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Journal articles on the topic 'Wireless Internet'

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Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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1

Lee, Dennis Seymour. "Wireless Internet Security." Information Systems Security 11, no. 3 (July 2002): 34–50. http://dx.doi.org/10.1201/1086/43321.11.3.20020708/37898.6.

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2

Posegga, Joachim, and Simon Vetter. "Wireless Internet Security." Informatik-Spektrum 24, no. 6 (December 1, 2001): 383–86. http://dx.doi.org/10.1007/s002870100194.

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3

Radhika, R., and R. Ramachandran. "Wireless Mobile Internet." IETE Technical Review 21, no. 3 (May 2004): 191–97. http://dx.doi.org/10.1080/02564602.2004.11417145.

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4

Pichna, Roman, Tero Ojanpera, Harri Posti, and Jouni Karppinen. "Wireless Internet — IMT-2000/Wireless LAN interworking." Journal of Communications and Networks 2, no. 1 (March 2000): 46–57. http://dx.doi.org/10.1109/jcn.2000.6596596.

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5

Milivojević, Sanja, and Elizabeth Radulski. "The 'Future Internet' and crime: Towards a criminology of the Internet of Things." Crimen 11, no. 3 (2020): 255–71. http://dx.doi.org/10.5937/crimen2003255m.

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The Internet of Things (IoT) is poised to revolutionise the way we live and communicate, and the manner in which we engage with our social and natural world. In the IoT, objects such as household items, vending machines and cars have the ability to sense and share data with other things, via wireless, Bluetooth, or Radio Frequency IDentification (RFID) technology. "Smart things" have the capability to control their performance, as well as our experiences and decisions. In this exploratory paper, we overview recent developments in the IoT technology, and their relevance for criminology. Our aim is to partially fill the gap in the literature, by flagging emerging issues criminologists and social scientists ought to engage with in the future. The focus is exclusively on the IoT while other advances, such as facial recognition technology, are only lightly touched upon. This paper, thus, serves as a starting point in the conversation, as we invite scholars to join us in forecasting-if not preventing-the unwanted consequences of the "future Internet".
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6

Diponegoro, Muhammad, Wendy Yuniarto, Rusman Rusman, and Sarah Bibi. "Optimasi Kinerja Jaringan Wireless Menggunakan Repeater Berbasis Open DD-WRT Dengan Metode Drive Test Studi Kasus Pada Jaringan Internet Jurusan Teknik Elektro Politeknik Negeri Pontianak." Jurnal ELIT 3, no. 1 (April 4, 2022): 11–19. http://dx.doi.org/10.31573/elit.v3i1.380.

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Keberadaan internet ini perlu didukung oleh sinyal jaringan wireless yang stabil, karena sinyal jaringan yang stabil akan membantu kinerja dalam melakukan aktivitas e-learning. Namun pada saat ini sinyal jaringan internet wireless di Jurusan Teknik Elektro kurang stabil dan tidak dapat terkoneksi pada jam sibuk perkuliahan. Terdapat permasalahan sinyal intermet tidak dapat menjangkau suluruh tempat dan mempengaruhi aktivitas e-learning yang di lakukan. Salah satu penyebabnya yaitu ketebatasan pada access point atau hotspot pemancar internet wireless, implementasi Repeater diterapkan dengan mengamati hasi l penerapan melalui pengamatan delay, Packet loss ratio dan Bandwidth,
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7

Agius, H. "Review: Wireless Internet Handbook." Computer Bulletin 46, no. 4 (July 1, 2004): 31. http://dx.doi.org/10.1093/combul/46.4.31.

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8

Abd-Alhameed, Raed A., Bashir A. L. Gwandu, Jonathan Rodriguez, Peter S. Excell, Mohammad J. Ngala, and Abubakar Sadiq Hussaini. "Green Wireless Internet Technology." IET Science, Measurement & Technology 8, no. 6 (November 1, 2014): 337–41. http://dx.doi.org/10.1049/iet-smt.2014.0348.

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9

Zhang, Min, Vincent Marchau, Bert Van Wee, and Toon Van Der Hoorn. "Wireless Internet on Trains." Transportation Research Record: Journal of the Transportation Research Board 1977, no. 1 (January 2006): 277–85. http://dx.doi.org/10.1177/0361198106197700132.

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10

Gupta, V., and S. Gupta. "Securing the wireless internet." IEEE Communications Magazine 39, no. 12 (2001): 68–74. http://dx.doi.org/10.1109/35.968814.

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11

Hu, Fei, and Neeraj K. Sharma. "Enhancing wireless internet performance." IEEE Communications Surveys & Tutorials 4, no. 1 (2002): 2–15. http://dx.doi.org/10.1109/comst.2002.5341331.

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12

Elliott, C. "Building the wireless Internet." IEEE Spectrum 38, no. 1 (January 2001): 14–16. http://dx.doi.org/10.1109/6.893322.

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13

Braun, Torsten, Georg Carle, Yevgeni Koucheryavy, and Vassilis Tsaoussidis. "Wired/wireless Internet communications." Computer Communications 29, no. 13-14 (August 2006): 2599–600. http://dx.doi.org/10.1016/j.comcom.2006.01.014.

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14

Braun, Torsten, Georg Carle, Sonia Fahmy, and Yevgeni Koucheryavy. "Wired/wireless internet communications." Computer Communications 30, no. 7 (May 2007): 1441–42. http://dx.doi.org/10.1016/j.comcom.2006.12.029.

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15

Shin, Dong Hee. "Virtual gratifications of wireless Internet: Is wireless portable Internet reinforced by unrealized gratifications?" Telematics and Informatics 26, no. 1 (February 2009): 44–56. http://dx.doi.org/10.1016/j.tele.2007.12.003.

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16

Kouki, Rihab, Hichem Salhi, and Faouzi Bouani. "Embedded predictive control strategy based on Internet of Things technology: Application to a thermal process under imperfect wireless network." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 234, no. 7 (December 6, 2019): 775–91. http://dx.doi.org/10.1177/0959651819890954.

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This article is concerned with the design of wireless-networked control framework based on Internet of Things technology and predictive control strategy to remote control a thermal benchmark system. In order to improve the control performance of systems, an autonomous real-time solution is proposed for handling network problems. The adopted control strategy is divided into two cooperative parts under a master–slave architecture, in which two STM32 microcontrollers are investigated. The slave board is connected closely to the process and the master one is a distant controller. The microcontrollers communicate wirelessly through the Transmission Control Protocol/Internet Protocol. In the master board, a model predictive output-estimator-based controller is designed to control wirelessly the benchmark system, even though the incoming outputs from the slave board are lost. However, a buffered structure is implemented on the slave board to compensate the input losses of the arrived control sequences. The performance of the proposed wireless-networked predictive control compensation strategy for packet loss and perturbation handling in the wireless-networked control system in this work is verified through different experimentation conditions. Also, a comparative study with a wireless-networked proportional integral controller is performed to demonstrate the effectiveness of wireless-networked predictive control strategy for practical Internet of Things applications.
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17

Lee, Sangjae, and Byung Gon Kim. "User Factors Affecting Both Subscription Intention and Time for 4G Wireless Internet Service." SAGE Open 10, no. 4 (October 2020): 215824402098073. http://dx.doi.org/10.1177/2158244020980730.

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While much attention is paid to 4G wireless Internet service based on long term evolution (LTE) technology, the previous studies investigating both subscription intention and of 4G wireless Internet service time are lacking. This study attempts to fill this void by analyzing the subscription intention and time of 4G wireless Internet service users using a bivariate two-equation model. Further, as previous studies on self-efficacy and innovativeness are lacking in mobile service adoption despite the importance of user capability for adopting Internet service, this study intends to fill the void by including user technical competency representing possession of comprehensive knowledge for 4G wireless Internet service, extensive use of wireless Internet, and the use of advanced smart phone. The analysis results of bivariate two-equation model using the sample of 810 Korean users show that if users have the comprehensive knowledge for 4G wireless service, or use advanced mobile smart phone, or greatly use wireless Internet through advanced mobile smart phone, or who are male they are more likely to adopt 4G wireless service. The subscription time is shorter for the users who extensively use wireless Internet and use advanced mobile smart phone or, are male, and have high before tax monthly income. This study contributes to literature in mobile services by suggesting user technical competency as affecting subscription intention and time for 4G wireless Internet service. Managers may better concentrate their marketing efforts to the group of people using wireless Internet extensively and advanced mobile smart phone, and who are male.
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18

Al-Shafi, Shafi. "Free Wireless Internet Park Services." Journal of Cases on Information Technology 10, no. 3 (July 2008): 21–34. http://dx.doi.org/10.4018/jcit.2008070103.

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19

Banerjee, N., Wei Wu, and S. K. Das. "Mobility support in wireless Internet." IEEE Wireless Communications 10, no. 5 (October 2003): 54–61. http://dx.doi.org/10.1109/mwc.2003.1241101.

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20

Singh, S. "India Connects to Wireless Internet." IEEE Spectrum 43, no. 9 (September 2006): 20. http://dx.doi.org/10.1109/mspec.2006.1688252.

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21

Makki, S. A. M., Niki Pissinou, and Philippe Daroux. "Mobile and wireless Internet access." Computer Communications 26, no. 7 (May 2003): 734–46. http://dx.doi.org/10.1016/s0140-3664(02)00208-6.

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22

Patel, Sarvar, Zulfikar Ramzan, and Ganapathy S. Sundaram. "Security for wireless internet access." Bell Labs Technical Journal 6, no. 2 (August 14, 2002): 74–83. http://dx.doi.org/10.1002/bltj.6.

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23

Shanthi, Dr A. S., R. Sivaranjani, S. Iyyapan, N. Veeramani, and A. William James. "Wireless Home Automation System Using IOT and Node MCU Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 5238–42. http://dx.doi.org/10.22214/ijraset.2023.52759.

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Abstract: The Internet of Things commonly known as IOT (Internet of Things), refers to any device that can be connected to Internet and further controlled using it. Home Automation Systems(HAS) involves the control and automation of lighting, ventilation, security. A wireless home automation system is developed in way that a different set of tasks are performed automatically. This system allows one to wirelessly control lights, fans, air conditioners, television sets, security cameras, etc.
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24

Sapavath, Naveen Naik, and Danda B. Rawat. "Wireless Virtualization Architecture: Wireless Networking for Internet of Things." IEEE Internet of Things Journal 7, no. 7 (July 2020): 5946–53. http://dx.doi.org/10.1109/jiot.2019.2942542.

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25

Fletcher, Michael, Eric Paulz, Devin Ridge, and Alan J. Michaels. "Low-Latency Wireless Network Extension for Industrial Internet of Things." Sensors 24, no. 7 (March 26, 2024): 2113. http://dx.doi.org/10.3390/s24072113.

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The timely delivery of critical messages in real-time environments is an increasing requirement for industrial Internet of Things (IIoT) networks. Similar to wired time-sensitive networking (TSN) techniques, which bifurcate traffic flows based on priority, the proposed wireless method aims to ensure that critical traffic arrives rapidly across multiple hops to enable numerous IIoT use cases. IIoT architectures are migrating toward wirelessly connected edges, creating a desire to extend TSN-like functionality to a wireless format. Existing protocols possess inherent challenges to achieving this prioritized low-latency communication, ranging from rigidly scheduled time division transmissions, scalability/jitter of carrier-sense multiple access (CSMA) protocols, and encryption-induced latency. This paper presents a hardware-validated low-latency technique built upon receiver-assigned code division multiple access (RA-CDMA) techniques to implement a secure wireless TSN-like extension suitable for the IIoT. Results from our hardware prototype, constructed on the IntelFPGA Arria 10 platform, show that (sub-)millisecond single-hop latencies can be achieved for each of the available message types, ranging from 12 bits up to 224 bits of payload. By achieving one-way transmission of under 1 ms, a reliable wireless TSN extension with comparable timelines to 802.1Q and/or 5G is achievable and proven in concept through our hardware prototype.
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26

Zhou, Bing. "A Wireless Internet of Things Architecture Based on Mobile Internet." International Journal of Online Engineering (iJOE) 13, no. 10 (November 7, 2017): 132. http://dx.doi.org/10.3991/ijoe.v13i10.7745.

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<p><span style="font-size: small;"><span style="font-family: Times New Roman;">In order to develop a valid wireless Internet of things system, a wireless Internet of things framework based on mobile Internet is designed. The architecture of the Internet of things determines the architecture of the Internet of things business platform. There is no uniform standard for the architecture of the Internet of things service platform. The Internet of things business platform is mostly in an isolated state. The platform uses the common information management platform of Internet websites to manage mobile internet. Combined with the technologies of perception, identification and network transmission in the Internet of things technology, it is a content management Web management information system with both B/S (Browser/Server) and C/S structure (Client/Server). The platform can operate anywhere, and can give full play to the processing capacity of the client PC, and greatly reduce the application server running data load. The experimental results show that compared with the centralized database system, in the same piece of redundant condition, when the test table data is greater than the 1 million and the concurrent number is 100, the distributed database system has shorter concurrent query time and faster system response rate. Based on the above finding, it is concluded that wireless Internet of things technology based on mobile Internet will promote the development of the whole logistics industry and other related industries.</span></span></p>
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27

Ijemaru, Gerald K., Kenneth L. M. Ang, and Jasmine K. P. Seng. "Mobile Collectors for Opportunistic Internet of Things in Smart City Environment with Wireless Power Transfer." Electronics 10, no. 6 (March 16, 2021): 697. http://dx.doi.org/10.3390/electronics10060697.

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In the context of Internet of Things (IoT) for Smart City (SC) applications, Mobile Data Collectors (MDCs) can be opportunistically exploited as wireless energy transmitters to recharge the energy-constrained IoT sensor-nodes placed within their charging vicinity or coverage area. The use of MDCs has been well studied and presents several advantages compared to the traditional methods that employ static sinks. However, data collection and transmission from the hundreds of thousands of sensors sparsely distributed across virtually every smart city has raised some new challenges. One of these concerns lies in how these sensors are being powered as majority of the IoT sensors are extremely energy-constrained owing to their smallness and mode of deployments. It is also evident that sensor-nodes closer to the sinks dissipate their energy faster than their counterparts. Moreover, battery recharging or replacement is impractical and incurs very large operational costs. Recent breakthrough in wireless power transfer (WPT) technologies allows the transfer of energy to the energy-hungry IoT sensor-nodes wirelessly. WPT finds applications in medical implants, electric vehicles, wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs), mobile phones, and so on. The present study highlights the use of mobile collectors (data mules) as wireless power transmitters for opportunistic IoT-SC operations. Specifically, mobile vehicles used for data collection are further exploited as wireless power transmitters (wireless battery chargers) to wirelessly recharge the energy-constrained IoT nodes placed within their coverage vicinity. This paper first gives a comprehensive survey of the different aspects of wireless energy transmission technologies—architecture, energy sources, IoT energy harvesting modes, WPT techniques and applications that can be exploited for SC scenarios. A comparative analysis of the WPT technologies is also highlighted to determine the most energy-efficient technique for IoT scenarios. We then propose a WPT scheme that exploits vehicular networks for opportunistic IoT-SC operations. Experiments are conducted using simulations to evaluate the performance of the proposed model and to investigate WPT efficiency of a power-hungry opportunistic IoT network for different trade-off factors.
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28

Nourildean, Shayma Wail, Mustafa Dhia Hassib, and Yousra Abd Mohammed. "Internet of things based wireless sensor network: a review." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (July 1, 2022): 246. http://dx.doi.org/10.11591/ijeecs.v27.i1.pp246-261.

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Recently, Internet of Things (IoT) technologies are developing technology with a variety of applications. The Internet of Things (IoTs) is defined as a network of ordinary objects such as Internet TVs, smartphones, actuators and sensors that are smartly connected together to enable new types of communication between people and things as well as between things themselves. Wireless sensor networks (WSNs) play an important part in Internet of Things (IoT) technology. A contribution to wireless sensor networks and IoT applications is wireless sensor nodes’ construction with high-speed CPUs and low-power radio links. The IoT-based wireless Sensor network (WSN) is a game-changing smart monitoring solution. ZigBee standard is an important wireless sensor network (WSN) and Internet of Things (IoT) communication protocol in order to facilitate low-power, low-cost IoT applications and to handle numerous network topologies. This paper presented a review on the energy efficient and routing topologies of ZigBee WSN, applications of IoT enabled Wireless Sensor Network as well IoT WSN security challenges.
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29

Seung-Que Lee, Namhun Park, Choongho Cho, Hyongwoo Lee, and Seungwan Ryu. "The wireless broadband (wibro) system for broadband wireless internet services." IEEE Communications Magazine 44, no. 7 (September 2006): 106–12. http://dx.doi.org/10.1109/mcom.2006.1668390.

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30

Arokia Nerling Rasoni, G., A. Babisha, and A. Priyanka. "Energy Distribution Management Using Internet of Things." Journal of Computational and Theoretical Nanoscience 17, no. 4 (April 1, 2020): 1911–15. http://dx.doi.org/10.1166/jctn.2020.8465.

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The development of automatic Power management system is presented in this paper. The power management system is consists of WIFI Digital Power meters installed in every consumer unit and an Electricity e-Billing system at the energy provider side. The WI-FI Digital Power meter (ZPM) is a single phase digital kWh power meter with embedded WIFI modem which utilize the Wireless sensor network to send its power usage reading using information back to the energy provider wirelessly. In Power management system the priority will be given to the devices depends upon our requirement.
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31

Zhang, Xiaoqiang. "An Intelligent Wireless Charger Based on the Internet of Things." Security and Communication Networks 2021 (November 10, 2021): 1–12. http://dx.doi.org/10.1155/2021/5558914.

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With the development of the times and the progress of science and technology, people continue to explore new possibilities; the leap from wired to wireless is one of them, breaking the limitations. Similar to wireless mice and wireless microphones, this paper aims to study an Internet of Things-based smart wireless charger that, by using mathematical analysis and wireless charging technology, requires experiments to include wireless charging stations, associated chip areas, and home gateways that are used in combination with them. In the experiment, the control circuit, transmit circuit, and reception circuit of wireless charger are studied, and the wireless charging system is analyzed and calculated in detail, and a wireless charger is designed. Electromagnetic field sensing, radio wave transmission, and resonance methods are applied to achieve the shortest charging time and the best quality in order to prevent the charger from heating and burning during charging. Experimental data show that this Internet of Things-based smart wireless charger can fully replace wired chargers for 99% of small appliances; the charging efficiency of large electrical appliances such as desktop computer is also 1.4 to 1.6 times increased. Experimental data show that this Internet of Things-based smart wireless charger can efficiently and conveniently charge electrical appliances; however it is relatively expensive; the required technology is relatively complex but can make charging more efficient. It can be seen that wireless charging has a major breakthrough in the concept of future charging.
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32

Deng, Der-Jiunn, Xun Yang, and Mohammed Atiquzzaman. "Editorial: Recent Advances in Wireless Internet." Mobile Networks and Applications 26, no. 3 (January 15, 2021): 1068–69. http://dx.doi.org/10.1007/s11036-020-01716-y.

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33

Kook, Jung Gak, and Hee Wan Kim. "Hacking Countermeasures for Wireless Internet Service." Journal of Service Research and Studies 6, no. 3 (September 30, 2016): 79–90. http://dx.doi.org/10.18807/jsrs.2016.6.3.079.

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34

Liu, Wei, K. T. Chau, Calvin C. T. Chow, and Christopher H. T. Lee. "Wireless Energy Trading in Traffic Internet." IEEE Transactions on Power Electronics 37, no. 4 (April 2022): 4831–41. http://dx.doi.org/10.1109/tpel.2021.3118458.

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35

Lee, Hoon. "DiffServ-Aware Pricing for Wireless Internet." Journal of Korean Institute of Communications and Information Sciences 37, no. 7B (July 31, 2012): 550–64. http://dx.doi.org/10.7840/kics.2012.37.7b.550.

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36

Loo, Alfred, and Charlie Choi. "Infrastructure for games on wireless Internet." Electronic Library 22, no. 1 (February 2004): 8–15. http://dx.doi.org/10.1108/02640470410520069.

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37

Flammia, G. "The wireless Internet today and tomorrow." IEEE Intelligent Systems 15, no. 5 (September 2000): 82–83. http://dx.doi.org/10.1109/5254.889109.

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38

Dutta, Ashutosh, Tao Zhang, Sunil Madhani, Kenichi Taniuchi, Kensaku Fujimoto, Yasuhiro Katsube, Yoshihiro Ohba, and Henning Schulzrinne. "Secure universal mobility for wireless Internet." ACM SIGMOBILE Mobile Computing and Communications Review 9, no. 3 (July 2005): 45–57. http://dx.doi.org/10.1145/1094549.1094557.

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39

Kalden, R., I. Meirick, and M. Meyer. "Wireless Internet access based on GPRS." IEEE Personal Communications 7, no. 2 (April 2000): 8–18. http://dx.doi.org/10.1109/98.839328.

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40

Tully, John, and Arnis Riekstins. "Licence-free wireless internet access technologies." Computer Networks 31, no. 21 (November 1999): 2205–13. http://dx.doi.org/10.1016/s1389-1286(99)00096-1.

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41

Lehr, William, and Lee W. McKnight. "Wireless Internet access: 3G vs. WiFi?" Telecommunications Policy 27, no. 5-6 (June 2003): 351–70. http://dx.doi.org/10.1016/s0308-5961(03)00004-1.

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42

Marx-Perez, E., and J. Sole-Pareta. "Accessing internet applications from wireless computers." Computer Standards & Interfaces 20, no. 6-7 (March 1999): 426–27. http://dx.doi.org/10.1016/s0920-5489(99)90847-4.

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43

I, Chih-Lin, Shuangfeng Han, Zhikun Xu, Sen Wang, Qi Sun, and Yami Chen. "New Paradigm of 5G Wireless Internet." IEEE Journal on Selected Areas in Communications 34, no. 3 (March 2016): 474–82. http://dx.doi.org/10.1109/jsac.2016.2525739.

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44

Lu, June, Chun‐Sheng Yu, Chang Liu, and James E. Yao. "Technology acceptance model for wireless Internet." Internet Research 13, no. 3 (August 2003): 206–22. http://dx.doi.org/10.1108/10662240310478222.

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45

Dey, Lipika, B. Raghu, Hitesh Sharma, and Amit Sharma. "Bringing Internet Services to Wireless Devices." IETE Technical Review 18, no. 4 (July 2001): 295–305. http://dx.doi.org/10.1080/02564602.2001.11416975.

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46

Goodman, D. J. "The wireless Internet: promises and challenges." Computer 33, no. 7 (July 2000): 36–41. http://dx.doi.org/10.1109/2.869368.

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47

Jajszczyk, A. "The wireless mobile internet [Book Review]." IEEE Communications Magazine 41, no. 12 (December 2003): 8–10. http://dx.doi.org/10.1109/mcom.2003.1252793.

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48

Leavitt, Neal. "Will wap deliver the wireless internet?" Computer 33, no. 5 (May 2000): 16–20. http://dx.doi.org/10.1109/mc.2000.841780.

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49

Dutta-Roy, A. "Fixed wireless routes for Internet access." IEEE Spectrum 36, no. 9 (September 1999): 61–69. http://dx.doi.org/10.1109/6.789600.

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50

Battiti, Roberto, Marco Conti, and Renato Lo Cigno. "Internet Wireless Access: 802.11 and Beyond." Mobile Networks and Applications 11, no. 2 (March 31, 2006): 213–14. http://dx.doi.org/10.1007/s11036-005-4473-1.

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