TODS)
Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
A genetic algorithm for fragment allocation in a distributed database system
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
A new approach to developing and implementing eager database replication protocols
ACM Transactions on Database Systems (TODS)
A Model for Database Allocation Incorporating a Concurrency Control Mechanism
IEEE Transactions on Knowledge and Data Engineering
Allocating Data and Operations to Nodes in Distributed Database Design
IEEE Transactions on Knowledge and Data Engineering
Multi-Dimensional Database Allocation for Parallel Data Warehouses
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Query-Driven Data Allocation Algorithms for Distributed Database Systems
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
Incremental data allocation and reallocation in distributed database systems
Data warehousing and web engineering
An Adaptive Object Allocation and Replication Algorithm in Distributed Databases
ICDCSW '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Dynamic XML documents with distribution and replication
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Document replication and distribution in extensible geographically distributed web servers
Journal of Parallel and Distributed Computing - Scalable web services and architecture
The optimal location of replicas in a network using a READ-ONE-WRITE-ALL policy
Distributed Computing
Replica placement in adaptive content distribution networks
Proceedings of the 2004 ACM symposium on Applied computing
Choosing Replica Placement Heuristics for Wide-Area Systems
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Database fragmentation and allocation: an integrated methodology and case study
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Secure dynamic fragment and replica allocation in large-scale distributed file systems
IEEE Transactions on Parallel and Distributed Systems
A Joint Design Approach of Partitioning and Allocation in Parallel Data Warehouses
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A software development tool for improving quality of service in distributed database systems
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
DYFRAM: dynamic fragmentation and replica management in distributed database systems
Distributed and Parallel Databases
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Verification of partitioning and allocation techniques on teradata DBMS
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
Performance optimality enhancement algorithm in DDBS (POEA)
Computers in Human Behavior
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For a distributed database system to function efficiently, the fragments of the database need to be located judiciously at various sites across the relevant communications network. The problem of allocating these fragments to the most appropriate sites is a difficult one to solve, however, with most approaches available relying on heuristic techniques. Optimal approaches are usually based on mathematical programming, and formulations available for this problem are based on the linearization of nonlinear binary integer programs and have been observed to be ineffective except on very small problems. This paper presents new integer programming formulations for the nonredundant version of the fragment allocation problem. This formulation is extended to address problems which have both storage and processing capacity constraints; the approach is observed to be particularly effective in the presence of capacity restrictions. Extensive computational tests conducted over a variety of parameter values indicate that the reformulations are very effective even on relatively large problems, thereby reducing the need for heuristic approaches.