Relevant bibliographies by topics / Wireless computing

Academic literature on the topic 'Wireless computing'

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Published: 4 June 2021
Last updated: 19 February 2023

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Journal articles on the topic "Wireless computing"

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Li, Fan, Jinyuan Chen, and Zhiying Wang. "Wireless MapReduce Distributed Computing." IEEE Transactions on Information Theory 65, no. 10 (October 2019): 6101–14. http://dx.doi.org/10.1109/tit.2019.2924621.

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Goel, Shipra. "Grid Computing integrated with Mobile computing wireless devices." International Journal of Mobile Network Communications & Telematics 1, no. 2 (December 31, 2011): 39–48. http://dx.doi.org/10.5121/ijmnct.2011.1203.

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WAKAMIYA, Naoki. "Neural Computing on Wireless Networks." IEICE ESS Fundamentals Review 14, no. 4 (April 1, 2021): 308–17. http://dx.doi.org/10.1587/essfr.14.4_308.

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Manvi, Sunilkumar S., and Mahantesh N. Birje. "Wireless Grid Computing: A Survey." IETE Journal of Education 50, no. 3 (September 2009): 119–31. http://dx.doi.org/10.1080/09747338.2009.10876059.

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Master, Neal, Aditya Dua, Dimitrios Tsamis, Jatinder Pal Singh, and Nicholas Bambos. "Adaptive Prefetching in Wireless Computing." IEEE Transactions on Wireless Communications 15, no. 5 (May 2016): 3296–310. http://dx.doi.org/10.1109/twc.2016.2519882.

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Lefor, Alan T., and Maarten K. Lefor. "Wireless computing in health care." Current Surgery 60, no. 4 (July 2003): 477–79. http://dx.doi.org/10.1016/s0149-7944(03)00087-4.

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Schumny, Harald. "Bluetooth, wireless mobile computing, eBooks." Computer Standards & Interfaces 24, no. 3 (July 2002): 189–91. http://dx.doi.org/10.1016/s0920-5489(02)00033-8.

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Patton, Janice K. "Wireless Computing in the Library." Community & Junior College Libraries 10, no. 3 (March 2002): 11–16. http://dx.doi.org/10.1300/j107v10n03_03.

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Rhyu, Sunkyung, and SangYeob Oh. "ICT-Based Wireless Personal Computing." Wireless Personal Communications 93, no. 1 (January 23, 2017): 1–5. http://dx.doi.org/10.1007/s11277-017-3955-3.

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Wang, Xingzhu. "A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing." Wireless Communications and Mobile Computing 2022 (October 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/1499736.

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In order to improve the communication security of wireless mobile network, a collaborative intrusion detection method based on cloud computing is studied. The mobile terminal and the cloud computing platform are connected by the wireless mobile network. The cloud computing platform authentication server adopts a dual server and multifactor authentication scheme for mobile cloud computing to provide authentication services for mobile terminal users. The web server of the cloud computing platform uses the intrusion node detection protocol of the neighbor classification mechanism to provide a communication security protocol for users; Using the HMM algorithm, the intrusion detection module of the computing platform realizes the intrusion detection of wireless mobile network. Finally, using authentication service, security protocol, and intrusion detection module completes the cooperative detection of mobile network intrusion. The experimental results show that this method can realize the cooperative detection of wireless mobile network intrusion, and the detection accuracy is as high as 98%, which ensures the communication security of wireless mobile network.
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Dissertations / Theses on the topic "Wireless computing"

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Datla, Dinesh. "Wireless Distributed Computing in Cloud Computing Networks." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51729.

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The explosion in growth of smart wireless devices has increased the ubiquitous presence of computational resources and location-based data. This new reality of numerous wireless devices capable of collecting, sharing, and processing information, makes possible an avenue for new enhanced applications. Multiple radio nodes with diverse functionalities can form a wireless cloud computing network (WCCN) and collaborate on executing complex applications using wireless distributed computing (WDC). Such a dynamically composed virtual cloud environment can offer services and resources hosted by individual nodes for consumption by user applications. This dissertation proposes an architectural framework for WCCNs and presents the different phases of its development, namely, development of a mathematical system model of WCCNs, simulation analysis of the performance benefits offered by WCCNs, design of decision-making mechanisms in the architecture, and development of a prototype to validate the proposed architecture. The dissertation presents a system model that captures power consumption, energy consumption, and latency experienced by computational and communication activities in a typical WCCN. In addition, it derives a stochastic model of the response time experienced by a user application when executed in a WCCN. Decision-making and resource allocation play a critical role in the proposed architecture. Two adaptive algorithms are presented, namely, a workload allocation algorithm and a task allocation - scheduling algorithm. The proposed algorithms are analyzed for power efficiency, energy efficiency, and improvement in the execution time of user applications that are achieved by workload distribution. Experimental results gathered from a software-defined radio network prototype of the proposed architecture validate the theoretical analysis and show that it is possible to achieve 80 % improvement in execution time with the help of just three nodes in the network.
Ph. D.
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Yang, Zhimin. "Opportunistic Computing in Wireless Networks." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1267743144.

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Ergüt, Salih. "Context-aware computing for wireless networks." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p3402341.

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Thesis (Ph. D.)--University of California, San Diego, 2010.
Title from first page of PDF file (viewed May 14, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
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Chen, Xuetao. "Resource Allocation for Wireless Distributed Computing Networks." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/77054.

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Wireless distributed computing networks (WDCNs) will become the next frontier of the wireless industry as the performance of wireless platforms is being increased every year and wireless industries are looking for "killer" applications for increased channel capacity. However, WDCNs have several unique problems compared with currently well-investigated methods for wireless sensor networks and wired distributed computing. For example, it is difficult for WDCNs to be power/energy efficient considering the uncertainty and heterogeneity of the wireless environment. In addition, the service model has to take account of the interference-limited feature of wireless channels to reduce the service delay. Our research proposes a two-phase model for WDCNs including the service provision phase and the service access phase according to different traffic patterns and performance requirements. For the service provision phase, we investigate the impact of communication channel conditions on the average execution time of the computing tasks within WDCNs. We then discuses how to increase the robustness and power efficiency for WDCNs subject to the impact of channel variance and spatial heterogeneity. A resource allocation solution for computation oriented WDCNs is then introduced in detail which mitigates the effects of channel variations with a stochastic programming solution. Stochastic geometry and queue theory are combined to analyze the average performance of service response time and to design optimal access strategies during the service access phase. This access model provides a framework to analyze the service access performance and evaluate whether the channel heterogeneity should be considered. Based on this analysis, optimal strategies to access the service nodes can be determined in order to reduce the service response time. In addition, network initialization and synchronization are investigated in order to build a multiple channel WDCN in dynamic spectrum access (DSA) environments. Further, an efficient primary user detection method is proposed to reduce the channel vacation latency for WDCNs in DSA environments. Finally, this dissertation presents the complete design and implementation of a WDCN on COgnitive Radio Network (CORNET). Based on SDR technologies, software dedicated to WDCNs is designed and implemented across the PHY layer, MAC layer, and application layer. System experiments are carried out to demonstrate the performance issues and solutions presented in this dissertation. Wireless distributed computing networks (WDCNs) will become the next frontier of the wireless industry as the performance of wireless platforms is being increased every year and wireless industries are looking for "killer" applications for increased channel capacity. However, WDCNs have several unique problems compared with currently well-investigated methods for wireless sensor networks and wired distributed computing. For example, it is difficult for WDCNs to be power/energy efficient considering the uncertainty and heterogeneity of the wireless environment. In addition, the service model has to take account of the interference-limited feature of wireless channels to reduce the service delay. Our research proposes a two-phase model for WDCNs including the service provision phase and the service access phase according to different traffic patterns and performance requirements. For the service provision phase, we investigate the impact of communication channel conditions on the average execution time of the computing tasks within WDCNs. We then discuses how to increase the robustness and power efficiency for WDCNs subject to the impact of channel variance and spatial heterogeneity. A resource allocation solution for computation oriented WDCNs is then introduced in detail which mitigates the effects of channel variations with a stochastic programming solution. Stochastic geometry and queue theory are combined to analyze the average performance of service response time and to design optimal access strategies during the service access phase. This access model provides a framework to analyze the service access performance and evaluate whether the channel heterogeneity should be considered. Based on this analysis, optimal strategies to access the service nodes can be determined in order to reduce the service response time. In addition, network initialization and synchronization are investigated in order to build a multiple channel WDCN in dynamic spectrum access (DSA) environments. Further, an efficient primary user detection method is proposed to reduce the channel vacation latency for WDCNs in DSA environments. Finally, this dissertation presents the complete design and implementation of a WDCN on COgnitive Radio Network (CORNET). Based on SDR technologies, software dedicated to WDCNs is designed and implemented across the PHY layer, MAC layer, and application layer. System experiments are carried out to demonstrate the performance issues and solutions presented in this dissertation.
Ph. D.
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Karra, Kiran. "Wireless Distributed Computing on the Android Platform." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/35256.

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The last couple of years have seen an explosive growth in smartphone sales. Additionally, the computational power of modern smartphones has been increasing at a high rate. For example, the popular iPhone 4S has a 1 GHz processor with 512 MB of RAM [5]. Other popular smartphones such as the Samsung Galaxy Nexus S also have similar specications. These smartphones are as powerful as desktop computers of the 2005 era, and the tight integration of many dierent hardware chipsets in these mobile devices makes for a unique mobile platform that can be exploited for capabilities other than traditional uses of a phone, such as talk and text [4]. In this work, the concept using smartphones that run the Android operating system for distributed computing over a wireless mesh network is explored. This is also known as wireless distributed computing (WDC). The complexities of WDC on mobile devices are different from traditional distributed computing because of, among other things, the unreliable wireless communications channel and the limited power available to each computing node. This thesis develops the theoretical foundations for WDC. A mathematical model representing the total amount of resources required to distribute a task with WDC is developed. It is shown that given a task that is distributable, under certain conditions, there exists a theoretical minimum amount of resources that can be used in order to perform a task using WDC. Finally, the WDC architecture is developed, an Android App implementation of the WDC architecture is tested, and it is shown in a practical application that using WDC to perform a task provides a performance increase over processing the job locally on the Android OS.
Master of Science
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Al-Turkistany, Mohammad. "Adaptation framework for wireless thin-client computing." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0013423.

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Sen, Sanjoy Kumar. "Efficient Algorithms and Framework for Bandwidth Allocation, Quality-of-Service Provisioning and Location Management in Mobile Wireless Computing." Thesis, University of North Texas, 1997. https://digital.library.unt.edu/ark:/67531/metadc278885/.

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The fusion of computers and communications has promised to herald the age of information super-highway over high speed communication networks where the ultimate goal is to enable a multitude of users at any place, access information from anywhere and at any time. This, in a nutshell, is the goal envisioned by the Personal Communication Services (PCS) and Xerox's ubiquitous computing. In view of the remarkable growth of the mobile communication users in the last few years, the radio frequency spectrum allocated by the FCC (Federal Communications Commission) to this service is still very limited and the usable bandwidth is by far much less than the expected demand, particularly in view of the emergence of the next generation wireless multimedia applications like video-on-demand, WWW browsing, traveler information systems etc. Proper management of available spectrum is necessary not only to accommodate these high bandwidth applications, but also to alleviate problems due to sudden explosion of traffic in so called hot cells. In this dissertation, we have developed simple load balancing techniques to cope with the problem of tele-traffic overloads in one or more hot cells in the system. The objective is to ease out the high channel demand in hot cells by borrowing channels from suitable cold cells and by proper assignment (or, re-assignment) of the channels among the users. We also investigate possible ways of improving system capacity by rescheduling bandwidth in case of wireless multimedia traffic. In our proposed scheme, traffic using multiple channels releases one or more channels to increase the carried traffic or throughput in the system. Two orthogonal QoS parameters, called carried traffic and bandwidth degradation, are identified and a cost function describing the total revenue earned by the system from a bandwidth degradation and call admission policy, is formulated. A channel sharing scheme is proposed for co-existing real-time and non-real-time traffic and analyzed using a Markov modulated Poisson process (MMPP) based queueing model. The location management problem in mobile computing deals with the problem of a combined management of location updates and paging in the network, both of which consume scarce network resources like bandwidth, CPU cycles etc. An easily implementable location update scheme is developed which considers per-user mobility pattern on top of the conventional location area based approach and computes an update strategy for each user by minimizing the average location management cost. The cost optimization problem is elegantly solved using a genetic algorithm.
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Jallad, A. H. M. "Distributed computing in space-based wireless sensor networks." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/773025/.

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This thesis investigates the application of distributed computing in general and wireless sensor networks in particular to space applications. Particularly, the thesis addresses issues related to the design of "space-based wireless sensor networks" that consist of ultra-small satellite nodes flying together in close formations. The design space of space-based wireless sensor networks is explored. Consequently, a methodology for designing space-based wireless sensor networks is proposed that is based on a modular architecture. The hardware modules take the form of 3-D Multi-Chip Modules (MCM). The design of hardware modules is demonstrated by designing a representative on-board computer module. The onboard computer module contains an FPGA which includes a system-on-chip architecture that is based on soft components and provides a degree of flexibility at the later stages of the design of the mission.
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Graylin, William W. (William Wang) 1968. "Addressing the complexity of multimedia wireless computing solutions." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/80624.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (leaves 98-100).
by William W. Graylin.
S.M.
M.B.A.
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Gagnon, Jason S. "Wireless communication and computing at the construction jobsite." Thesis, Virginia Tech, 1996. http://hdl.handle.net/10919/44825.

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This thesis explores the information flow at a construction site and examines how wireless communication technology can meet these information needs. The construction industry is dynamic. Therefore, traditional methods of communication have limited applicability to a construction jobsite. However, the advances in the wireless communication field are making that form of communication a viable option for the construction jobsite.

The information flow models in some other industries are examined as point of comparison with the construction industry. People in the construction industry can learn what information transmission methods have worked in other industries. Also, much can be learned from other industries that have already embraced wireless technology into their workplace.

An articulation of information needs at a construction jobsite is made. A large refinery that is under construction in Houston, Texas was the primary a source for articulating the information needs at a construction site. A detailed summary of a data reconnaissance visit to this project is included.

A methodology for identifying determining the applicability of different formats of wireless technology for a set of information needs is included. A second methodology for identifying and classifying information needs by a given company is also included. Finally, two examples of how to use these methodologies are presented.


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Books on the topic "Wireless computing"

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Williams, Veronica A. Wireless computing primer. New York: M & T Books, 1996.

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Williams, Veronica. Wireless computing primer. New York: M & T Books, 1996.

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Chandrakasan, Anantha P., and Robert W. Brodersen, eds. Technologies for Wireless Computing. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1453-0.

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Eshaghian-Wilner, Mary Mehrnoosh, ed. Wireless Computing in Medicine. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118993620.

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P, Chandrakasan Anantha, and Brodersen Robert W. 1945-, eds. Technologies for wireless computing. Boston: Kluwer Academic Publishers, 1996.

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Chandrakasan, Anantha P. Technologies for Wireless Computing. Boston, MA: Springer US, 1996.

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Wireless computing: A manager's guide to wireless networking. New York: Van Nostrand Reinhold, 1997.

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Mohsen, Guizani, ed. Wireless systems and mobile computing. Huntington, New York: Nova Science, 2001.

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Conder, Shane. Android wireless application development. 2nd ed. Boston: Pearson Educacion, Inc, 2011.

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1956-, Phillips Nigel, ed. Mobile commerce and wireless computing systems. Harlow, England: Pearson/Addison Wesley, 2004.

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Book chapters on the topic "Wireless computing"

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Cheng, Xiang, Luoyang Fang, Liuqing Yang, and Shuguang Cui. "Computing." In Wireless Networks, 35–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96116-3_4.

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Membrey, Peter, and David Hows. "WiPi: Wireless Computing." In Learn Raspberry Pi 2 with Linux and Windows 10, 193–210. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-1162-5_9.

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Membrey, Peter, and David Hows. "WiPi: Wireless Computing." In Learn Raspberry Pi with Linux, 181–97. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-4822-4_9.

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Vaezi, Mojtaba, and Ying Zhang. "Virtualization and Cloud Computing." In Wireless Networks, 11–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54496-0_2.

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Wang, Jingjing, and Chunxiao Jiang. "Mobile Edge Computing in FANET." In Wireless Networks, 197–287. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8850-8_5.

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Gao, Jie, Mushu Li, and Weihua Zhuang. "Collaborative Computing for Internet of Vehicles." In Wireless Networks, 93–121. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88743-8_4.

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Prasad, Ramjee, and Vandana Rohokale. "Cloud Computing." In Springer Series in Wireless Technology, 111–24. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31703-4_8.

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Xu, Cheng, Ce Zhang, and Jianliang Xu. "Verifiable Cloud Computing." In Encyclopedia of Wireless Networks, 1448–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_299.

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Xu, Cheng, Ce Zhang, and Jianliang Xu. "Verifiable Cloud Computing." In Encyclopedia of Wireless Networks, 1–4. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-32903-1_299-1.

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Cybenko, George. "High performance wireless computing." In Lecture Notes in Computer Science, 71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0024204.

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Conference papers on the topic "Wireless computing"

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Krishnaswamy, Dilip. "Wireless distributed computing." In the 1st International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2185216.2185228.

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Chan, Carri W., Nicholas Bambos, and Jatinder Pal Singh. "Network-Assisted Wireless Computing." In 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2008. http://dx.doi.org/10.1109/pimrc.2008.4699674.

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Li, Fan, Jinyuan Chen, and Zhiying Wang. "Wireless MapReduce Distributed Computing." In 2018 IEEE International Symposium on Information Theory (ISIT). IEEE, 2018. http://dx.doi.org/10.1109/isit.2018.8437709.

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Ba, He, Wendi Heinzelman, Charles-Antoine Janssen, and Jiye Shi. "Mobile computing - A green computing resource." In 2013 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2013. http://dx.doi.org/10.1109/wcnc.2013.6555295.

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Li, Songze, Qian Yu, Mohammad Ali Maddah-Ali, and A. Salman Avestimehr. "Edge-Facilitated Wireless Distributed Computing." In GLOBECOM 2016 - 2016 IEEE Global Communications Conference. IEEE, 2016. http://dx.doi.org/10.1109/glocom.2016.7841765.

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R Simpson, William. "Wireless Computing and it Ecosystems." In Fifth International Conference on Wireless & Mobile Networks. Academy & Industry Research Collaboration Center (AIRCC), 2013. http://dx.doi.org/10.5121/csit.2013.3705.

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Kostrzewski, Andrew A., Tomasz P. Jannson, and Stephen A. Kupiec. "Soft computing and wireless communication." In International Symposium on Optical Science and Technology, edited by Bruno Bosacchi, David B. Fogel, and James C. Bezdek. SPIE, 2001. http://dx.doi.org/10.1117/12.448328.

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Salefski, Bill, and Levent Caglar. "Re-configurable computing in wireless." In the 38th conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/378239.378459.

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Watson, T. "Application Design for Wireless Computing." In 1994 First Workshop on Mobile Computing Systems and Applications (WMCSA). IEEE, 1994. http://dx.doi.org/10.1109/wmcsa.1994.10.

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Dai, Mingjun, Jialong Yuan, Yanli Tong, Lan Wang, and Xiaohui Lin. "Computing Resource Allocation for Heterogeneous Coded Distributed Computing." In 2022 31st Wireless and Optical Communications Conference (WOCC). IEEE, 2022. http://dx.doi.org/10.1109/wocc55104.2022.9880592.

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Reports on the topic "Wireless computing"

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Kung, H. T. Wireless Computing Architecture II. Fort Belvoir, VA: Defense Technical Information Center, November 2010. http://dx.doi.org/10.21236/ada533077.

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Brian Wells. Direct Methanol Fuel Cell Power Supply For All-Day True Wireless Mobile Computing. Office of Scientific and Technical Information (OSTI), November 2008. http://dx.doi.org/10.2172/970458.

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Sauer, Jennifer. Shady Signals: Wireless Computing and Online Safety Among Internet Users Age 18 and Older. AARP Research, May 2015. http://dx.doi.org/10.26419/res.00102.001.

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Sauer, Jennifer. Shady Signals: Wireless Computing and Online Safety Among Washington Internet Users Age 18-Plus: Infographic. AARP Research, May 2015. http://dx.doi.org/10.26419/res.00102.002.

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