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Journal articles on the topic 'Mobile networks'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

S, Durga Devi, and Mythrae R. "The Mathematics of Mobile Networks." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (2019): 795–97. http://dx.doi.org/10.31142/ijtsrd21492.

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2

Zavlanos, Michael M., Alejandro Ribeiro, and George J. Pappas. "Network Integrity in Mobile Robotic Networks." IEEE Transactions on Automatic Control 58, no. 1 (2013): 3–18. http://dx.doi.org/10.1109/tac.2012.2203215.

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3

Kwun Han and S. Ghosh. "Going mobile [mobile-computing networks]." IEEE Circuits and Devices Magazine 14, no. 1 (1998): 10–22. http://dx.doi.org/10.1109/101.648595.

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4

Fu Jie Tey, Fu Jie Tey, Tin-Yu Wu Fu Jie Tey, Yueh Wu Tin-Yu Wu, and Jiann-Liang Chen Yueh Wu. "Generative Adversarial Network for Simulation of Load Balancing Optimization in Mobile Networks." 網際網路技術學刊 23, no. 2 (2022): 297–304. http://dx.doi.org/10.53106/160792642022032302010.

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<p>The commercial operation of 5G networks is almost ready to be launched, but problems related to wireless environment, load balancing for example, remain. Many load balancing methods have been proposed, but they were implemented in simulation environments that greatly differ from 5G networks. Current load balancing algorithms, on the other hand, focus on the selection of appropriate Wi-Fi or macro & small cells for Device to Device (D2D) communications, but Wi-Fi facilities and small cells are not available all the time. For this reason, we propose to use the macro cells that provi

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5

Mohan, Seshadri, Nitin Agarwal, and Ashutosh Dutta. "Social networks meet mobile networks." IEEE Communications Magazine 50, no. 6 (2012): 72–73. http://dx.doi.org/10.1109/mcom.2012.6211488.

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6

Sugumaran, Vijayan, Shriram Raghunathan, and K. Vivekanandan. "Mobile Community Networks." International Journal of Mobile Computing and Multimedia Communications 1, no. 2 (2009): 61–79. http://dx.doi.org/10.4018/jmcmc.2009040105.

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7

Wang, You-Chiun. "Mobile Sensor Networks." ACM Computing Surveys 47, no. 1 (2014): 1–36. http://dx.doi.org/10.1145/2617662.

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8

Campbell, Andrew T., Michael E. Kounavis, and Raymond R. F. Liao. "Programmable mobile networks." Computer Networks 31, no. 7 (1999): 741–65. http://dx.doi.org/10.1016/s0169-7552(98)00298-0.

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9

Sheng-Yuan Tu and Ali H. Sayed. "Mobile Adaptive Networks." IEEE Journal of Selected Topics in Signal Processing 5, no. 4 (2011): 649–64. http://dx.doi.org/10.1109/jstsp.2011.2125943.

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10

Irvine, J. M., I. S. Groves, and R. Tafazolli. "Future mobile networks." Electronics & Communication Engineering Journal 12, no. 6 (2000): 262–70. http://dx.doi.org/10.1049/ecej:20000604.

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11

Guo, Zhaoming, Shihua Bi, Yi Jiang, and Zheren Long. "Mobile Network Computers Should be the Terminal of Mobile Communication Networks." Wireless Personal Communications 85, no. 4 (2015): 1895–904. http://dx.doi.org/10.1007/s11277-015-2878-0.

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12

Alrashed, Ebrahim A., and Mehmet Hakan Karaata. "Imposter Detection in Mobile Wireless Sensor Networks." International Journal of Computer and Communication Engineering 3, no. 6 (2014): 434–41. http://dx.doi.org/10.7763/ijcce.2014.v3.364.

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13

Liu, Qiang, Min Chen, Jie Zhang, Bingwen Shen, and Zhong Chu. "Network Planning for WiMAX-R Networks." JUCS - Journal of Universal Computer Science 18, no. (9) (2012): 1194–217. https://doi.org/10.3217/jucs-018-09-1194.

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In this paper, a novel network planning process of the Mobile WiMAX for Railway (WiMAX-R) network is proposed. We first analyze the factors need considered in network planning. After introducing the WiMAX-R network architecture, the WiMAX-R network planning process is presented in detail. The process comprises application analysis, capacity prediction, network parameters configuring, coverage planning, handover planning and network simulation validation. In each step, Mobile WiMAX technical features and railway environment characters are both take into consideration. Finally, we simulated a Wi

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14

Ray, Shweta. "Intelligent-Driven Green Resource Allocation for Industrial Internet of Things In 5g Heterogeneous Network." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (2022): 55–67. http://dx.doi.org/10.22214/ijraset.2022.45161.

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Abstract: Mobile networks' energy consumption is rising in tandem with the volume of traffic and the number of people utilising mobile technology. To maintain the long-term survival of the next generation of mobile networks, there must be an emphasis on energy efficiency. By minimising the network's power consumption and proposing an energy-efficient network architecture, this thesis addresses the issue of increasing 5G and beyond network efficiency. The first component of this thesis focuses on base stations (BSs), the most energy-intensive part of mobile networks. Mobile network providers of

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15

Palackal, Antony, Paul Nyaga Mbatia, Dan-Bright Dzorgbo, Ricardo B. Duque, Marcus Antonius Ynalvez, and Wesley M. Shrum. "Are mobile phones changing social networks? A longitudinal study of core networks in Kerala." New Media & Society 13, no. 3 (2011): 391–410. http://dx.doi.org/10.1177/1461444810393900.

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Mobile telephony has diffused more rapidly than any Indian technology in recent memory, yet systematic studies of its impact are rare, focusing on technological rather than social change. We employ network surveys of separate groups of Kerala residents in 2002 and again in 2007 to examine recent shifts in mobile usage patterns and social relationships. Results show (1) near saturation of mobiles among both the professionals and nonprofessionals sampled, (2) a decrease in the number of social linkages across tie types and physical locations, and (3) a shift towards friends and family but away f

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16

Gabilondo, Álvaro, Zaloa Fernández, Roberto Viola, et al. "Traffic Classification for Network Slicing in Mobile Networks." Electronics 11, no. 7 (2022): 1097. http://dx.doi.org/10.3390/electronics11071097.

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Network slicing is a promising technique used in the smart delivery of traffic and can satisfy the requirements of specific applications or systems based on the features of the 5G network. To this end, an appropriate slice needs to be selected for each data flow to efficiently transmit data for different applications and heterogeneous requirements. To apply the slicing paradigm at the radio segment of a cellular network, this paper presents two approaches for dynamically classifying the traffic types of individual flows and transmitting them through a specific slice with an associated 5G quali

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17

Choi, Sang-Il, Ji-In Kim, and Seok-Joo Koh. "Network-based Mobility Control in Mobile LISP Networks." KIPS Transactions:PartC 18C, no. 5 (2011): 339–42. http://dx.doi.org/10.3745/kipstc.2011.18c.5.339.

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18

Banchs, Albert, Gustavo de Veciana, Vincenzo Sciancalepore, and Xavier Costa-Perez. "Resource Allocation for Network Slicing in Mobile Networks." IEEE Access 8 (2020): 214696–706. http://dx.doi.org/10.1109/access.2020.3040949.

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19

Palanisamy, B., N. Karthik, K. Chandrakumar, K. Thirunavukkarasu, and R. Jayasudha. "Improving Network Security in Mobile Ad Hoc Networks." Journal of Computational and Theoretical Nanoscience 16, no. 5 (2019): 2299–301. http://dx.doi.org/10.1166/jctn.2019.7888.

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20

Yang, Yinying, Mirela I. Fonoage, and Mihaela Cardei. "Improving network lifetime with mobile wireless sensor networks." Computer Communications 33, no. 4 (2010): 409–19. http://dx.doi.org/10.1016/j.comcom.2009.11.010.

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21

VikramPhaneendra, S., Sreenivasulu T, and B. Jalaja Kumari. "Identifying Stable Network in Mobile Ad-Hoc Networks." International Journal of Computer Applications 43, no. 18 (2012): 22–25. http://dx.doi.org/10.5120/6204-8761.

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22

Chen, Chi-Yuan, Fan-Hsun Tseng, Chin-Feng Lai, and Han-Chieh Chao. "Network planning for mobile multi-hop relay networks." Wireless Communications and Mobile Computing 15, no. 7 (2013): 1142–54. http://dx.doi.org/10.1002/wcm.2396.

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23

Qi Xu, Deyun Gao, Huachun Zhou, Bohao Feng, and Taixin Li. "OpenNSP: Open Network Service Provision for Mobile Networks." Research Briefs on Information and Communication Technology Evolution 3 (May 15, 2017): 42–52. http://dx.doi.org/10.56801/rebicte.v3i.43.

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In recent years, many innovative techniques are emerged for satisfying various user requirements,such as Software Definition Network (SDN) and Network Function Virtualization (NFV). However,the current solutions for network service provision still lack enough flexibility and openness thatresult in high expenditures and complexity. Thus, we propose an Open Network Service Provision(OpenNSP) solution in this paper, aiming to address the multi-domain problems of service functionchain outsourcing for mobile networks. Particularly, OpenNSP is based on IETF hierarchical servicefunction chaining (hSF

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24

Murugan, S., and Dr M. Jeyakarthic. "Optimal Deep Neural Network based Classification Model for Intrusion Detection in Mobile Adhoc Networks." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (2019): 1374–87. http://dx.doi.org/10.5373/jardcs/v11sp10/20192983.

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25

Ramya, K. "Mobile Computing Broadband Networks." International Journal for Research in Applied Science and Engineering Technology V, no. II (2017): 292–94. http://dx.doi.org/10.22214/ijraset.2017.2045.

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26

Sousa, E. S. "CDMA Mobile Communication Networks." Journal of Communication and Information Systems 9, no. 1 (1994): 5–26. http://dx.doi.org/10.14209/jcis.1994.1.

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27

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 1 (2019): 42. http://dx.doi.org/10.1109/mcom.2019.8613272.

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28

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 4 (2019): 94. http://dx.doi.org/10.1109/mcom.2019.8703472.

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29

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 9 (2019): 112. http://dx.doi.org/10.1109/mcom.2019.8847237.

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30

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 57, no. 12 (2019): 37. http://dx.doi.org/10.1109/mcom.2019.8930823.

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31

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 3 (2020): 54. http://dx.doi.org/10.1109/mcom.2020.9040263.

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32

Alexander, Tom, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 5 (2020): 48. http://dx.doi.org/10.1109/mcom.2020.9112741.

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33

Alexander, Thomas, Wojciech Mazurczyk, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 7 (2020): 12. http://dx.doi.org/10.1109/mcom.2020.9161987.

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34

Alexander, Tom, Ilker Demirkol, Amitabh Mishra, and Alberto Perotti. "Mobile Communications and Networks." IEEE Communications Magazine 58, no. 9 (2020): 73. http://dx.doi.org/10.1109/mcom.2020.9214392.

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35

Kolios, Panayiotis, Vasilis Friderikos, and Katerina Papadaki. "Future Wireless Mobile Networks." IEEE Vehicular Technology Magazine 6, no. 1 (2011): 24–30. http://dx.doi.org/10.1109/mvt.2010.939905.

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36

Huber, J. F. "Mobile next-generation networks." IEEE Multimedia 11, no. 1 (2004): 72–83. http://dx.doi.org/10.1109/mmul.2004.1261110.

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37

Alwan, A., R. Bagrodia, N. Bambos, et al. "adaptive mobile multimedia networks." IEEE Personal Communications 3, no. 2 (1996): 34–51. http://dx.doi.org/10.1109/98.490751.

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38

Yelland, Mark. "Fraud in mobile networks." Computer Fraud & Security 2013, no. 3 (2013): 5–9. http://dx.doi.org/10.1016/s1361-3723(13)70027-7.

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39

Shen, Wei-Liang, Chung-Shiuan Chen, Kate Ching-Ju Lin, and Kien A. Hua. "Autonomous Mobile Mesh Networks." IEEE Transactions on Mobile Computing 13, no. 2 (2014): 364–76. http://dx.doi.org/10.1109/tmc.2012.259.

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40

Resende, Mauricio G. C. "“Mobile Networks and Computing,”." Journal of Combinatorial Optimization 5, no. 4 (2001): 497–98. http://dx.doi.org/10.1023/a:1011633010511.

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41

You, Ilsun, and Takahiro Hara. "Mobile and Wireless Networks." Mobile Information Systems 6, no. 1 (2010): 1–3. http://dx.doi.org/10.1155/2010/201674.

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42

Núñez, J., M. J. Avedillo, and J. M. Quintana. "Domino inspired MOBILE networks." Electronics Letters 48, no. 5 (2012): 292. http://dx.doi.org/10.1049/el.2011.3295.

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43

Wiart, Joe. "Towards green mobile networks." annals of telecommunications - annales des télécommunications 67, no. 3-4 (2012): 111–12. http://dx.doi.org/10.1007/s12243-012-0294-y.

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44

Chen, Wanshi, Ilker Demirkol, Gunes Karabulut-Kurt, Miraj Mostafa, and Stefano Ruffini. "Mobile Communications and Networks." IEEE Communications Magazine 61, no. 7 (2023): 104–5. http://dx.doi.org/10.1109/mcom.2023.10192262.

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45

Liu, Zhong Yuan. "A New Network Selection Procedure Using Access Networks Consent." Applied Mechanics and Materials 496-500 (January 2014): 2007–10. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2007.

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The paper proposes a new network selection procedure using access networks consent. The proposed mechanism supports WLAN, WIMAX and 3G networks. Using mobility prediction model coupled with GIS information system the access networks at future location of mobile terminal. Using pre handover mechanisms with EAP HO NS and AAA extensions proposed in this paper the home access networks negotiate with visiting access networks and networks entities to allocate and reserve resources for accommodating mobile terminals enabling the solution proposed is efficient. Using these mechanisms the mobile termin

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46

Kim, Dae-Young, Dae-sik Ko, and Seokhoon Kim. "Network Access Control for Location-Based Mobile Services in Heterogeneous Wireless Networks." Mobile Information Systems 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6195024.

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Recent advances in information communication technology and software have enabled mobile terminals to employ various capabilities as a smartphone. They adopt multiple interfaces for wireless communication and run as a portable computer. Mobile services are also transferred from voice to data. Mobile terminals can access Internet for data services anytime anywhere. By using location-based information, improved mobile services are enabled in heterogeneous networks. In the mobile service environment, it is required that mobile terminals should efficiently use wireless network resources. In additi

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47

S.SivaNageswara Rao, Dr, Orchu Aruna, and Dr K.Lakshminadh. "Mobile ad hoc network integrated wireless networks: a survey." International Journal of Engineering & Technology 7, no. 1.9 (2018): 217. http://dx.doi.org/10.14419/ijet.v7i1.9.9827.

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Now a day, every one using mobile devices for communicating with others. The development of new technologies, like Internet of Things (IoT) needs coverage, connectivity, scalability and QoS. In ubiquity networks, the major issues are coverage, connectivity, scalability and QoS. To solve these limitations, integrating wireless networks with ad hoc networks. This paper provides detail survey on how ad hoc networks are integrated with Cellular Network, Wireless Mesh Networks and Wireless Sensor Networks. This integration may resolve the problems of coverage, connectivity, scalability and QoS.

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48

Nada, Fayza A. "Steady State Analysis of Base Station Buffer Occupancy in a Cellular Mobile System." Journal of Computer Networks and Communications 2023 (March 23, 2023): 1–13. http://dx.doi.org/10.1155/2023/1364824.

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The 3rd generation partnership project (3GPP) standards organizations makes great efforts in order to reduce the latency of 5G mobile networks to the least possible extent. Recently, these networks are associated with big buffers to maximize the network utilization and minimize the wasted wireless resources. However, in existence of the TCP congestions, having bottlenecks are still expected on radio access networks (RANs) data paths. Consequently, this influences the network performance and reduces its quality of services (QoSs). Apparently, studying and improving the behavior of buffers deplo

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49

Hailu, Dawit Hadush. "Performance Evaluation of Ethernet Network for Mobile Fronthual Networks." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 1 (2017): 287. http://dx.doi.org/10.11591/ijeecs.v7.i1.pp287-298.

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<p>Increasing mobile data traffic due to the rise of both smartphones and tablets has led to high-capacity demand of mobile data network. To meet the ever-growing capacity demand and reduce the cost of mobile network components, Cloud Radio Access Network (C-RAN) has emerged as a promising solution. In such network, the mobile operator’s Remote Radio Head (RRH) and Base Band Unit (BBU) are often separated and the connection between them has very tight timing and latency requirements imposed by Common Public Radio Interface (CPRI) and 3rd Generation Partnership Project (3GPP). This fronth

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50

Xu, Xia, Jin Tang, and Hua Xiang. "Data Transmission Reliability Analysis of Wireless Sensor Networks for Social Network Optimization." Journal of Sensors 2022 (January 6, 2022): 1–12. http://dx.doi.org/10.1155/2022/3842722.

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With the rapid development of the Internet in recent years, people are using the Internet less and less frequently. People publish and obtain information through various channels on the Internet, and online social networks have become one of the most important channels. Many nodes in social networks and frequent interactions between nodes create great difficulties for privacy protection, and some of the existing studies also have problems such as cumbersome computational steps and low efficiency. In this paper, we take the complex environment of social networks as the research background and f

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