Assessing prime-time for geotargeting with mobile big data

2013 ◽  
Vol 1 (3) ◽  
pp. 174-183 ◽  
Author(s):  
Syagnik Banerjee ◽  
Vijay Viswanathan ◽  
Kalyan Raman ◽  
Hao Ying
Keyword(s):  
Big Data ◽  
Prime Time ◽  
Mobile Big Data

Assessing Prime-Time for Geotargeting with Mobile Big Data

2015 ◽  
Author(s):  
Syagnik (Sy) Banerjee ◽  
Vijay Viswanathan ◽  
Kalyan Raman ◽  
Hao Ying
Keyword(s):  
Big Data ◽  
Prime Time ◽  
Mobile Big Data

Mobile Big Data Query Based on Double R-Tree and Double Indexing

2013 ◽  
Vol 756-759 ◽  
pp. 916-921
Author(s):  
Ye Liang
Keyword(s):  
Big Data ◽  
Dynamic Condition ◽  
Index Structure ◽  
Limited Area ◽  
Universal Method ◽  
Mobile Objects ◽  
Data Query ◽  
Mobile Big Data ◽  
Structure Query ◽  
Window Query

The amount of data in our industry and the world is exploding. Data is being collected and stored at unprecedented rates. The challenge is not only to store and manage the vast volume of data, which is also called big data, but also to analyze and query from it. In order to put forward the universal method to response mobile big data query, queries are separated and grouped according to kinds of query for massive mobile objects in the space. The indexing method for grouping the mobile objects with Grid (GG TPR-tree) has great efficiency to manage a massive capacity of mobile objects within a limited area, but it only could meet a part of requirements for mobile big data query if the GG TPR-tree was used solely. This thesis offers solutions to simple immediate query, simple continuous query, active window query, and continuous window query, dynamic condition query and other query requests by employing DTDI index structure. The experiments prove that with the support of DTDI index structure, query of massive mobile objects has higher precision and better query performance.

Protecting lightweight block cipher implementation in mobile big data computing

2016 ◽  
Vol 11 (2) ◽  
pp. 252-264
Author(s):  
Weidong Qiu ◽  
Bozhong Liu ◽  
Can Ge ◽  
Lingzhi Xu ◽  
Xiaoming Tang ◽  
...  
Keyword(s):  
Big Data ◽  
Block Cipher ◽  
Mobile Big Data ◽  
Lightweight Block Cipher ◽  
Big Data Computing

Mobile Big Data

2016 ◽  
pp. 138-158
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Value Chain ◽  
Mobile Technologies ◽  
Complex Concept ◽  
Current Trends ◽  
Mobile Big Data ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Data Ecosystem

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.

Reality mining: A prediction algorithm for disease dynamics based on mobile big data

2017 ◽  
Vol 379 ◽  
pp. 82-93 ◽  
Author(s):  
Yuanfang Chen ◽  
Noel Crespi ◽  
Antonio M. Ortiz ◽  
Lei Shu
Keyword(s):  
Big Data ◽  
Prediction Algorithm ◽  
Disease Dynamics ◽  
Mobile Big Data ◽  
Reality Mining

Mobile Big Data: The Fuel for Data-Driven Wireless

2017 ◽  
Vol 4 (5) ◽  
pp. 1489-1516 ◽  
Author(s):  
Xiang Cheng ◽  
Luoyang Fang ◽  
Liuqing Yang ◽  
Shuguang Cui
Keyword(s):  
Big Data ◽  
Data Driven ◽  
Mobile Big Data

Mobile big data fault-tolerant processing for ehealth networks

IEEE Network ◽  
2016 ◽  
Vol 30 (1) ◽  
pp. 36-42 ◽  
Author(s):  
Kun Wang ◽  
Yun Shao ◽  
Lei Shu ◽  
Chunsheng Zhu ◽  
Yan Zhang
Keyword(s):  
Big Data ◽  
Fault Tolerant ◽  
Mobile Big Data
Sign in / Sign up

Export Citation Format

Share Document