Cooperative Heuristics for the Federated View Selection Problem
نویسنده
چکیده
The federated view selection problem (FVSP) is an optimization technique designed to enhance query performance in a federated data warehouse environment through the materialization of select views given resource constraints and storage restrictions. Current research focuses on single-instance heuristics, which have difficulty scaling. In this work, we introduce two commonly used cooperative heuristics – cooperative coevolutionary genetic algorithms (CCGA) and discrete cooperative particle swarm optimization (DiCPSO) – to the FVSP. Existing implementations of these heuristics on non-federated view selection problem instances assume dimension independence. This, however, does not always hold, and can have a profound impact on solution quality. Thus, a cooperative construction technique for dimension dependence is also presented. CCGA and DiCPSO are compared using random, linear, and dimension dependence solution space segmentation. The results indicate CCGA with the submitted dimension dependent constructor increases solution quality slightly to significantly, while moderately to dramatically decreasing execution time compared to all other occurrences. Keywords—Data warehouse, federation, federated view selection problem, heuristics, optimization, view selection problem.
منابع مشابه
The Federated View Selection Problem
Database federation is becoming an increased reality for business and clinical organizations due to rapid data accumulation, making a single, monolithic data warehouse difficult to achieve. A commonly used technique to decrease query execution time in data warehousing environments is to precompute and store beneficial views. Known as the view selection problem, this process seeks to identify th...
متن کاملA Hybrid Solution Approach Based on Benders Decomposition and Meta-Heuristics to Solve Supply Chain Network Design Problem
Supply Chain Network Design (SCND) is a strategic supply chain management problem that determines its configuration. This mainly focuses on the facilities location, capacity sizing, technology selection, supplier selection, transportation, allocation of production and distribution facilities to the market, and so on. Although the optimal solution of the SCND problem leads to a significant reduc...
متن کاملAn optimization technique for vendor selection with quantity discounts using Genetic Algorithm
Vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. The problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. Such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. This paper propose...
متن کاملSpeeding Up Materialized View Selection in Data Warehouses Using a Randomized Algorithm
A data warehouse stores information that is collected from multiple, heterogeneous information sources for the purpose of complex querying and analysis. Information in the warehouse is typically stored in the form of materialized views, which represent pre-computed portions of frequently asked queries. One of the most important tasks when designing a warehouse is the selection of materialized v...
متن کاملIntegrated , Distributed Fault Management for Communication Networks
This report describes an integrated, distributed fault management (IDFM) system for communication networks. The architecture is based on a distributed intelligent agent paradigm, with probabilistic networks as the framework for knowledge representation and evidence inferencing. A static strategy for generating the suggestive test sequence is proposed, based on which a heuristic dynamic strategy...
متن کامل