How good can databases deal with Netflow data?

Abarca Ortiz, E. (2011). How good can databases deal with Netflow data?. http://hdl.handle.net/10251/14798.Archivo delegad

Towards a Scalable Dynamic Spatial Database System

With the rise of GPS-enabled smartphones and other similar mobile devices, massive amounts of location data are available. However, no scalable solutions for soft real-time spatial queries on large sets of moving objects have yet emerged. In this paper we explore and measure the limits of actual algorithms and implementations regarding different application scenarios. And finally we propose a novel distributed architecture to solve the scalability issues.Comment: (2012

SecureDBaaS Model for Accessing Encrypted Cloud Databases

Cloud computing has recently emerged being a compelling paradigm that pertains to managing and delivering services over the web. The particular prevalent problem connected with cloud is confidentiality, security, as well as reliability etc., in which how the cloud provider assures. To recognize this, a novel architecture is usually introduced that will integrates cloud database services and as well executing concurrent operations on encrypted information. Also a new homomorphic encryption algorithm will likely be incorporated to offer confidentiality as well as concurrent execution of various SQL operations. This will be the first option supporting quite a few stributed clienteles to access encrypted cloud databases. One of main thing is that it eliminates advanced proxies in between cloud user and provider. The performance on the architecture is usually lculated by means of theoretical and practical results which are subjected to TPC-C benchmark standard tools for a number of clients as well as network latencies

AT-GIS: highly parallel spatial query processing with associative transducers

Users in many domains, including urban planning, transportation, and environmental science want to execute analytical queries over continuously updated spatial datasets. Current solutions for largescale spatial query processing either rely on extensions to RDBMS, which entails expensive loading and indexing phases when the data changes, or distributed map/reduce frameworks, running on resource-hungry compute clusters. Both solutions struggle with the sequential bottleneck of parsing complex, hierarchical spatial data formats, which frequently dominates query execution time. Our goal is to fully exploit the parallelism offered by modern multicore CPUs for parsing and query execution, thus providing the performance of a cluster with the resources of a single machine. We describe AT-GIS, a highly-parallel spatial query processing system that scales linearly to a large number of CPU cores. ATGIS integrates the parsing and querying of spatial data using a new computational abstraction called associative transducers(ATs). ATs can form a single data-parallel pipeline for computation without requiring the spatial input data to be split into logically independent blocks. Using ATs, AT-GIS can execute, in parallel, spatial query operators on the raw input data in multiple formats, without any pre-processing. On a single 64-core machine, AT-GIS provides 3× the performance of an 8-node Hadoop cluster with 192 cores for containment queries, and 10× for aggregation queries

Clustering Techniques : A solution for e-business

The purpose of this thesis was to provide the best clustering solution for the Archipelago web site project which would have been part of the Central Baltic Intereg IV programme 2007-2013. The entire program is a merger between the central Baltic regions of Finland, including the Åland Islands, Sweden and Estonia. A literature review of articles and research on various clustering techniques for the different sections of the project led to the findings of this document. Clustering was needed for web servers and the underlying database implementation. Additionally, the operating system used for all servers in both sections was required to present the best clustering solution. Implementing OSI layer 7 clustering for the web server cluster, MySQL database clustering and using Linux operating system would have provided the best solution for the Archipelago website. This implementation would have provided unlimited scalability, availability and high performance for the web site. Also, it is the most cost effective solution because it would utilize the commodity hardware