Issues in storage and retrieval of multimedia data

1995 ◽  
Vol 3 (5-6) ◽  
pp. 298-304 ◽  
Author(s):  
T. L. Kunii ◽  
Y. Shinagawa ◽  
R. M. Paul ◽  
M. F. Khan ◽  
A. A. Khokhar
Keyword(s):  
Multimedia Data ◽  
Storage And Retrieval

Efficient Share Generator for Slicing and Securely Retrieving the Cloud-Hosted Heterogeneous Multimedia Data

2021 ◽  
pp. 20-32
Author(s):  
admin admin ◽  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
Implementation Strategies ◽  
Critical Issue ◽  
Multimedia Data ◽  
Storage And Retrieval ◽  
Remote Storage ◽  
Source Transformation ◽  
Cloud Servers

Recently, the security of heterogeneous multimedia data becomes a very critical issue, substantially with the proliferation of multimedia data and applications. Cloud computing is the hidden back-end for storing heterogeneous multimedia data. Notwithstanding that using cloud storage is indispensable, but the remote storage servers are untrusted. Therefore, one of the most critical challenges is securing multimedia data storage and retrieval from the untrusted cloud servers. This paper applies a Shamir Secrete-Sharing scheme and integrates with cloud computing to guarantee efficiency and security for sensitive multimedia data storage and retrieval. The proposed scheme can fully support the comprehensive and multilevel security control requirements for the cloud-hosted multimedia data and applications. In addition, our scheme is also based on a source transformation that provides powerful mutual interdependence in its encrypted representation—the Share Generator slices and encrypts the multimedia data before sending it to the cloud storage. The extensive experimental evaluation on various configurations confirmed the effectiveness and efficiency of our scheme, which showed excellent performance and compatibility with several implementation strategies.

PDSRS: An attribute based approach for multimedia data storage and retrieval

2011 ◽  
pp. 119-122
Author(s):  
Sonali Ajankar ◽  
Sanjay Nalbalwar ◽  
Z. A. Usmani
Keyword(s):  
Data Storage ◽  
Multimedia Data ◽  
Storage And Retrieval

scholarly journals MINIMIZING LATENCY AND JITTER FOR LARGE-SCALE MULTIMEDIA REPOSITORIES THROUGH PREFIX CACHING

2003 ◽  
Vol 03 (01) ◽  
pp. 95-117 ◽  
Author(s):  
SUNIL PRABHAKAR ◽  
RAHUL CHARI
Keyword(s):  
Large Scale ◽  
Data Access ◽  
Multimedia Data ◽  
Secondary Storage ◽  
Storage And Retrieval ◽  
Multiple User ◽  
Large Size ◽  
Tertiary Storage ◽  
Hierarchical Storage ◽  
Access Patterns

Multimedia data poses challenges for efficient storage and retrieval due to its large size and playback timing requirements. For applications that store very large volumes of multimedia data, hierarchical storage offers a scalable and economical alternative to store data on magnetic disks. In a hierarchical storage architecture data is stored on a tape or optical disk based tertiary storage layer with the secondary storage disks serving as a cache or buffer. Due to the need for swapping media on drives, retrieving multimedia data from tertiary storage can potentially result in large delays before playback (startup latency) begins as well as during playback (jitter). In this paper we address the important problem of reducing startup latency and jitter for very large multimedia repositories. We propose that secondary storage should not be used as a cache in the traditional manner — instead, most of the secondary storage should be used to permanently store partial objects. Furthermore, replication is employed at the tertiary storage level to avoid expensive media switching. In particular, we show that by saving the initial segments of documents permanently on secondary storage, and replicating them on tertiary storage, startup latency can be significantly reduced. Since we are effectively reducing the amount of secondary storage available for buffering the data from tertiary storage, an increase in jitter may be expected. However, our results show that the technique also reduces jitter, in contrast to the expected behavior. Our technique exploits the pattern of data access. Advance knowledge of the access pattern is helpful, but not essential. Lack of this information or changes in access patterns are handled through adaptive techniques. Our study addresses both single- and multiple-user scenarios. Our results show that startup latency can be reduced by as much as 75% and jitter practically eliminated through the use of these techniques.

scholarly journals Association-Based Image Retrieval

2011 ◽  
pp. 379-406
Author(s):  
Arun Kulkarni ◽  
Leonard Brown
Keyword(s):  
Image Retrieval ◽  
Relevance Feedback ◽  
Human Perception ◽  
Human Memory ◽  
Image Features ◽  
Multimedia Data ◽  
Query Image ◽  
Storage And Retrieval ◽  
Image Storage And Retrieval ◽  
High Level

With advances in computer technology and the World Wide Web there has been an explosion in the amount and complexity of multimedia data that are generated, stored, transmitted, analyzed, and accessed. In order to extract useful information from this huge amount of data, many content-based image retrieval (CBIR) systems have been developed in the last decade. A Typical CBIR system captures image features that represent image properties such as color, texture, or shape of objects in the query image and try to retrieve images from the database with similar features. Recent advances in CBIR systems include relevance feedback based interactive systems. The main advantage of CBIR systems with relevance feedback is that these systems take into account the gap between the high-level concepts and low-level features and subjectivity of human perception of visual content. CBIR systems with relevance feedback are more efficient than conventional CBIR systems; however, these systems depend on human interaction. In this chapter, we describe a new approach for image storage and retrieval called association-based image retrieval (ABIR). The authors try to mimic human memory. The human brain stores and retrieves images by association. They use a generalized bi-directional associative memory (GBAM) to store associations between feature vectors that represent images stored in the database. Section I introduces the reader to the CBIR system. In Section II, they present architecture for the ABIR system, Section III deals with preprocessing and feature extraction techniques, and Section IV presents various models of GBAM. In Section V, they present case studies.

CONTENT-BASED RETRIEVAL OF MULTIMEDIA INFORMATION

2001 ◽  
Vol 01 (01) ◽  
pp. 83-91 ◽  
Author(s):  
DAGAN (DAVID) FENG
Keyword(s):  
Information Technology ◽  
Signal Processing ◽  
Multimedia Information ◽  
Information Management ◽  
Data Storage ◽  
Video Retrieval ◽  
Multimedia Data ◽  
Content Based Retrieval ◽  
Storage And Retrieval ◽  
Research Activities

The recent information explosion has led to massively increased demand for multimedia data storage and retrieval techniques. Content-based retrieval is an important alternative and complement to the traditional keyword-based searching for multimedia data and can greatly enhance information management. For the last ten years, the Biomedical and Multimedia Information Technology (BMIT) Group and recently the Center for Multimedia Signal Processing (CMSP) have conducted systematic studies and research activities on this topic. Some of the works relating to content-based image/video retrieval and their applications are briefly presented in this paper.

Mobile Exam System – MES

2012 ◽  
pp. 1-20 ◽  
Author(s):  
Joan Lu ◽  
Aswin Sundaram ◽  
Zhaozong Meng ◽  
Priya A ◽  
Gehao Lu ◽  
...  
Keyword(s):  
Data Storage ◽  
Database Management ◽  
Evaluation System ◽  
Rapid Development ◽  
Database Management System ◽  
Student Response ◽  
Multimedia Data ◽  
Student Response System ◽  
Storage And Retrieval ◽  
Exam System

As the mobile applications are constantly facing a rapid development in the recent years especially in the academic environment such as student response system (Lópeza, Royoa, Labordab, & Calvoa, 2009; Ngai & Gunasekaran, 2007; Mary & Biju, 2008; Nayak & Erinjeri, 2008; Roth, Ivanchenko, & Record, 2008; Lu, Stav, & Pein, 2009; Lu, 2009; Turning Technologies, 2010) used in universities and other educational institutions; However, an effective and scalable Database Management System to support fast and reliable data storage and retrieval is missing. This paper presents Database Management Architecture for an Innovative Evaluation System based on Mobile Learning Applications. The need for a relatively stable, independent, and extensible data model for faster data storage and retrieval is analyzed and investigated. Finally a case study to prove the concept of the urgent need for the system is proposed. It concludes that the system is important by emphasizing further investigation to support multimedia data types, such as video clips, images and documents in near future.

Data Management in Three-Dimensional Structures

2011 ◽  
pp. 228-232
Author(s):  
Xiong Wang
Keyword(s):  
Data Mining ◽  
Data Management ◽  
Pattern Discovery ◽  
Three Dimensional ◽  
Nearest Neighbor Search ◽  
Multimedia Data ◽  
Frequent Pattern ◽  
Search Range ◽  
Storage And Retrieval ◽  
Neighbor Search

Data management in its general term refers to activities that involve the acquisition, storage, and retrieval of data. Traditionally, information retrieval is facilitated through queries, such as exact search, nearest neighbor search, range search, etc. In the last decade, data mining has emerged as one of the most dynamic fields in the frontier of data management. Data mining refers to the process of extracting useful knowledge from the data. Popular data mining techniques include association rule discovery, frequent pattern discovery, classification, and clustering. In this chapter, we discuss data management in a specific type of data i.e., three-dimensional structures. While research on text and multimedia data management has attracted considerable attention and substantial progress has been made, data management in three-dimensional structures is still in its infancy (Castelli & Bergman, 2001; Paquet & Rioux, 1999). Data management in 3D structures raises several interesting problems: 1. Similarity search 2. Pattern discovery 3. Classification 4. Clustering

Indirect measurements in micro-space with the EM

1995 ◽  
Vol 53 ◽  
pp. 598-599
Author(s):  
Sterling P. Newberry
Keyword(s):  
Electron Microscope ◽  
Standard Model ◽  
Particle Physics ◽  
Information Storage ◽  
Storage Space ◽  
Indirect Measurements ◽  
Storage And Retrieval ◽  
Adequate Information ◽  
Compelling Reason ◽  
The Standard Model

At the 1958 meeting of our society, then known as EMSA, the author introduced the concept of microspace and suggested its use to provide adequate information storage space and the use of electron microscope techniques to provide storage and retrieval access. At this current meeting of MSA, he wishes to suggest an additional use of the power of the electron microscope.The author has been contemplating this new use for some time and would have suggested it in the EMSA fiftieth year commemorative volume, but for page limitations. There is compelling reason to put forth this suggestion today because problems have arisen in the “Standard Model” of particle physics and funds are being greatly reduced just as we need higher energy machines to resolve these problems. Therefore, any techniques which complement or augment what we can accomplish during this austerity period with the machines at hand is worth exploring.

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