Given a distributed multimedia database system and a set of queries as well as their frequencies from each site, the objective of a data allocation algorithm is to locate the multimedia data objects (MDOs) at different sites so as to minimize the total data transfer cost incurred in executing the queries. The data allocation problem, however, is NP-complete, and thus requires fast heuristics to generate efficient solutions. In this paper we propose three data allocation algorithms which are based on a genetic technique, an evolutionary process, and neural networks. We have implemented and evaluated these algorithms on our distributed multimedia database system test-bed. A comparison of the algorithms reveals trade-offs between their solution quality and time-complexity. 1

Abstract. A major cost in executing queries in a distributed database system is the data transfer cost incurred in transferring relations (fragments) accessed by a query from different sites to the site where the query is initiated. The objective of a data allocation algorithm is to determine an assignment of fragments at different sites so as to minimize the total data transfer cost incurred in executing a set of queries. This is equivalent to minimizing the average query execution time, which is of primary importance in a wide class of distributed conventional as well as multimedia database systems. The data allocation problem, however, is NP-complete, and thus requires fast heuristics to generate efficient solutions. Furthermore, the optimal allocation of database objects highly depends on the query execution strategy employed by a distributed database system, and the given query execution strategy usually assumes an allocation of the fragments. We develop a site-independent fragment dependency graph representation to model the dependencies among the fragments accessed by a query, and use it to formulate and tackle data allocation problems for distributed database systems based on query-site and move-small query execution strategies. We have designed and evaluated evolutionary algorithms for data allocation for distributed database systems.

We consider the consistency control problem for replicated data in a distributed computing system (DCS) and propose a new algorithm to dynamically regenerate copies of data objects in response to node failures and network partitioning in the system. The DCS is assumed to have strict consistency constraints for data object copies. The new algorithm combines the advantages of voting based algorithms and regeneration mechanisms to maintain mutual consistency of replicated data objects in the case of node failures and network partitioning. Our algorithm extends the feasibility of regeneration to DCS on wide area networks, and is able to satisfy user queries as long as there is one current partition in the system. 1 Introduction In a distributed computing environment, two types of failures may occur: the processor at a given site may fail (referred to as site failure), and communication between two sites may fail (referred to as communication link failure). When a site fails, processing at...

We consider the consistency control problem for replicated data in a distributed computing system (DCS) and propose a new algorithm to dynamically regenerate copies of data objects in response to node failures and network partitioning in the system. The DCS is assumed to have strict consistency constraints for data object copies. The new algorithm combines the advantages of voting based algorithms and regeneration mechanisms to maintain mutual consistency of replicated data objects in the case of node failures and network partitioning. Our algorithm extends the feasibility of regeneration to DCS on wide area networks, and is able to satisfy user queries as long as there is one current partition in the system. A stochastic availability analysis of our algorithm shows that it provides improved availability as compared to previously proposed dynamic voting algorithms. 1 Introduction In a distributed computing environment, two types of failures may occur: the processor at a given site may...

A major cost in executing queries in a distributed database system is the data transfer cost incurred in transferring multiple database objects (fragments) accessed by a query from different sites to the site where the query is initiated. The objective of a data allocation algorithm is to locate the fragments at different sites so as to minimize the total data transfer cost incurred in executing a set of queries. We develop a site-independent fragment dependency graph representation to model the dependencies among the fragments accessed by a query, and use it to formulate and solve data allocation problems for distributed database systems based on (query-site and move-small) query execution strategies. We show that an optimal solution can be achieved when the query-site query execution strategy is employed, and for the move-small query execution strategy we performed experimental evaluation about the effectiveness of a hillclimbing heuristic algorithm in achieving a near-optimal soluti...

Scope and Purpose-The two-level hierarchical network structure with the upper level hub-ring and the lower level star-type connections is found in a wide variety of application areas such as communications, transportation, physical distribution, etc. Topological design of such networks, despite its practical importance, has not been effectively dealt with in the literature, owing to the associated computations complexity. This work is inspired by some recent successes of other network design studies which incorporate the dual-based approach in a unified framework different from the conventional approach of partitioning the whole problem into two easy subprob~ems. The design problem is formulated into a mixed O-l integer programming model in such a way that its special structure can be exploited to deveiop an efficient dual-based heuristic. The computational experience with the heuristic strongly suggests that it is effective enough to be applicable even to fairly large real-world network problems. Abstract-This paper deals with topological design of a hie~rchical two-levef network where the upper-level hub network is of ring type and the lower-level local access networks are of star-type. The problem is modeled as a mixed 0- 1 integer programming, the special structure of which is exploited for the development of a dual-based lower bounding procedure. A heuristic procedure is developed to construct a primal feasible solution from the dual solution obtained by the dual procedure. The performance of our method is well demonstrated by the computational experiments conducted with a variety of test problems ranging up to 20 hub nodes and 50 user nodes. 1.

this paper, we considered the multi-resource generalized assignment problem and proposed a tabu search algorithm in which a sophisticated neighborhood called the chained shift neighborhood is used. It was confirmed through computational comparisons on benchmark instances that the method is e#ective, especially for type D and E instances, which are known to be very di#cult