Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.1
2.8
Journals
Future Internet
Special Issues
Information Processing and Management for Large and Complex Networks
share announcement

Information Processing and Management for Large and Complex Networks

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 11619

Special Issue Editors

Dr. Fabrizio Montecchiani

E-Mail Website
Guest Editor
Department of Engineering, University of Perugia, 06125 Perugia, Italy
Interests: network visualization and visual analytic; large-scale graph processing; graph drawing and computational geometry; algorithm engineering
Prof. Dr. Walter Didimo

E-Mail Website
Guest Editor
Department of Engineering, University of Perugia, 06121 Perugia, Italy
Interests: graph drawing; information visualization; computational geometry; algorithm engineering
Dr. Andrea Fronzetti Colladon

E-Mail Website
Guest Editor
Department of Engineering, University of Perugia , 06121 Perugia, Italy
Interests: big data; creativity and innovation management; social network analysis; semantic analysis

Special Issue Information

Dear Colleagues,

Network-based models are pervasive in many fields of science and technology, as they naturally capture relationships between entities. The study of relationships emerged as a pivotal addition to standard social and behavioral research, going beyond the single attributes of the social units. Indeed, networks (or graphs) are widely used to model relational data in a variety of application domains, including social sciences, economy and finance, information and homeland security, management, biology, computer networks, marketing, and software design. With the increasing amount of relational data generated every day, processing, managing, and analyzing large-scale graphs have become prominent problems in data science, which pose several challenges ranging from the design of efficient graph algorithms to the development of scalable and effective systems. 

This special issue calls for papers that contribute to the multifaceted research on processing, managing, and analyzing large and complex networks. Interested authors are invited to contribute their original, unpublished work. Topics of interest include, but are not limited to, the following: 

  • Management information systems
  • Big network data management
  • Large-scale graph processing algorithms and systems
  • Parallel and distributed graph algorithms
  • Strategic information systems
  • Decision support systems
  • Graph drawing and network visualization techniques
  • Human-computer interaction for network analysis
  • Graph benchmarks and generators

Dr. Fabrizio Montecchiani
Prof. Dr. Walter Didimo
Dr. Andrea Fronzetti Colladon
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 387 KiB  
Article
Megalos: A Scalable Architecture for the Virtualization of Large Network Scenarios
by Mariano Scazzariello, Lorenzo Ariemma, Giuseppe Di Battista and Maurizio Patrignani
Future Internet 2021, 13(9), 227; https://doi.org/10.3390/fi13090227 - 30 Aug 2021
Cited by 7 | Viewed by 4252
Abstract
We introduce an open-source, scalable, and distributed architecture, called Megalos, that supports the implementation of virtual network scenarios consisting of virtual devices (VDs) where each VD may have several Layer 2 interfaces assigned to virtual LANs. We rely on Docker containers to realize [...] Read more.
We introduce an open-source, scalable, and distributed architecture, called Megalos, that supports the implementation of virtual network scenarios consisting of virtual devices (VDs) where each VD may have several Layer 2 interfaces assigned to virtual LANs. We rely on Docker containers to realize vendor-independent VDs and we leverage Kubernetes for the management of the nodes of a distributed cluster. Our architecture does not require platform-specific configurations and supports a seamless interconnection between the virtual environment and the physical one. Also, it guarantees the segregation of each virtual LAN traffic from the traffic of other LANs, from the cluster traffic, and from Internet traffic. Further, a packet is only sent to the cluster node containing the recipient VD. We produce several example applications where we emulate large network scenarios, with thousands of VDs and LANs. Finally, we experimentally show the scalability potential of Megalos by measuring the overhead of the distributed environment and of its signaling protocols. Full article
(This article belongs to the Special Issue Information Processing and Management for Large and Complex Networks)
►▼ Show Figures

Figure 1

31 pages, 997 KiB  
Article
Two-Layer Network Caching for Different Service Requirements
by Gianluca Reali and Mauro Femminella
Future Internet 2021, 13(4), 85; https://doi.org/10.3390/fi13040085 - 27 Mar 2021
Cited by 3 | Viewed by 2769
Abstract
Network caching is a technique used to speed-up user access to frequently requested contents in complex data networks. This paper presents a two-layer overlay network caching system for content distribution. It is used to define some caching scenarios with increasing complexity, which refers [...] Read more.
Network caching is a technique used to speed-up user access to frequently requested contents in complex data networks. This paper presents a two-layer overlay network caching system for content distribution. It is used to define some caching scenarios with increasing complexity, which refers to real situations, including mobile 5G connectivity. For each scenario our aim is to maximize the hit ratio, which leads to the formulation of NP-complete optimization problems. The heuristic solutions proposed are based on the theory of the maximization of monotone submodular functions under matroid constraints. After the determination of the approximation ratio of the greedy heuristic algorithms proposed, a numerical performance analysis is shown. This analysis includes a comparison with the Least-Frequently Used (LFU) eviction strategy adapted to the analyzed systems. Results show very good performance, under the hypotheses of either known or unknown popularity of contents. Full article
(This article belongs to the Special Issue Information Processing and Management for Large and Complex Networks)
►▼ Show Figures

Figure 1

13 pages, 1555 KiB  
Article
E-Mail Network Patterns and Body Language Predict Risk-Taking Attitude
by Jiachen Sun and Peter Gloor
Future Internet 2021, 13(1), 17; https://doi.org/10.3390/fi13010017 - 14 Jan 2021
Cited by 2 | Viewed by 3221
Abstract
As the Enron scandal and Bernie Madoff’s pyramid scheme have shown, individuals’ attitude towards ethical risks can have a huge impact on society at large. In this paper, we compare risk-taking attitudes assessed with the Domain-Specific Risk-Taking (DOSPERT) survey with individual e-mail networking [...] Read more.
As the Enron scandal and Bernie Madoff’s pyramid scheme have shown, individuals’ attitude towards ethical risks can have a huge impact on society at large. In this paper, we compare risk-taking attitudes assessed with the Domain-Specific Risk-Taking (DOSPERT) survey with individual e-mail networking patterns and body language measured with smartwatches. We find that e-mail communication signals such as network structure and dynamics, and content features as well as real-world behavioral signals measured through a smartwatch such as heart rate, acceleration, and mood state demonstrate a strong correlation with the individuals’ risk-preference in the different domains of the DOSPERT survey. For instance, we found that people with higher degree centrality in the e-mail network show higher likelihood to take social risks, while using language expressing a “you live only once” attitude indicates lower willingness to take risks in some domains. Our results show that analyzing the human interaction in organizational networks provides valuable information for decision makers and managers to support an increase in ethical behavior of the organization’s members. Full article
(This article belongs to the Special Issue Information Processing and Management for Large and Complex Networks)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop