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Electronics
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Opportunistic Networks
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Opportunistic Networks

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 16835

Special Issue Editor

Prof. Dr. Enrique Hernández-Orallo

E-Mail Website
Guest Editor
Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: opportunistic networks; network performance evaluation; VANETs; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Opportunistic networks (OppNets) have arisen as an effective infrastructure-less communication model for message broadcasting, based on taking advantage of the dynamically created direct and localized communication links (e.g., through a Wi-Fi Direct channels) to exchange messages between nearby nodes. Although OppNets initially received attention to allow communication where infrastructure is not available (for example, rural areas or disaster scenarios), currently, other promising application areas have arisen, such as crowdsensing and urban sensing, content sharing, and mobile social networking. In general, the performance of these OppNets relies on the interrelation between technical aspects (related to protocols operation) and human social behaving, which define the nodes’ mobility. These aspects have not been explored in depth yet and clearly impact the performance of OppNets. 

This Special Issue encourages submissions not only related to recent research developments on opportunistic networks but also articles describing experimental results and mobility data obtained from real scenarios. 

Prof. Dr. Enrique Hernández-Orallo
Guest Editor

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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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.

Keywords

  • Architecture for OppNets
  • Unicast and multicast routing
  • Simulation and modeling of OppNets
  • Mobility analysis and models for OppNets
  • Security issues in OppNets
  • New applications and services based on OppNets
  • Opportunistic mobile social networks
  • Mobile crowdsensing and urban sensing
  • Vehicular social networks (VSN)

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Published Papers (6 papers)

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Research

24 pages, 3847 KiB  
Article
How Human Mobility Models Can Help to Deal with COVID-19
by Enrique Hernández-Orallo and Antonio Armero-Martínez
Electronics 2021, 10(1), 33; https://doi.org/10.3390/electronics10010033 - 28 Dec 2020
Cited by 10 | Viewed by 3179
Abstract
One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, [...] Read more.
One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, opportunistic networks, etc. In this paper, we propose the use of these models for evaluating the temporal and spatial risk of transmission of the COVID-19 disease. First, we study both pure synthetic model and simulated models based on pedestrian simulators, generated for real urban scenarios such as a square and a subway station. In order to evaluate the risk, two different risks of exposure are defined. The results show that we can obtain not only the temporal risk but also a heat map with the exposure risk in the evaluated scenario. This is particularly interesting for public spaces, where health authorities could make effective risk management plans to reduce the risk of transmission. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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15 pages, 478 KiB  
Article
RSSGM: Recurrent Self-Similar Gauss–Markov Mobility Model
by Mohammed J. F. Alenazi, Shatha O. Abbas, Saleh Almowuena and Maazen Alsabaan
Electronics 2020, 9(12), 2089; https://doi.org/10.3390/electronics9122089 - 7 Dec 2020
Cited by 9 | Viewed by 2924
Abstract
Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees [...] Read more.
Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees of randomness or adequately mimic human movements by injecting possible crossing points and adding recurrent patterns. In this paper, we propose the recurrent self-similar Gauss–Markov mobility (RSSGM) model, a novel mobility model that is suitable for applications in which nodes exhibit recurrent visits to selected locations with semi-similar routes. Examples of such applications include daily human routines, airplane and public transportation routes, and intra-campus student walks. First, we present the proposed algorithm and its assumptions, and then we study its behavior in different scenarios. The study’s results show that different and more realistic mobility traces can be achieved without the need for complex computational models or existing GPS records. Our model can flexibly adjust its behavior to fit any application by carefully tuning and choosing the right values for its parameters. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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18 pages, 1825 KiB  
Article
Effective Data Selection and Management Method Based on Dynamic Regulation in Opportunistic Social Networks
by Jia Wu, Sheng Yin, Yutong Xiao and Genghua Yu
Electronics 2020, 9(8), 1271; https://doi.org/10.3390/electronics9081271 - 7 Aug 2020
Cited by 10 | Viewed by 2226
Abstract
5G has brought a huge increase in data, and the number of nodes and types of messages are becoming more and more complex. The Internet of things has become a large and complex network. More and more devices can be used as nodes [...] Read more.
5G has brought a huge increase in data, and the number of nodes and types of messages are becoming more and more complex. The Internet of things has become a large and complex network. More and more devices can be used as nodes in opportunistic social networks. The attitude of nodes to messages is different and changeable. However, in the previous opportunistic network algorithm and mass data transmission environment, due to the lack of effective information selection and management means, it was easy to lead to transmission delay and high consumption. Therefore, we propose Effective Data Selection and Management (EDSM). EDSM uses the current state of the node as the basis for forwarding messages. When the cache space is insufficient, EDSM will perform cache replacement based on the message cache value and delete the information with the lowest cache value. Simulation results show that the algorithm has good performance in terms of delivery rate and latency. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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19 pages, 5071 KiB  
Article
Mechanism to Estimate Effective Spectrum Availability Inside Smart Buildings
by Washington Medina, Francisco Novillo, Eduardo Chancay and Juan Romero
Electronics 2020, 9(8), 1244; https://doi.org/10.3390/electronics9081244 - 2 Aug 2020
Cited by 1 | Viewed by 2234
Abstract
Smart cities and smart buildings must provide their customers with many services, including those associated with health, productivity, and energy efficiency, among others. Short-range wireless systems can provide all of these services, but the significant growth of wireless networks operating within a smart [...] Read more.
Smart cities and smart buildings must provide their customers with many services, including those associated with health, productivity, and energy efficiency, among others. Short-range wireless systems can provide all of these services, but the significant growth of wireless networks operating within a smart building (SB) can produce the phenomenon of spectrum shortages. Spectrum shortages could be resolved using Cognitive Radio (CR)-based systems to improve the efficiency of electromagnetic spectrum use by taking advantage of the reusable spectrum available in the building’s interior. This study proposes a mechanism using two interference conditions to quickly estimate the minimum amount of effective spectrum availability (ESA) inside an SB. The results show that an SB contains ESA distributed across 36% to 98% of the building’s area for reuse, as a function of the height of the building and of the distance from the base station (BS) of the primary system. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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14 pages, 2492 KiB  
Article
Multi-Objective Optimization of Task-to-Node Assignment in Opportunistic Fog RAN
by Jofina Jijin, Boon-Chong Seet and Peter Han Joo Chong
Electronics 2020, 9(3), 474; https://doi.org/10.3390/electronics9030474 - 12 Mar 2020
Cited by 5 | Viewed by 2930
Abstract
The opportunistic fog radio access network (OF-RAN) is a promising RAN architecture proposed for next-generation cellular networks. OF-RAN extends the current fog RAN (F-RAN) architecture by introducing virtual fog access points (v-FAPs) that can be formed on-demand by a set of resourceful end-user [...] Read more.
The opportunistic fog radio access network (OF-RAN) is a promising RAN architecture proposed for next-generation cellular networks. OF-RAN extends the current fog RAN (F-RAN) architecture by introducing virtual fog access points (v-FAPs) that can be formed on-demand by a set of resourceful end-user devices available in an opportunistic manner. These devices in the v-FAP collaboratively serve as the service nodes to a resource-limited local client by performing resource-demanding processing tasks on its behalf. Hence, appropriately assigning the client task to the service nodes of the v-FAP, i.e., task-to-node assignment (TNA), is a fundamental problem in OF-RAN. This paper formulates and solves the TNA as a multi-objective optimization problem, with the goals of minimizing energy and latency of the v-FAP, while maximizing fairness (or load balancing) amongst its service nodes by minimizing their maximum load. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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22 pages, 1456 KiB  
Article
SRMM: A Social Relationship-Aware Human Mobility Model
by Dat Van Anh Duong and Seokhoon Yoon
Electronics 2020, 9(2), 221; https://doi.org/10.3390/electronics9020221 - 28 Jan 2020
Cited by 3 | Viewed by 2726
Abstract
Since human movement patterns are important for validating the performance of wireless networks, several traces of human movements in real life have been collected. However, collecting data about human movements is costly and time-consuming. Moreover, multiple traces are demanded to test various network [...] Read more.
Since human movement patterns are important for validating the performance of wireless networks, several traces of human movements in real life have been collected. However, collecting data about human movements is costly and time-consuming. Moreover, multiple traces are demanded to test various network scenarios. As a result, a lot of synthetic models of human movement have been proposed. Nevertheless, most of the proposed models were often based on random generation, and cannot produce realistic human movements. Although there have been a few models that tried to capture the characteristics of human movement in real life (e.g., flights, inter-contact times, and pause times following the truncated power-law distribution), those models still cannot reflect realistic human movements due to a lack of consideration for social context among people. To address those limitations, in this paper, we propose a novel human mobility model called the social relationship–aware human mobility model (SRMM), which considers social context as well as the characteristics of human movement. SRMM partitions people into social groups by exploiting information from a social graph. Then, the movements of people are determined by considering the distances to places and social relationships. The proposed model is first evaluated by using a synthetic map, and then a real road map is considered. The results of SRMM are compared with a real trace and other synthetic mobility models. The obtained results indicate that SRMM is consistently better at reflecting both human movement characteristics and social relationships. Full article
(This article belongs to the Special Issue Opportunistic Networks)
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