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Journal articles on the topic 'Communications opportunistes'

Author: Grafiati

Published: 21 December 2024

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1

Martín-Pascual, Miguel Ángel, and Celia Andreu-Sánchez. "Practical Application of Mesh Opportunistic Networks." Applied System Innovation 6, no. 3 (June 16, 2023): 60. http://dx.doi.org/10.3390/asi6030060.

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Opportunistic networks allow for communication between nearby mobile devices through a radio connection, avoiding the need for cellular data coverage or a Wi-Fi connection. The limited spatial range of this type of communication can be overcome by using nodes in a mesh network. The purpose of this research was to examine a commercial application of electronic mesh communication without a mobile data plan, Wi-Fi, or satellite. A mixed study, with qualitative and quantitative strategies, was designed. An experimental session, in which participants tested opportunistic networks developing different tasks for performance, was carried out to examine the system. Different complementary approaches were adopted: a survey, a focus group, and an analysis of participants’ performance. We found that the main advantage of this type of communication is the lack of a need to use data networks for one-to-one and group communications. Opportunistic networks can be integrated into professional communication workflows. They can be used in situations where traditional telephones and the Internet are compromised, such as at mass events, emergency situations, or in the presence of frequency inhibitors.

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2

Carreras, Iacopo, Andrea Zanardi, Elio Salvadori, and Daniele Miorandi. "A Distributed Monitoring Framework for Opportunistic Communication Systems An Experimental Approach." International Journal of Adaptive, Resilient and Autonomic Systems 2, no. 3 (July 2011): 45–62. http://dx.doi.org/10.4018/jaras.2011070104.

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Opportunistic communication systems aim at producing and sharing digital resources by means of localized wireless data exchanges among mobile nodes. The design and evaluation of systems able to exploit this emerging communication paradigm is a challenging problem. This paper presents the authors’ experience in developing U-Hopper, a middleware running over widely diffused mobile handsets and supporting the development of context-aware services based on opportunistic communications. The authors present the design of the platform, and describe the distributed monitoring framework that was set up in order to monitor and dynamically reconfigure it at run time. The paper concludes with an experimental evaluation of the framework, showing its practical utilization when monitoring an operational opportunistic communication system.

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3

Pajevic, Ljubica, and Gunnar Karlsson. "Modeling opportunistic communication with churn." Computer Communications 96 (December 2016): 123–35. http://dx.doi.org/10.1016/j.comcom.2016.04.018.

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Helgason, Olafur, Sylvia T. Kouyoumdjieva, and Gunnar Karlsson. "Opportunistic Communication and Human Mobility." IEEE Transactions on Mobile Computing 13, no. 7 (July 2014): 1597–610. http://dx.doi.org/10.1109/tmc.2013.160.

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Amin, Osama, and Lutz Lampe. "Opportunistic Energy Efficient Cooperative Communication." IEEE Wireless Communications Letters 1, no. 5 (October 2012): 412–15. http://dx.doi.org/10.1109/wcl.2012.061212.120206.

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6

Gorbil, Gokce, and Erol Gelenbe. "Opportunistic Communications for Emergency Support Systems." Procedia Computer Science 5 (2011): 39–47. http://dx.doi.org/10.1016/j.procs.2011.07.008.

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7

Nagananda, K. G. "Secure communications over opportunistic-relay channels." Physical Communication 7 (June 2013): 105–21. http://dx.doi.org/10.1016/j.phycom.2012.11.002.

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8

Davoli, Luca, Emanuele Pagliari, and Gianluigi Ferrari. "Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming." Drones 5, no. 2 (April 15, 2021): 26. http://dx.doi.org/10.3390/drones5020026.

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Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key “ingredient” to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases.

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9

Ciobanu, Radu Ioan, and Ciprian Dobre. "Opportunistic Networks." International Journal of Virtual Communities and Social Networking 5, no. 2 (April 2013): 11–26. http://dx.doi.org/10.4018/jvcsn.2013040102.

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When mobile devices are unable to establish direct communication, or when communication should be offloaded to cope with large throughputs, mobile collaboration can be used to facilitate communication through opportunistic networks. These types of networks, formed when mobile devices communicate only using short-range transmission protocols, usually when users are close, can help applications still exchange data. Routes are built dynamically, since each mobile device is acting according to the store-carry-and-forward paradigm. Thus, contacts are seen as opportunities to move data towards the destination. In such networks data dissemination is usually based on a publish/subscribe model. Opportunistic data dissemination also raises questions concerning user privacy and incentives. In this the authors present a motivation of using opportunistic networks in various real life use cases, and then analyze existing relevant work in the area of data dissemination. The authors present the categories of a proposed taxonomy that captures the capabilities of data dissemination techniques used in opportunistic networks. Moreover, the authors survey relevant techniques and analyze them using the proposed taxonomy.

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10

Johnston, Matthew, Isaac Keslassy, and Eytan Modiano. "Channel Probing in Opportunistic Communication Systems." IEEE Transactions on Information Theory 63, no. 11 (November 2017): 7535–52. http://dx.doi.org/10.1109/tit.2017.2717580.

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11

Khalil, Ayman, and Besma Zeddini. "A Secure Opportunistic Network with Efficient Routing for Enhanced Efficiency and Sustainability." Future Internet 16, no. 2 (February 8, 2024): 56. http://dx.doi.org/10.3390/fi16020056.

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The intersection of cybersecurity and opportunistic networks has ushered in a new era of innovation in the realm of wireless communications. In an increasingly interconnected world, where seamless data exchange is pivotal for both individual users and organizations, the need for efficient, reliable, and sustainable networking solutions has never been more pressing. Opportunistic networks, characterized by intermittent connectivity and dynamic network conditions, present unique challenges that necessitate innovative approaches for optimal performance and sustainability. This paper introduces a groundbreaking paradigm that integrates the principles of cybersecurity with opportunistic networks. At its core, this study presents a novel routing protocol meticulously designed to significantly outperform existing solutions concerning key metrics such as delivery probability, overhead ratio, and communication delay. Leveraging cybersecurity’s inherent strengths, our protocol not only fortifies the network’s security posture but also provides a foundation for enhancing efficiency and sustainability in opportunistic networks. The overarching goal of this paper is to address the inherent limitations of conventional opportunistic network protocols. By proposing an innovative routing protocol, we aim to optimize data delivery, minimize overhead, and reduce communication latency. These objectives are crucial for ensuring seamless and timely information exchange, especially in scenarios where traditional networking infrastructures fall short. By large-scale simulations, the new model proves its effectiveness in the different scenarios, especially in terms of message delivery probability, while ensuring reasonable overhead and latency.

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12

Zhang, Qian, Qi Xi, Chen He, and Lingge Jiang. "User Clustered Opportunistic Beamforming for Stratospheric Communications." IEEE Communications Letters 20, no. 9 (September 2016): 1832–35. http://dx.doi.org/10.1109/lcomm.2016.2584038.

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13

Gozalvez, Javier, and Miguel Sepulcre. "Opportunistic technique for efficient wireless vehicular communications." IEEE Vehicular Technology Magazine 2, no. 4 (December 2007): 33–39. http://dx.doi.org/10.1109/mvt.2008.917448.

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14

Bletsas, Aggelos, Hyundong Shin, and Moe Win. "Cooperative Communications with Outage-Optimal Opportunistic Relaying." IEEE Transactions on Wireless Communications 6, no. 9 (September 2007): 3450–60. http://dx.doi.org/10.1109/twc.2007.06020050.

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15

Passarella, Andrea, and Konstantinos Oikonomou. "Special Section on Autonomic and Opportunistic Communications." Computer Communications 33, no. 13 (August 2010): 1471. http://dx.doi.org/10.1016/j.comcom.2010.05.004.

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16

Chen, L., R. A. Carrasco, and I. J. Wassell. "Opportunistic nonorthogonal amplify-and-forward cooperative communications." Electronics Letters 47, no. 10 (2011): 626. http://dx.doi.org/10.1049/el.2011.0487.

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17

Boldrini, C., K. Lee, M. Önen, J. Ott, and E. Pagani. "Opportunistic networks." Computer Communications 48 (July 2014): 1–4. http://dx.doi.org/10.1016/j.comcom.2014.04.007.

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18

Shaqfeh, Mohammad. "Opportunistic Cooperative Communication Using Buffer-Aided Relays." Qatar Foundation Annual Research Forum Proceedings, no. 2013 (November 2013): ICTP 025. http://dx.doi.org/10.5339/qfarf.2013.ictp-025.

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19

Hadzi-Velkov, Zoran, Ivana Nikoloska, Hristina Chingoska, and Nikola Zlatanov. "Opportunistic Scheduling in Wireless Powered Communication Networks." IEEE Transactions on Wireless Communications 16, no. 6 (June 2017): 4106–19. http://dx.doi.org/10.1109/twc.2017.2691785.

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20

Valerio, Lorenzo, and Matteo Mordacchini. "Special Section on Opportunistic Communication and Computation." Computer Communications 96 (December 2016): 109. http://dx.doi.org/10.1016/j.comcom.2016.11.004.

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21

Kouyoumdjieva, Sylvia T., and Gunnar Karlsson. "Impact of Duty Cycling on Opportunistic Communication." IEEE Transactions on Mobile Computing 15, no. 7 (July 1, 2016): 1686–98. http://dx.doi.org/10.1109/tmc.2015.2478470.

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22

Kokuti, Andras, and Erol Gelenbe. "Directional Navigation Improves Opportunistic Communication for Emergencies." Sensors 14, no. 8 (August 20, 2014): 15387–99. http://dx.doi.org/10.3390/s140815387.

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23

Nawaz, Farhan, Hemant Kumar, Syed Ali Hassan, and Haejoon Jung. "Opportunistic Large Array Propagation Models: A Comprehensive Survey." Sensors 21, no. 12 (June 19, 2021): 4206. http://dx.doi.org/10.3390/s21124206.

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Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density . Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

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24

YUAN, Runping, Taiyi ZHANG, Jing ZHANG, Jianxiong HUANG, and Zhenjie FENG. "Opportunistic Cooperative Communications over Nakagami-m Fading Channels." IEICE Transactions on Communications E93-B, no. 10 (2010): 2812–16. http://dx.doi.org/10.1587/transcom.e93.b.2812.

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25

Park, Gwangwoo, Youngjun Shim, Insun Jang, and Sangheon Pack. "Bloom-filter-aided redundancy elimination in opportunistic communications." IEEE Wireless Communications 23, no. 1 (February 2016): 112–19. http://dx.doi.org/10.1109/mwc.2016.7422413.

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26

Hui, Pan, and Jon Crowcroft. "Human mobility models and opportunistic communications system design." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1872 (March 6, 2008): 2005–16. http://dx.doi.org/10.1098/rsta.2008.0010.

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In this paper, we seek to improve understanding of the structure of human mobility, with a view to using this for designing algorithms for the dissemination of data among mobile users. We analyse community structures and node centrality from the human mobility traces and use these two metrics to design efficient forwarding algorithms in terms of delivery ratio and delivery cost for mobile networks. This is the first empirical study of community and centrality using real human mobility datasets.

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27

Lee, Il-Gu. "Opportunistic Secure Communications for Wireless Local Area Networks." International Journal of Control and Automation 10, no. 12 (December 31, 2017): 109–20. http://dx.doi.org/10.14257/ijca.2017.10.12.10.

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28

Asadi, Arash, and Vincenzo Mancuso. "A Survey on Opportunistic Scheduling in Wireless Communications." IEEE Communications Surveys & Tutorials 15, no. 4 (2013): 1671–88. http://dx.doi.org/10.1109/surv.2013.011413.00082.

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29

Qiao, Liqiang. "Mobile Data Traffic Offloading through Opportunistic Vehicular Communications." Wireless Communications and Mobile Computing 2020 (December 22, 2020): 1–12. http://dx.doi.org/10.1155/2020/3093581.

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To cope with an exponentially increasing demand on mobile data traffic in cellular network, proximity-based opportunistic vehicular communications can be exploited as a complementary mean to offload and reduce the load of cellular network. In this paper, we propose a two-phase approach for mobile data traffic offloading, which exploits opportunistic contact and future utility with user mobility. The proposed approach includes one phase of initial source selection and subsequent phase of data forwarding. In phase 1, we build a weighted reachability graph, which is a very useful high-level abstraction for studying vehicular communication over time. Then, we propose an initial source selection algorithm, named VRank, and apply it in the weight reachability graph to identify some influential vehicles to serve as initial sources according to the rank of VRank. In phase 2, we formulate the forwarding schedule problem as a global utility maximization problem, which takes heterogeneous user interest and future utility contribution into consideration. Then, we propose an efficient scheme MGUP to solve the problem by providing a solution that decides which object should be broadcast. The effectiveness of our algorithm is verified through extensive simulation using real vehicular trace.

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30

Shao, Wenjuan, Qingguo Shen, and Liaoruo Huang. "Social-aware content dissemination through opportunistic D2D communications." Transactions on Emerging Telecommunications Technologies 30, no. 1 (November 28, 2018): e3542. http://dx.doi.org/10.1002/ett.3542.

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31

Singh, Vishal, Andy Dong, and John S. Gero. "Social learning in design teams: The importance of direct and indirect communications." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 27, no. 2 (April 18, 2013): 167–82. http://dx.doi.org/10.1017/s0890060413000061.

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AbstractThis paper discusses the effects of direct and indirect communications on social learning and task coordination in design teams. The findings reported in this paper are based on a computational model that simulates the formation of transactive memory (TM) through social learning from direct and indirect communications. Direct communications are explicit information exchanged between team members whereas indirect communication may be opportunistic and coincidental, resulting in learning and information gained through observations of the actions of others. However, team structure mediates opportunities for communication. Three types of team structures are studied, which are differentiated on the basis of their constraints on and opportunities for direct and indirect communications across the team. The differences across the team structures are investigated through a series of simulations in which team member retention, cognitive busyness of team members, and task complexity are additional moderating variables, and task coordination and formation of TM are the dependent variables. Fewer communications to coordinate the same tasks are taken as the measure of efficient task coordination. Findings suggest that reduction in communication and learning opportunities are more detrimental to the task coordination in flat teams as compared to functional teams. Indirect communications contribute more to the formation of TM than to task coordination. Flat teams facilitate the formation of TM, whereas functional teams are more appropriate for efficient task coordination, indicating that the role of TM in mediating task coordination varies with team structure.

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32

Kang Kim, Hojin, Raimundo Becerra, Sandy Bolufé, Cesar A. Azurdia-Meza, Samuel Montejo-Sánchez, and David Zabala-Blanco. "Neuroevolution-Based Adaptive Antenna Array Beamforming Scheme to Improve the V2V Communication Performance at Intersections." Sensors 21, no. 9 (April 23, 2021): 2956. http://dx.doi.org/10.3390/s21092956.

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The opportunistic exchange of information between vehicles can significantly contribute to reducing the occurrence of accidents and mitigating their damages. However, in urban environments, especially at intersection scenarios, obstacles such as buildings and walls block the line of sight between the transmitter and receiver, reducing the vehicular communication range and thus harming the performance of road safety applications. Furthermore, the sizes of the surrounding vehicles and weather conditions may affect the communication. This makes communications in urban V2V communication scenarios extremely difficult. Since the late notification of vehicles or incidents can lead to the loss of human lives, this paper focuses on improving urban vehicle-to-vehicle (V2V) communications at intersections by using a transmission scheme able of adapting to the surrounding environment. Therefore, we proposed a neuroevolution of augmenting topologies-based adaptive beamforming scheme to control the radiation pattern of an antenna array and thus mitigate the effects generated by shadowing in urban V2V communication at intersection scenarios. This work considered the IEEE 802.11p standard for the physical layer of the vehicular communication link. The results show that our proposal outperformed the isotropic antenna in terms of the communication range and response time, as well as other traditional machine learning approaches, such as genetic algorithms and mutation strategy-based particle swarm optimization.

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33

Wang, Kun, Guoli Feng, Lizhong Zhang, and Jia Wu. "Energy Transmission and Equilibrium Scheme in Data Communication Opportunistic Networks." Applied System Innovation 3, no. 4 (December 3, 2020): 54. http://dx.doi.org/10.3390/asi3040054.

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In data communication, a good communication scheme can improve the transmission of data packets among nodes. The opportunistic network is a convenient wireless communication network and its model is easily applied in data communication. Energy consumption among nodes in the opportunistic network is an important parameter. The over-consumption of energy may cause the nodes to be dead, and then many useful data packets would be lost. Especially in data communication, this tendency is obvious. However, many researchers rarely consider energy consumption in the opportunistic network. This paper suggests a scheme in which data packets are transmitted among nodes. Energy supply and equilibrium is found in opportunistic networks. This scheme not only supplies energy to active nodes, but also considers inactive nodes to energy supply objects. Then, this scheme accomplishes data packets transmission and improves energy utilization in the opportunistic network. With the evidence of simulation and comparison of the epidemic algorithm, the direct delivery algorithm, and spray and wait algorithm in the opportunistic network, this scheme can be an equilibrium for energy consumption, for improving the delivering ratio, and the size of the cache time.

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34

Abbas, Asad, Moez Krichen, Roobaea Alroobaea, Sharaf Malebary, Usman Tariq, and Md Jalil Piran. "An opportunistic data dissemination for autonomous vehicles communication." Soft Computing 25, no. 18 (February 18, 2021): 11899–912. http://dx.doi.org/10.1007/s00500-020-05542-y.

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35

Wei, Hao, and Zhang Xing. "Distributed Mobile Computing Mechanism Based on Opportunistic Communication." Information Technology Journal 12, no. 23 (November 15, 2013): 7255–59. http://dx.doi.org/10.3923/itj.2013.7255.7259.

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36

Rajpoot, Nidhi, and Rajendra Singh Kushwah. "An Efficient Opportunistic Routing Protocol in Underwater Communication." International Journal of u- and e-Service, Science and Technology 8, no. 6 (June 30, 2015): 135–46. http://dx.doi.org/10.14257/ijunesst.2015.8.6.13.

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37

Ashraf, Manzur, Aruna Jayasuriya, and Sylvie Perreau. "Distributed opportunistic communication protocol for wireless multihop networks." International Journal of Mobile Network Design and Innovation 3, no. 2 (2009): 112. http://dx.doi.org/10.1504/ijmndi.2009.030843.

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38

Xiao, Hongjiang, Qionghai Dai, and Xiangyang Ji. "Opportunistic video communication over cooperative decode-forward networks." Tsinghua Science and Technology 15, no. 2 (April 2010): 209–15. http://dx.doi.org/10.1016/s1007-0214(10)70052-3.

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39

Lio’, Pietro, and Sasitharan Balasubramaniam. "Opportunistic routing through conjugation in bacteria communication nanonetwork." Nano Communication Networks 3, no. 1 (March 2012): 36–45. http://dx.doi.org/10.1016/j.nancom.2011.10.003.

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40

Zorba, Nizar, and Ana I. Perez-Neira. "Opportunistic Grassmannian Beamforming for Multiuser and Multiantenna Downlink Communications." IEEE Transactions on Wireless Communications 7, no. 4 (April 2008): 1174–78. http://dx.doi.org/10.1109/twc.2008.060972.

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41

Sciancalepore, Vincenzo, Domenico Giustiniano, Albert Banchs, and Andreea Hossmann-Picu. "Offloading Cellular Traffic Through Opportunistic Communications: Analysis and Optimization." IEEE Journal on Selected Areas in Communications 34, no. 1 (January 2016): 122–37. http://dx.doi.org/10.1109/jsac.2015.2452472.

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42

Han, Bo, Pan Hui, V. S. Anil Kumar, Madhav V. Marathe, Jianhua Shao, and Aravind Srinivasan. "Mobile Data Offloading through Opportunistic Communications and Social Participation." IEEE Transactions on Mobile Computing 11, no. 5 (May 2012): 821–34. http://dx.doi.org/10.1109/tmc.2011.101.

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43

Yan, Yan, Baoxian Zhang, and Cheng Li. "Opportunistic network coding based cooperative retransmissions in D2D communications." Computer Networks 113 (February 2017): 72–83. http://dx.doi.org/10.1016/j.comnet.2016.12.004.

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44

Hang Li, Qinghua Guo, Defeng Huang, and YingJun Zhang. "User Identification for Opportunistic OFDM-Based Multiuser Wireless Communications." IEEE Transactions on Vehicular Technology 61, no. 4 (May 2012): 1673–84. http://dx.doi.org/10.1109/tvt.2012.2187936.

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45

Shatila, Hazem, Mohamed Khedr, and Jeffrey H. Reed. "Opportunistic channel allocation decision making in cognitive radio communications." International Journal of Communication Systems 27, no. 2 (April 13, 2012): 216–32. http://dx.doi.org/10.1002/dac.2350.

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46

Leligou, Helen C., Periklis Chatzimisios, Lambros Sarakis, Theofanis Orphanoudakis, Panagiotis Karkazis, and Theodore Zahariadis. "An 802.11p Compliant System Prototype Supporting Road Safety and Traffic Management Applications." International Journal of Wireless Networks and Broadband Technologies 3, no. 1 (January 2014): 1–17. http://dx.doi.org/10.4018/ijwnbt.2014010101.

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During the last decades Intelligent Transportation Systems (ITS) have been attracting the interest of an increasing number of researchers, engineers and entrepreneurs, as well as citizens and civil authorities, since they can contribute towards improving road transport safety and efficiency and ameliorate environmental conditions and life quality. Emerging technologies yield miniaturized sensing, processing and communication devices that enable a high degree of integration and open the way for a large number of smart applications that can exploit automated fusion of information and enable efficient decisions by collecting, processing and communicating a large number of data in real-time. The cornerstone of these applications is the realization of an opportunistic wireless communication system between vehicles as well as between vehicles and infrastructure over which the right piece of information reaches the right location on time. In this paper, the authors present the design and implementation of representative safety and traffic management applications. Specifically the authors discuss the hardware and software requirements presenting a use case based on the NEC Linkbird-MX platform, which supports IEEE 802.11p based communications. The authors show how the functionality of IEEE 802.11p can be exploited to build efficient road safety and traffic management applications over mobile opportunistic systems and discuss practical implementation issues.

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47

Hu, Qingsong, Juan Ding, and Shiyin Li. "A Novel Cognitive Opportunistic Communication Framework for Coal Mines." Mathematical Problems in Engineering 2019 (January 3, 2019): 1–10. http://dx.doi.org/10.1155/2019/6109303.

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The dynamic advancement and harsh environment of coal mines often result in intermittent or regional wireless connection between sending nodes and receiving nodes and then lead to the decrease of transmission success ratio and even failure. To solve this problem, the environmental cognition and best-effort transmission are both demanded. Here we proposed a novel communication framework for coal mines based on a cognitive opportunistic concept to address the wireless network communication problems in coal mines, which consists of the node mobility model in coal mines, cooperative cognition of the time-varying communication environment, and the opportunistic routing of intermittent or regional connection scenarios. To realize this framework, real time neighbor discovering mechanisms and mobility perceiving strategies, called environment cognition, must be deeply investigated to predict the trends of node movement. The obtained results of environment cognition are then used to analyze current channel characteristics in order to determine and set optimum communication system parameters and reduce the probability of intermittent or regional connection. To address those unavoidable situations of the intermittent or regional connection, the opportunistic routing mechanism is brought forward to provide relatively stable data transmission. Finally, as an example of cognitive opportunistic mine communication of this framework, personnel evacuation under an emergency is discussed.

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48

Grossi, Emanuele, Marco Lops, Antonia Maria Tulino, and Luca Venturino. "Opportunistic Sensing Using mmWave Communication Signals: A Subspace Approach." IEEE Transactions on Wireless Communications 20, no. 7 (July 2021): 4420–34. http://dx.doi.org/10.1109/twc.2021.3058775.

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49

Al-Ghanimi, Hayder. "Opportunistic Communication in Highly Congested and Dynamic Urban Areas." IOSR Journal of Engineering 3, no. 10 (October 2013): 46–52. http://dx.doi.org/10.9790/3021-031014652.

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50

Fajardo, Jovilyn Therese B., Keiichi Yasumoto, Naoki Shibata, Weihua Sun, and Minoru Ito. "Disaster Information Collection with Opportunistic Communication and Message Aggregation." Journal of Information Processing 22, no. 2 (2014): 106–17. http://dx.doi.org/10.2197/ipsjjip.22.106.

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