Utility Maximization for Multimedia Data Dissemination in Large-Scale VANETs

2017 ◽  
Vol 16 (4) ◽  
pp. 1188-1198 ◽  
Author(s):  
Min Xing ◽  
Jianping He ◽  
Lin Cai
Keyword(s):  
Utility Maximization ◽  
Large Scale ◽  
Data Dissemination ◽  
Multimedia Data

scholarly journals Utility Maximization for Large-Scale Cell-Free Massive MIMO Downlink

2021 ◽  
pp. 1-1
Author(s):  
Muhammad Farooq ◽  
Hien Quoc Ngo ◽  
Een-Kee Hong ◽  
Le-Nam Tran
Keyword(s):  
Massive Mimo ◽  
Utility Maximization ◽  
Large Scale ◽  
Mimo Downlink

Delay Minimization for Data Dissemination in Large-Scale VANETs with Buses and Taxis

2016 ◽  
Vol 15 (8) ◽  
pp. 1939-1950 ◽  
Author(s):  
Jianping He ◽  
Lin Cai ◽  
Peng Cheng ◽  
Jianping Pan
Keyword(s):  
Large Scale ◽  
Data Dissemination ◽  
Delay Minimization

scholarly journals Temporal Activity Path Based Character Correction in Heterogeneous Social Networks via Multimedia Sources

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Large Scale ◽  
Multimedia Data ◽  
Attribute Information ◽  
Novel Method ◽  
Relationship Network ◽  
Heterogeneous Social Networks ◽  
The Relationship ◽  
Over Time

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

2013 ◽  
Vol 68 (1) ◽  
pp. 488-507 ◽  
Author(s):  
Wei Kuang Lai ◽  
Yi-Uan Chen ◽  
Tin-Yu Wu ◽  
Mohammad S. Obaidat
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Multimedia Data ◽  
Hadoop Platform

An Energy-Efficient Data Dissemination Scheme in Large-Scale Wireless Sensor Networks

2013 ◽  
Vol 5 (3) ◽  
pp. 34-54
Author(s):  
Shiow-Fen Hwang ◽  
Han-Huei Lin ◽  
Chyi-Ren Dow
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Storage ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Dissemination ◽  
Wireless Sensor ◽  
Event Data ◽  
Efficient Data

In wireless sensor networks, due to limited energy, how to disseminate the event data in an energy-efficient way to allow sinks quickly querying and receiving the needed event data is a practical and important issue. Many studies about data dissemination have been proposed. However, most of them are not energy-efficient, especially in large-scale networks. Hence, in this paper the authors proposed an energy-efficient data dissemination scheme in large-scale wireless sensor networks. First, the authors design a data storage method which disseminates only a few amount event data by dividing the network into regions and levels, and thus reducing the energy consumption. Then, the authors develop an efficient sink query forwarding strategy by probability analysis so that a sink can query events easily according to its location to reduce the delay time of querying event data, as well as energy consumption. In addition, a simple and efficient maintenance mechanism is also provided. The simulation results show that the proposed scheme outperforms TTDD and LBDD in terms of the energy consumption and control overhead.

Data Dissemination in Mobile Environments

2011 ◽  
pp. 38-48
Author(s):  
Panayotis Fouliras
Keyword(s):  
Video Streaming ◽  
Data Dissemination ◽  
Multimedia Data ◽  
P2p Network ◽  
Mobile Environments ◽  
Mobile Environment ◽  
Advantages And Disadvantages ◽  
Relative Value ◽  
Additional Constraints

Data dissemination today represents one of the cornerstones of network-based services and even more so for mobile environments. This becomes more important for large volumes of multimedia data such as video, which have the additional constraints of speedy, accurate, and isochronous delivery often to thousands of clients. In this chapter, we focus on video streaming with emphasis on the mobile environment, first outlining the related issues and then the most important of the existing proposals employing a simple but concise classification. New trends are included such as overlay and p2p network-based methods. The advantages and disadvantages for each proposal are also presented so that the reader can better appreciate their relative value.

Interoperability in Internet of Media Things and Integration Big Media

2022 ◽  
pp. 59-79
Author(s):  
Dragorad A. Milovanovic ◽  
Vladan Pantovic
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Large Scale ◽  
Reference Model ◽  
Big Data Analytics ◽  
Multimedia Data ◽  
Data Sets ◽  
Large Scale Systems ◽  
New Class ◽  
Media Applications

Multimedia-related things is a new class of connected objects that can be searched, discovered, and composited on the internet of media things (IoMT). A huge amount of data sets come from audio-visual sources or have a multimedia nature. However, multimedia data is currently not incorporated in the big data (BD) frameworks. The research projects, standardization initiatives, and industrial activities for integration are outlined in this chapter. MPEG IoMT interoperability and network-based media processing (NBMP) framework as an instance of the big media (BM) reference model are explored. Conceptual model of IoT and big data integration for analytics is proposed. Big data analytics is rapidly evolving both in terms of functionality and the underlying model. The authors pointed out that IoMT analytics is closely related to big data analytics, which facilitates the integration of multimedia objects in big media applications in large-scale systems. These two technologies are mutually dependent and should be researched and developed jointly.

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