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 10073

Special Issue Editors


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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

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

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 Interested authors are invited to contribute their original, unpublished work.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.

Published Papers (3 papers)

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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 6 | Viewed by 3659
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)
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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 2 | Viewed by 2333
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)
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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 2861
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)
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