Academic literature on the topic 'Mobile collaborative applications'
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Journal articles on the topic "Mobile collaborative applications"
MESSEGUER, ROC, ESUNLY MEDINA, SERGIO F. OCHOA, JOSÉ A. PINO, ANDRES NEYEM, LEANDRO NAVARRO, and DOLORS ROYO. "COMMUNICATION SUPPORT FOR MOBILE COLLABORATIVE WORK: AN EXPERIMENTAL STUDY." International Journal of Information Technology & Decision Making 11, no. 06 (November 2012): 1035–63. http://dx.doi.org/10.1142/s0219622012400147.
Full textGuetmi, Nadir, and Abdessamad Imine. "Cloud patterns for mobile collaborative applications." International Journal of Intelligent Information and Database Systems 10, no. 3/4 (2017): 191. http://dx.doi.org/10.1504/ijiids.2017.087245.
Full textGuetmi, Nadir, and Abdessamad Imine. "Cloud patterns for mobile collaborative applications." International Journal of Intelligent Information and Database Systems 10, no. 3/4 (2017): 191. http://dx.doi.org/10.1504/ijiids.2017.10007786.
Full textLee, Hochul, Jaehun Lee, Young Choon Lee, and Sooyong Kang. "CollaboRoid: Mobile platform support for collaborative applications." Pervasive and Mobile Computing 55 (April 2019): 13–31. http://dx.doi.org/10.1016/j.pmcj.2019.02.006.
Full textLundin, J., and M. Magnusson. "Collaborative learning in mobile work." Journal of Computer Assisted Learning 19, no. 3 (September 2003): 273–83. http://dx.doi.org/10.1046/j.0266-4909.2003.00029.x.
Full textPark, Sanghun, Wontae Kim, and Insung Ihm. "Mobile collaborative medical display system." Computer Methods and Programs in Biomedicine 89, no. 3 (March 2008): 248–60. http://dx.doi.org/10.1016/j.cmpb.2007.11.012.
Full textMallampalli, Sasi Sekhar, and Shriya Goyal. "Mobile Applications for Developing Second Language Collaborative Writing." International Journal of Interactive Mobile Technologies (iJIM) 15, no. 07 (April 9, 2021): 185. http://dx.doi.org/10.3991/ijim.v15i07.19885.
Full textJiang, Pingyu, Leijie Fu, and Bo Yu. "Developing a mobile collaborative toolkit for industrial applications." International Journal of Internet Manufacturing and Services 2, no. 3/4 (2010): 365. http://dx.doi.org/10.1504/ijims.2010.033944.
Full textMantyjarvi, J., P. Huuskonen, and J. Himberg. "Collaborative context determination to support mobile terminal applications." IEEE Wireless Communications 9, no. 5 (October 2002): 39–45. http://dx.doi.org/10.1109/mwc.2002.1043852.
Full textNeyem, Andrés, Sergio F. Ochoa, José A. Pino, and Rubén Darío Franco. "A reusable structural design for mobile collaborative applications." Journal of Systems and Software 85, no. 3 (March 2012): 511–24. http://dx.doi.org/10.1016/j.jss.2011.05.046.
Full textDissertations / Theses on the topic "Mobile collaborative applications"
Soon, Chien Jon. "An architecture for user configurable mobile collaborative geographic applications." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/37311/1/Chien_Soon_Thesis.pdf.
Full textGolchay, Roya. "From mobile to cloud : Using bio-inspired algorithms for collaborative application offloading." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI009.
Full textNot bounded by time and place, and having now a wide range of capabilities, smartphones are all-in-one always connected devices - the favorite devices selected by users as the most effective, convenient and neces- sary communication tools. Current applications developed for smartphones have to face a growing demand in functionalities - from users, in data collecting and storage - from IoT device in vicinity, in computing resources - for data analysis and user profiling; while - at the same time - they have to fit into a compact and constrained design, limited energy savings, and a relatively resource-poor execution environment. Using resource- rich systems is the classic solution introduced in Mobile Cloud Computing to overcome these mobile device limitations by remotely executing all or part of applications to cloud environments. The technique is known as application offloading. Offloading to a cloud - implemented as geographically-distant data center - however introduces a great network latency that is not acceptable to smartphone users. Hence, massive offloading to a centralized architecture creates a bottleneck that prevents scalability required by the expanding market of IoT devices. Fog Computing has been introduced to bring back the storage and computation capabilities in the user vicinity or close to a needed location. Some architectures are emerging, but few algorithms exist to deal with the dynamic properties of these environments. In this thesis, we focus our interest on designing ACOMMA, an Ant-inspired Collaborative Offloading Middleware for Mobile Applications that allowing to dynamically offload application partitions - at the same time - to several remote clouds or to spontaneously-created local clouds including devices in the vicinity. The main contributions of this thesis are twofold. If many middlewares dealt with one or more of offloading challenges, few proposed an open architecture based on services which is easy to use for any mobile device without any special requirement. Among the main challenges are the issues of what and when to offload in a dynamically changing environment where mobile device profile, context, and server properties play a considerable role in effectiveness. To this end, we develop bio-inspired decision-making algorithms: a dynamic bi-objective decision-making process with learning, and a decision-making process in collaboration with other mobile devices in the vicinity. We define an offloading mechanism with a fine-grained method-level application partitioning on its call graph. We use ant colony algorithms to optimize bi-objectively the CPU consumption and the total execution time - including the network latency
McCaffery, Duncan James. "Supporting Low Latency Interactive Distributed Collaborative Applications in Mobile Environments." Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.524740.
Full textHommerberg, Måns. "Enriching Circuit Switched Mobile Phone Calls with Cooperative Web Applications." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-159974.
Full textJUNIOR, JONER MARTINS VEIGA DUARTE. "A FRAMEWORK FOR COLLABORATIVE USE OF MOBILE DEVICES FOR REMOTE CONTROL OF SCIENTIFIC APPLICATIONS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=21806@1.
Full textCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Hoje em dia, o uso de dispositivos móveis se tornou bastante popular e criou maneiras diferentes de interação com sua interface sensível ao toque. Aplicações de visualização científica possuem um potencial muito grande de desfrutar dessas novas formas de interação, contudo o poder de processamento dos dispositivos móveis ainda não é suficiente para renderizar e-ou tratar o grande volume de dados que esse tipo de aplicação requer. Propomos um framework, seguindo um modelo cliente-servidor, que permite a utilização de dispositivos móveis para visualização e manipulação colaborativa de aplicações de visualização científica. No papel de servidor, a aplicação científica faz uso de uma biblioteca para compactar e enviar as imagens renderizadas para os clientes e também para tratar os eventos recebidos. No papel de cliente, está um aplicativo multiplataforma (iOS-Android) rodando nos dispositivos móveis, que interpreta os gestos de toque e exibe as imagens recebidas via rede Wi-Fi. O mesmo aplicativo é capaz de conectar em qualquer servidor, pois constrói a interface baseada numa descrição em Lua que o servidor fornece. Por fim, o framework proposto é avaliado em dois aplicativos industriais: Geresim e 3DReplay.
Nowadays, mobile devices have become very popular bringing new ways of interaction with their touch-based interface. Scientific visualization applications have a great potential to take advantage of this new kind of interaction, but the processing capabilities of mobile devices are still not enough to render or process the amount of data this type of application requires. We propose a framework, working as a client-server model, which allows the use of mobile devices to collaboratively visualize and manipulate scientific visualization applications. In the server role, the scientific application uses a library to compress and send rendered images to clients and also to process received events. In the client role, there is a multiplatform application (iOS-Android) running on mobile devices, which interpret touch gestures and show the images received through Wi-Fi network. The same application is able to connect in any server, since it builds its interface from a description in Lua language supplied by the server. Lastly, we evaluate the proposed framework with two industrial applications: Geresim e 3DReplay.
Kohen-Vacs, Dan. "A Design and Development Approach for Deploying Web and Mobile Applications to Support Collaborative Seamless Learning Activities." Doctoral thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-49137.
Full textDemigha, Oualid. "Energy Conservation for Collaborative Applications in Wireless Sensor Networks." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0058/document.
Full textWireless Sensor Networks is an emerging technology enabled by the recent advances in Micro-Electro-Mechanical Systems, that led to design tiny wireless sensor nodes characterized by small capacities of sensing, data processing and communication. To accomplish complex tasks such as target tracking, data collection and zone surveillance, these nodes need to collaborate between each others to overcome the lack of battery capacity. Since the development of the batteries hardware is very slow, the optimization effort should be inevitably focused on the software layers of the protocol stack of the nodes and their operating systems. In this thesis, we investigated the energy problem in the context of collaborative applications and proposed an approach based on node selection using predictions and data correlations, to meet the application requirements in terms of energy-efficiency and quality of data. First, we surveyed almost all the recent approaches proposed in the literature that treat the problem of energy-efficiency of prediction-based target tracking schemes, in order to extract the relevant recommendations. Next, we proposed a dynamic clustering protocol based on an enhanced version of the Distributed Kalman Filter used as a prediction algorithm, to design an energy-efficient target tracking scheme. Our proposed scheme use these predictions to anticipate the actions of the nodes and their roles to minimize their number in the tasks. Based on our findings issued from the simulation data, we generalized our approach to any data collection scheme that uses a geographic-based clustering algorithm. We formulated the problem of energy minimization under data precision constraints using a binary integer linear program to find its exact solution in the general context. We validated the model and proved some of its fundamental properties. Finally and given the complexity of the problem, we proposed and evaluated a heuristic solution consisting of a correlation-based adaptive clustering algorithm for data collection. We showed that, by relaxing some constraints of the problem, our heuristic solution achieves an acceptable level of energy-efficiency while preserving the quality of data
Syed, Shah Hassan. "Development of collaborative applications for mobile phones : Implementation of the voice messaging system (VMS) using the Peer2Me framework." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8753.
Full textThis study presents the implementation of a voice messaging system using the Peer2Me framework. Voice messaging system (VMS) is an attempt for a new era of communication which is an intuitive-to-use service that adds an emotional and personal dimension to messaging. It enables the user to send voice messages in a peer-to-peer network. One of the objectives of designing VMS is to use the Peer2Me framework which is a framework for developing mobile collaborative applications on mobile phones. For this purpose an initial background study of the framework, central concepts, related technology and state of the art was carried out. We started with the realization of the idea of the VMS by defining its functional and quality requirements, software architecture and high level design. The implementation was carried out in MIDP/J2ME. The application was tested throughout the implementation process and a system test was performed on real phones on completion of the implementation phase. At the end we evaluated our work, discussed the problems we encountered, answered our research questions, gave our conclusions and described further work that could be carried out on the VMS. (All source code of the VMS is attached along with this report).
Yu, Shuai. "Multi-user computation offloading in mobile edge computing." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS462.
Full textMobile Edge Computing (MEC) is an emerging computing model that extends the cloud and its services to the edge of the network. Consider the execution of emerging resource-intensive applications in MEC network, computation offloading is a proven successful paradigm for enabling resource-intensive applications on mobile devices. Moreover, in view of emerging mobile collaborative application (MCA), the offloaded tasks can be duplicated when multiple users are in the same proximity. This motivates us to design a collaborative computation offloading scheme for multi-user MEC network. In this context, we separately study the collaborative computation offloading schemes for the scenarios of MEC offloading, device-to-device (D2D) offloading and hybrid offloading, respectively. In the MEC offloading scenario, we assume that multiple mobile users offload duplicated computation tasks to the network edge servers, and share the computation results among them. Our goal is to develop the optimal fine-grained collaborative offloading strategies with caching enhancements to minimize the overall execution delay at the mobile terminal side. To this end, we propose an optimal offloading with caching-enhancement scheme (OOCS) for femto-cloud scenario and mobile edge computing scenario, respectively. Simulation results show that compared to six alternative solutions in literature, our single-user OOCS can reduce execution delay up to 42.83% and 33.28% for single-user femto-cloud and single-user mobile edge computing, respectively. On the other hand, our multi-user OOCS can further reduce 11.71% delay compared to single-user OOCS through users' cooperation. In the D2D offloading scenario, we assume that where duplicated computation tasks are processed on specific mobile users and computation results are shared through Device-to-Device (D2D) multicast channel. Our goal here is to find an optimal network partition for D2D multicast offloading, in order to minimize the overall energy consumption at the mobile terminal side. To this end, we first propose a D2D multicast-based computation offloading framework where the problem is modelled as a combinatorial optimization problem, and then solved using the concepts of from maximum weighted bipartite matching and coalitional game. Note that our proposal considers the delay constraint for each mobile user as well as the battery level to guarantee fairness. To gauge the effectiveness of our proposal, we simulate three typical interactive components. Simulation results show that our algorithm can significantly reduce the energy consumption, and guarantee the battery fairness among multiple users at the same time. We then extend the D2D offloading to hybrid offloading with social relationship consideration. In this context, we propose a hybrid multicast-based task execution framework for mobile edge computing, where a crowd of mobile devices at the network edge leverage network-assisted D2D collaboration for wireless distributed computing and outcome sharing. The framework is social-aware in order to build effective D2D links [...]
Ventura, Raphaël. "Estimation de la pollution sonore en milieu urbain par assimilation d'observations mobiles." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS387.
Full textNoise pollution is a major environmental health problems, and the determination of populations exposure is needed. This can be done through noise mapping. Usually, maps are simulation-based, and subject to high uncertainties. Observational data is distributed in space and time and hence conveys information that is complementary to simulation data. In this thesis, we propose data assimilation methods that allow one to merge prior noise maps issued by numerical simulation with phone-acquired (via the Ambiciti app) noise observations. We run a performance analysis that addresses the range, accuracy, precision and reproducibility of measurements. Conclusions of this evaluation lead us to the proposition of a calibration strategy that has been embedded in Ambiciti. The result of the prior map and observations merging is called an analysis, and is designed to have minimum error variance, based on the respective uncertainties of both data sources that we evaluated: spatial correlations for the prior error; measurement errors, time and location representativeness for the observations. We address the estimation problem on two different scales. The first method relies on the so-called ``best linear unbiased estimator''. It produces hourly noise maps, based on temporally averaged simulation maps and mobile phone audio data recorded at the neighborhood scale. The second method leverages the crowd-sensed Ambiciti user data available throughout the covered city. The observations set must be filtered and pre-processed, in order to only select the ones that were generated in adequate conditions. The prior simulation map is then corrected in a global fashion
Book chapters on the topic "Mobile collaborative applications"
Zhang, Sheng, and Jie Wu. "Collaborative Mobile Charging." In Wireless Power Transfer Algorithms, Technologies and Applications in Ad Hoc Communication Networks, 505–31. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46810-5_19.
Full textGuo, Yi, Lynne E. Parker, and Raj Madhavan. "Collaborative Robots for Infrastructure Security Applications." In Mobile Robots: The Evolutionary Approach, 185–200. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-49720-2_9.
Full textCruz Torres, Mario Henrique, Robrecht Haesevoets, and Tom Holvoet. "CooS: Coordination Support for Mobile Collaborative Applications." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 152–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40238-8_13.
Full textShrira, Liuba, and Hong Tian. "MX: Mobile Object Exchange for Collaborative Applications." In ECOOP 2003 – Object-Oriented Programming, 126–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45070-2_7.
Full textYang, Qinglin, Xiaofei Luo, Peng Li, and Toshiaki Miyazaki. "Collaborative Inference for Mobile Deep Learning Applications." In 2nd International Conference on 5G for Ubiquitous Connectivity, 1–12. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22316-8_1.
Full textReverte, Óscar Cánovas, and Félix J. García Clemente. "Learning Technological Innovation on Mobile Applications by Means of a Spiral of Projects." In Interactive Collaborative Learning, 16–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50340-0_2.
Full textTorres, Andrei B. B., Bill Kapralos, Alvaro Uribe-Quevedo, Enilda Zea Quero, and Adam Dubrowski. "A Gamified Educational Network for Collaborative Learning." In Internet of Things, Infrastructures and Mobile Applications, 266–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49932-7_26.
Full textBourimi, Mohamed, Thomas Barth, Bernd Ueberschär, and Kesdogan Dogan. "Towards Building User-Centric Privacy-Respecting Collaborative Applications." In Intelligent Interactive Assistance and Mobile Multimedia Computing, 341–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10263-9_33.
Full textHerskovic, Valeria, Sergio F. Ochoa, José A. Pino, Pedro Antunes, and Emilio Ormeño. "Identifying the Awareness Mechanisms for Mobile Collaborative Applications." In Lecture Notes in Computer Science, 241–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41347-6_18.
Full textMechaoui, Moulay Driss, and Abdessamad Imine. "Concurrency Control for Mobile Collaborative Applications in Cloud Environments." In Studies in Big Data, 269–88. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45145-9_11.
Full textConference papers on the topic "Mobile collaborative applications"
Pichiliani, Mauro Carlos, Prasun Dewan, and Celso Massaki Hirata. "Executive Summary: Lacomo: A Layer to Develop Collaborative Mobile Applications." In XV Simpósio Brasileiro de Sistemas Colaborativos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbsc.2019.7819.
Full textMtibaa, Abderrahmen, Mohammad Abu Snober, Antonio Carelli, Roberto Beraldi, and Hussein Alnuweiri. "Collaborative Mobile-To-Mobile Computation Offloading." In 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing. ICST, 2014. http://dx.doi.org/10.4108/icst.collaboratecom.2014.257610.
Full textGallardo-Lopez, Lizbeth, Beatriz A. Gonzalez-Beltran, Roberto Garcia-Madrid, Marco Ferruzca, Irma A. Zafra-Ballinas, and Jose A. Reyes-Ortiz. "Collaborative working: Understanding mobile applications requirements." In 2015 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2015. http://dx.doi.org/10.1109/csci.2015.86.
Full textKillijian, Marc-Olivier, David Powell, Michel Ban�tre, Paul Couderc, and Yves Roudier. "Collaborative backup for dependable mobile applications." In the 2nd workshop. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1028509.1028517.
Full textWorship, G. "Will utilities need collaborative mobile applications?" In IEE Colloquium on Mobile Computing and its Applications. IEE, 1995. http://dx.doi.org/10.1049/ic:19951392.
Full textNair, Rajesh. "Collaborative innovation for future mobile applications." In 2013 IEEE Asian Solid-State Circuits Conference (A-SSCC). IEEE, 2013. http://dx.doi.org/10.1109/asscc.2013.6690970.
Full textWang, Alf Inge, Tommy Bjornsgard, and Kim Saxlund. "Peer2Me - rapid application framework for mobile peer-to-peer applications." In 2007 International Symposium on Collaborative Technologies and Systems (CTS). IEEE, 2007. http://dx.doi.org/10.1109/cts.2007.4621778.
Full textBajaj, Garvita, and Pushpendra Singh. "Sahyog: A middleware for mobile collaborative applications." In 2015 7th International Conference on New Technologies, Mobility and Security (NTMS). IEEE, 2015. http://dx.doi.org/10.1109/ntms.2015.7266518.
Full textShamsi, Jawwad, S. Ali Raza, Hassan Farid, Taha Munir, and Abbas Mehdi. "MACNET: Mobile Adhoc Collaborative NETworks." In 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing. ICST, 2014. http://dx.doi.org/10.4108/icst.collaboratecom.2014.257322.
Full textNygaard, Mads, and Hien Nam Le. "Transaction Processing with mobile collaborative works." In 2006 International Conference on Collaborative Computing: Networking, Applications and Worksharing. IEEE, 2006. http://dx.doi.org/10.1109/colcom.2006.361875.
Full textReports on the topic "Mobile collaborative applications"
Oleksiuk, Vasyl P., and Olesia R. Oleksiuk. Exploring the potential of augmented reality for teaching school computer science. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4404.
Full textChotelal, Shreshta, Marla Dukharan, Jeetendra Khadan, and Melissa Marchand. Financial Inclusion and FinTech in Suriname. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0003988.
Full textO’Brien, Tom, Deanna Matsumoto, Diana Sanchez, Caitlin Mace, Elizabeth Warren, Eleni Hala, and Tyler Reeb. Southern California Regional Workforce Development Needs Assessment for the Transportation and Supply Chain Industry Sectors. Mineta Transportation Institute, October 2020. http://dx.doi.org/10.31979/mti.2020.1921.
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