Distributed DBA Abstract 2017

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The document proposes a scalable and efficient location database architecture for future mobile networks based on location-independent personal telecommunication numbers (PTNs). The proposed multi-tree database architecture consists of multiple database subsystems, each with a three-level tree structure connected only through the root. This architecture reduces database loads and signaling traffic by exploiting localized calling and mobility patterns. Two memory-resident indices are also proposed to further improve throughput. Analysis shows the architecture can effectively support high user densities in future mobile networks.

CreativeSoft (Corporate Office)
# 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016
Tel: +91-40-40159158
Mobile: 91-9247249455
Distributed DBA
ABSTRACT
The next-generation mobile network will support terminal mobility, personal mobility, and
service provider portability, making global roaming seamless. A location-independent personal
telecommunication number (PTN) scheme is conducive to implementing such a global mobile system.
However, the nongeographic PTNs coupled with the anticipated large number of mobile users in future
mobile networks may introduce very large centralized databases. This necessitates research into the
design and performance of high-throughput database technologies used in mobile systems to ensure
that future systems will be able to carry efficiently the anticipated loads. This project proposes a
scalable, robust, efficient location database architecture based on the location-
independent PTNs.
The proposed multitree database architecture consists of a number of database subsystems,
each of which is a three-level tree structure and is connected to the others only through its root. By
exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively
reduces the database loads as well as the signaling traffic incurred by the location registration and call
delivery procedures. In addition, two memory-resident database indices, memory-resident direct file
and
T-tree, are proposed for the location databases to further improve their throughput. Analysis
model and numerical results are presented to evaluate the efficiency of the proposed database
architecture. Results have revealed that the proposed database architecture for location management
can effectively support the anticipated
high user density in the future mobile networks.
EXISTING SYSTEM:

CreativeSoft (Corporate Office)
# 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016
Tel: +91-40-40159158
Mobile: 91-9247249455
In existing system different databases are used for each and every node. Here a node contains only their
own data and doesn’t search data of another nodes .Here the node can use their own data from a
particular database.

CreativeSoft (Corporate Office)
# 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016
Tel: +91-40-40159158
Mobile: 91-9247249455
PROPOSED SYSTEM:
The proposed multi-tree database architecture consists of a number of database subsystems,
each of which is a three-level tree structure and is connected to the others only through its root. By
exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively
reduces the database loads as well as the signaling traffic incurred by the location registration and call
delivery procedures. In addition, two memory-resident database indices, memory-resident direct file
and T-tree, are proposed for the location databases to further improve their throughput. Analysis model
and numerical results are presented to evaluate the efficiency of the proposed database architecture.
Results have revealed that the proposed database architecture for location management can effectively
support the anticipated high user density in the future mobile networks.
MODULES:
1. Network: Here we are using centralized database for constructing network. In this
Module we are using 3 different nodes for constructing network. After login each and
every node can use the data from the centralized database.
2. Search: Here 3 different nodes can search the data from centralized database. A node can
search the data from its own space if the file is not available it can also search others
nodes space.
System Requirement Specification:
Hardware Requirements
 Hard disk: - 80GB
 RAM: - 512MB
 Processor: - P V
Software Requirements

CreativeSoft (Corporate Office)
# 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016
Tel: +91-40-40159158
Mobile: 91-9247249455
 Operating Systems: WINDOWS NT 4 / 2000 / XP
 Technologies Used: Java,SWING, jdbc.
 Back End: MySql

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The document lists 59 research papers from 2006 to 2013 related to topics such as data mining, image processing, cloud computing, mobile computing, networking, and secure computing. The papers are from conferences and journals on topics including spatial queries, text classification, video retrieval, wireless systems modeling, and privacy-preserving data sharing. The document also provides contact information for S3 Infotech.

Survey on Privacy- Preserving Multi keyword Ranked Search over Encrypted Clou...

Editor IJMTER

The advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing.Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results. We first propose a basic MRSE scheme using secure inner product computation, and then significantly improve it to meet different privacy requirements in two levels of threat models. The Incremental High Utility Pattern Transaction Frequency Tree (IHUPTF-Tree) is designed according to the transaction frequency (descending order) of items to obtain a compact tree. By using high utility pattern the items can be arranged in an efficient manner. Tree structure is used to sort the items. Thus the items are sorted and frequent pattern is obtained. The frequent pattern items are retrieved from the database by using hybrid tree (H-Tree) structure. So the execution time becomes faster. Finally, the frequent pattern item that satisfies the threshold value is displayed.

Cooperative caching for efficient data access in disruption tolerant networks

LeMeniz Infotech

Cooperative caching for efficient data access in disruption tolerant networks Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. A novel approach is proposed to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduces data access delay.

A Comprehensive Study On Data Mining Process With Distribution

Lori Mitchell

This document discusses combining data mining processes with distribution. It proposes an architecture that involves gathering data from various sources, distributing it over a network using cloud computing, and allowing various types of users to query the data using DMQL. A converter is needed to transform queries to the appropriate format for mining. Combining distribution with mining provides benefits like accessing data from multiple sources and serving different user levels, but also introduces complexities in locating data and transforming formats.

Enabling Secure and Efficient Multi-Keyword Ranked Search Scheme

IRJET Journal

This document proposes a secure and efficient multi-keyword ranked search scheme over encrypted cloud data. It utilizes a tree-based index structure and "Greedy Depth-first Search" algorithm to enable sub-linear search times. The scheme supports dynamic insertion and deletion of documents without privacy leakage. It uses a secure k-Nearest Neighbor algorithm to encrypt index and query vectors, allowing accurate relevance scoring between encrypted vectors. The scheme aims to provide secure, efficient, and accurate multi-keyword ranked search and dynamic updates over outsourced encrypted data in the cloud.

BigData Analysis

Innfinision Cloud and BigData Solutions

This document provides an overview of big data analysis tools and methods presented by Ehsan Derakhshan of innfinision. It discusses what data and big data are, important questions about database selection, and several tools and solutions offered by innfinision including MongoDB, PyTables, Blosc, and Blaze. MongoDB is highlighted as a scalable and high performance document database. The advantages of these tools include optimized memory usage, rich queries, fast updates, and the ability to analyze and optimize queries.

MS Word file resumes16869r.doc.doc

butest

This document provides a summary of a candidate's skills and work experience for a position in analytics, data mining, and machine learning. The candidate has over 15 years of experience in data analysis, machine learning, artificial intelligence, and developing predictive models. They have extensive experience developing fraud detection models for credit cards and other domains. They also have a PhD in Computer Science and have published papers in conferences on topics like decision trees and feature selection.

Grid and cluster_computing_chapter1

Bharath Kumar

Grid computing allows for the sharing of distributed computing resources over a network. It provides users with access to high-end computing facilities in a dependable, consistent, and inexpensive manner. A grid aggregates distributed computing power to solve large-scale problems. It enables virtual organizations through coordinated sharing of resources across locations, organizations, and hardware/software boundaries. Grid computing provides computational utility to consumers by managing resource identification, allocation, and consolidation through middleware software. It allows under-utilized resources to be dynamically distributed in an equitable manner.

ICT L5+.pptx

AssemNazirova2

1. The document discusses key concepts related to database systems including the definition of a database, database management systems (DBMS), data models, database classification, data integrity, query optimization, structured query language (SQL), parallel databases, and object-relational mapping (ORM). 2. It provides details on common data models like hierarchical, network, and relational models. It also describes concepts like database architecture, data definition language, data manipulation language, and distributed databases. 3. Control questions are provided at the end to test understanding of database concepts like the difference between a database and data set, components of a database system, and main elements of a database.

Mobile Data Analytics

RICHARD AMUOK

This document discusses mobile data analytics and big data analysis using cloud computing. It introduces how massive amounts of data are generated from mobile devices and networks. Big data analysis tools like Hadoop, Spark and Storm are described for processing large datasets. Challenges of mobile big data analytics include limited device resources and connectivity. The document discusses how cloud computing addresses these issues by providing scalable infrastructure and handling computation and storage remotely. It also covers security considerations for cloud-based mobile analytics.

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Dotnet ieee titles 2013 14

Survey on Privacy- Preserving Multi keyword Ranked Search over Encrypted Clou...

Cooperative caching for efficient data access in disruption tolerant networks

A Comprehensive Study On Data Mining Process With Distribution

Enabling Secure and Efficient Multi-Keyword Ranked Search Scheme

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Distributed DBA Abstract 2017

1. CreativeSoft (Corporate Office) # 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016 Tel: +91-40-40159158 Mobile: 91-9247249455 Distributed DBA ABSTRACT The next-generation mobile network will support terminal mobility, personal mobility, and service provider portability, making global roaming seamless. A location-independent personal telecommunication number (PTN) scheme is conducive to implementing such a global mobile system. However, the nongeographic PTNs coupled with the anticipated large number of mobile users in future mobile networks may introduce very large centralized databases. This necessitates research into the design and performance of high-throughput database technologies used in mobile systems to ensure that future systems will be able to carry efficiently the anticipated loads. This project proposes a scalable, robust, efficient location database architecture based on the location- independent PTNs. The proposed multitree database architecture consists of a number of database subsystems, each of which is a three-level tree structure and is connected to the others only through its root. By exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively reduces the database loads as well as the signaling traffic incurred by the location registration and call delivery procedures. In addition, two memory-resident database indices, memory-resident direct file and T-tree, are proposed for the location databases to further improve their throughput. Analysis model and numerical results are presented to evaluate the efficiency of the proposed database architecture. Results have revealed that the proposed database architecture for location management can effectively support the anticipated high user density in the future mobile networks. EXISTING SYSTEM:

2. CreativeSoft (Corporate Office) # 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016 Tel: +91-40-40159158 Mobile: 91-9247249455 In existing system different databases are used for each and every node. Here a node contains only their own data and doesn’t search data of another nodes .Here the node can use their own data from a particular database.

3. CreativeSoft (Corporate Office) # 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016 Tel: +91-40-40159158 Mobile: 91-9247249455 PROPOSED SYSTEM: The proposed multi-tree database architecture consists of a number of database subsystems, each of which is a three-level tree structure and is connected to the others only through its root. By exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively reduces the database loads as well as the signaling traffic incurred by the location registration and call delivery procedures. In addition, two memory-resident database indices, memory-resident direct file and T-tree, are proposed for the location databases to further improve their throughput. Analysis model and numerical results are presented to evaluate the efficiency of the proposed database architecture. Results have revealed that the proposed database architecture for location management can effectively support the anticipated high user density in the future mobile networks. MODULES: 1. Network: Here we are using centralized database for constructing network. In this Module we are using 3 different nodes for constructing network. After login each and every node can use the data from the centralized database. 2. Search: Here 3 different nodes can search the data from centralized database. A node can search the data from its own space if the file is not available it can also search others nodes space. System Requirement Specification: Hardware Requirements  Hard disk: - 80GB  RAM: - 512MB  Processor: - P V Software Requirements

4. CreativeSoft (Corporate Office) # 412, Annpurna Block, Aditya Enclave, Ameerpet, Hyderabad – 500016 Tel: +91-40-40159158 Mobile: 91-9247249455  Operating Systems: WINDOWS NT 4 / 2000 / XP  Technologies Used: Java,SWING, jdbc.  Back End: MySql

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