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Future Internet, Volume 11, Issue 12

December 2019 - 18 articles

Cover Story: The avalanche of multimedia data published in online social networks poses serious challenges to researchers seeking to analyze such data for many different tasks, e.g., suspicious people/object detection, or dangerous event recognition. For such tasks, the classical “batch” approach of big data analysis is not suitable, due to constraints of real-time processing. This has led to the rise of stream processing big data platforms that are able to process data with a very low latency. However, this complicates the task of data analysis, since any implementation has to deal with the technicalities of such platforms. The RAM3S framework helps users to easily implement a variety of applications, being independent of details specific to the underlying stream processing big data engine.View this paper.
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Articles (18)

  • Article
  • Open Access
5 Citations
3,930 Views
16 Pages

9 December 2019

The text data of the social network platforms take the form of short texts, and the massive text data have high-dimensional and sparse characteristics, which does not make the traditional clustering algorithm perform well. In this paper, a new commun...

  • Article
  • Open Access
9 Citations
4,239 Views
18 Pages

5 December 2019

Static multi-controller deployment architecture cannot adapt to the drastic changes of network traffic, which will lead to a load imbalance between controllers, resulting in a high packet loss rate, high latency, and other network performance degrada...

  • Article
  • Open Access
3 Citations
4,534 Views
12 Pages

A Method of Node Layout of a Complex Network Based on Community Compression

  • Chengxiang Liu,
  • Wei Xiong,
  • Xitao Zhang and
  • Zheng Liu

2 December 2019

As the theory of complex networks is further studied, the scale of nodes in the network is increasing, which makes it difficult to find useful patterns from only the analysis of nodes. Therefore, this paper proposes a complex network node layout meth...

  • Article
  • Open Access
20 Citations
6,206 Views
15 Pages

Secure WiFi-Direct Using Key Exchange for IoT Device-to-Device Communications in a Smart Environment

  • Zakariae Belghazi,
  • Nabil Benamar,
  • Adnane Addaim and
  • Chaker Abdelaziz Kerrache

2 December 2019

With the rapid growth of Internet of Things (IoT) devices around the world, thousands of mobile users share many data with each other daily. IoT communication has been developed in the past few years to ensure direct connection among mobile users. Ho...

  • Article
  • Open Access
11 Citations
5,187 Views
16 Pages

29 November 2019

The avalanche of (both user- and device-generated) multimedia data published in online social networks poses serious challenges to researchers seeking to analyze such data for many different tasks, like recommendation, event recognition, and so on. F...

  • Article
  • Open Access
2 Citations
4,011 Views
24 Pages

Performance Analysis of On-Demand Scheduling with and without Network Coding in Wireless Broadcast

  • G. G. Md. Nawaz Ali,
  • Victor C. S. Lee,
  • Yuxuan Meng,
  • Peter H. J. Chong and
  • Jun Chen

26 November 2019

On-demand broadcast is a scalable approach to disseminating information to a large population of clients while satisfying dynamic needs of clients, such as in vehicular networks. However, in conventional broadcast approaches, only one data item can b...

  • Article
  • Open Access
16 Citations
4,972 Views
11 Pages

22 November 2019

Accurate prediction of bus arrival times is a challenging problem in the public transportation field. Previous studies have shown that to improve prediction accuracy, more heterogeneous measurements provide better results. So what other factors shoul...

  • Article
  • Open Access
23 Citations
5,149 Views
13 Pages

20 November 2019

Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict these changes,...

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Future Internet - ISSN 1999-5903