@conference {17859,
	title = {Scheduling multiple data visualization query workloads on a shared memory machine},
	booktitle = {Parallel and Distributed Processing Symposium., Proceedings International, IPDPS 2002, Abstracts and CD-ROM},
	year = {2002},
	month = {2002///},
	pages = {11 - 18},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images},
	keywords = {Atomic force microscopy, Biomedical informatics, Computer science, Data analysis, data visualisation, Data visualization, datasets, deductive databases, digitized microscopy image browsing, directed graph, directed graphs, dynamic query scheduling model, Educational institutions, high workloads, image database, limited resources, multiple data visualization query workloads, multiple query optimization, performance, priority queue, Processor scheduling, Query processing, query ranking, Relational databases, scheduling, shared memory machine, shared memory systems, Virtual Microscope, visual databases},
	isbn = {0-7695-1573-8},
	doi = {10.1109/IPDPS.2002.1015482},
	author = {Andrade,H. and Kurc, T. and Sussman, Alan and Saltz, J.}
}
@article {16479,
	title = {Logic-based query optimization for object databases},
	journal = {IEEE Transactions on Knowledge and Data Engineering},
	volume = {12},
	year = {2000},
	month = {2000/08//Jul},
	pages = {529 - 547},
	abstract = {We present a technique for transferring query optimization techniques, developed for relational databases, into object databases. We demonstrate this technique for ODMG database schemas defined in ODL and object queries expressed in OQL. The object schema is represented using a logical representation (Datalog). Semantic knowledge about the object data model, e.g., class hierarchy information, relationship between objects, etc., as well as semantic knowledge about a particular schema and application domain are expressed as integrity constraints. An OQL object query is represented as a logic query and query optimization is performed in the Datalog representation. We obtain equivalent (optimized) logic queries, and subsequently obtain equivalent (optimized) OQL queries for each equivalent logic query. We present one optimization technique for semantic query optimization (SQO) based on the residue technique of U. Charavarthy et al. (1990; 1986; 1988). We show that our technique generalizes previous research on SQO for object databases. We handle a large class of OQL queries, including queries with constructors and methods. We demonstrate how SQO can be used to eliminate queries which contain contradictions and simplify queries, e.g., by eliminating joins, or by reducing the access scope for evaluating a query to some specific subclass(es). We also demonstrate how the definition of a method or integrity constraints describing the method, can be used in optimizing a query with a method},
	keywords = {access scope, application domain, class hierarchy information, Constraint optimization, data integrity, Data models, Datalog, Datalog representation, deductive databases, equivalent logic query, integrity constraints, Lifting equipment, Logic, logic based query optimization, logic programming, logic queries, logic query, logical representation, object data model, object databases, object queries, object schema, object-oriented databases, ODL, ODMG database schemas, optimization technique, optimized OQL queries, OQL object query, query languages, Query optimization, query optimization techniques, Query processing, Relational databases, residue technique, semantic knowledge, semantic query optimization},
	isbn = {1041-4347},
	doi = {10.1109/69.868906},
	author = {Grant,J. and Gryz,J. and Minker, Jack and Raschid, Louiqa}
}
@conference {14575,
	title = {Parallel transitive closure computations using topological sort},
	booktitle = {, Proceedings of the First International Conference on Parallel and Distributed Information Systems, 1991},
	year = {1991},
	month = {1991/12/04/6},
	pages = {122 - 129},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Deals with parallel transitive closure computations. The sort-based approaches introduced sorts the tuples of the relation into topological order, and the sorted relation is then horizontally partitioned and distributed across several processing nodes of a message passing multiprocessor system. This data partitioning strategy allows the transitive closure computation of the local data fragments to be computed in parallel with no interprocessor communication. The construction of the final result then requires only a small number of joins. Extensive analytical results are included in the paper as well. They show that the proposed techniques leads to a speedup that is essentially linear with the number of processors. Its performance is significantly better than the recently published hashless parallel algorithm},
	keywords = {Computer science, Concurrent computing, data partitioning, Database systems, database theory, deductive databases, File systems, horizontal partitioning, joins, local data fragments, message passing multiprocessor system, Multiprocessing systems, Parallel algorithms, PARALLEL PROCESSING, parallel programming, parallel transitive closure, processing nodes, relation tuples, Relational databases, sorting, topological sort},
	isbn = {0-8186-2295-4},
	doi = {10.1109/PDIS.1991.183079},
	author = {Hua,K. A and Hannenhalli, Sridhar}
}
