Data declustering speeds up large data set retrieval by partitioning the data across multiple disks or sites and performing retrievals in parallel. Performance is determined by how the data is broken into ”buckets” and how the buckets are assigned to disks. While some work has been done for declustering uniformly distributed low dimensional data, little work has been done on declustering non-un...

In today’s world of computers, dealing with huge amounts of data is not unusual. The need to distribute this data in order to increase its availability and increase the performance of accessing it is more urgent than ever. For these reasons it is necessary to develop scalable distributed data structures. In this paper we propose EH , a distributedvariant of the Extendible Hashing data structure...

Association Rule Mining (ARM) finds the interesting relationship between presences of various items in a given database. Apriori is the traditional algorithm for learning association rules. However, it is affected by number of database scan and higher generation of candidate itemsets. Each level of candidate itemsets requires separate memory locations. Hash Based Frequent Itemsets Quadratic Pro...

This paper describes a generic algorithm for concurrent resizing and on-demand per-bucket rehashing for an extensible hash table. In contrast to known lock-based hash table algorithms, the proposed algorithm separates the resizing and rehashing stages so that they neither invalidate existing buckets nor block any concurrent operations. Instead, the rehashing work is deferred and split across su...

Aedes albopictus, a species known to transmit dengue and chikungunya viruses, is primarily a container-inhabiting mosquito. The potential for pathogen transmission by Ae. albopictus has increased our need to understand its ecology and population dynamics. Two parameters that we know little about are the impact of direct density-dependence and delayed density-dependence in the larval stage. The ...

Selectivity estimation of queries is of critical importance to query optimization. In order to get accurate estimations, database management systems must maintain statistics to capture the underlying data distribution. Histograms are extensively used in commercial database systems for this purpose. Most current histogram techniques make the assumption that all values in a single bucket appear w...

A novel access structure for similarity search in metric data, called Similarity Hashing (SH), is proposed. Its multi-level hash structure of separable buckets on each level supports easy insertion and bounded search costs, because at most one bucket needs to be accessed at each level for range queries up to a pre-de ned value of search radius. At the same time, the number of distance computati...

The product of research projects is information. Through the life cycle of a project, information comes from many sources and takes many forms. Traditionally, this body of information is summarized in a formal publication, typically a journal article. While formal publications enjoy the benefits of peer review and technical editing, they are also often compromises in media format and length. As...

From a hardware standpoint a heterogeneous architecture such as an SIMD array coupled onto a MIMD system, will yield a powerful solution for real time embedded vision tasks. From a software standpoint there is a need to approach this heterogeneous system in a homogeneous way. We investigated the feasibility of a uniform parallel programming approach on a heterogeneous machine. Using the paralle...