Academic literature on the topic 'Applications collaboratives mobiles'

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Journal articles on the topic "Applications collaboratives mobiles"

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Guetmi, 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.

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Guetmi, 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.

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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.

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Advances in mobile computing and wireless communication are easing the evolution from traditional nomadic work to computer-mediated mobile collaborative work. Technology allows efficient and effective interaction among mobile users and also provides access to shared resources available to them. However, the features and capabilities of the communication infrastructure supporting these activities influence the type of coordination and collaboration employed by mobile collaborative applications in real work scenarios. Developers of these applications are typically unaware of the constraints the communication infrastructure imposes on mobile collaborative systems, because they are not easy to foresee. That leads to a high probability of communication problems in otherwise fully functional mobile collaborative support applications. This paper presents an experimental study with real devices and networks on a realistic physical environment that shows how ad hoc networks can effectively support mobile collaborative work and the practical limitations. The paper analyzes several networking issues and determines how they influence mobile collaborative work in various interaction scenarios. The paper also presents the lessons learned in the study and provides recommendations to deal with some networking issues related to real-world ad hoc networks.
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Lee, 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.

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Hagiwara, Takuma, Kazuki Takashima, Morten Fjeld, and Yoshifumi Kitamura. "CamCutter: Impromptu Vision-Based Cross-Device Application Sharing." Interacting with Computers 31, no. 6 (November 1, 2019): 539–54. http://dx.doi.org/10.1093/iwcomp/iwz035.

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Abstract As the range of handheld, mobile and desktop devices expands and worldwide demand for collaborative application tools increases, there is a growing need for higher speed impromptu cross-device application sharing to keep up with workplace requirements for on-site or remote collaborations. To address this, we have developed CamCutter, a cross-device interaction technique enabling a user to quickly select and share an application running on another screen using the camera of a handheld device. This technique can accurately identify the targeted application on a display using our adapted computer vision algorithm, system architecture and software implementation, allowing impromptu real-time and synchronized application sharing between devices. For desktop and meeting room set-ups, we performed a technical evaluation, measuring accuracy and speed of migration. For a single-user reading task and a collaborative composition task, we carried out a user study comparing our technique with commercial screen sharing applications. The results of this study showed both higher performance and preference for our system. Finally, we discuss CamCutter’s limitations and present insights for future vision-based cross-device application sharing.
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Aurand, Martin. "Making a Collaborative Mobile Architectural Guidebook Application." Art Documentation: Journal of the Art Libraries Society of North America 36, no. 2 (September 2017): 322–31. http://dx.doi.org/10.1086/694247.

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Lundin, 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.

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Mallampalli, 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.

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<p>Developing writing skills in a foreign language is one of the demanding tasks for both teachers and students. It not only demands extensive reading and intensive practice in writing both inside and outside the classroom but also timely feedback and error-correction. The experimental study aimed at studying the impact of collaborative writing tasks using mobile applications like <em>WhatsApp</em>, <em>Google Docs</em>, and <em>Google Slides</em> on enhancing the writing ability at the pre-intermediate level of Common European Frame of Reference (CEFR). The participants were tertiary level students of Cihan University who were randomly divided into two equal groups (n=28). One group used <em>WhatsApp</em> and the other group used the <em>Google Docs</em> and <em>Google Slides</em> apps on their mobile devices. The comparative study analyzed the impact of each application on improving the writing skills of the students with pretest and posttest results and semi-structured interviews. The results indicated that the participants who used <em>Google Docs</em> and <em>Google Slides</em> apps have performed better than the participants in the <em>WhatsApp</em> group. The results have implications for teachers teaching writing skills and students who write using mobile applications.</p>
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Jiang, 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.

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Mantyjarvi, 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.

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Dissertations / Theses on the topic "Applications collaboratives mobiles"

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Guetmi, Nadir. "Modèles de conception pour des applications collaboratives dans le cloud." Thesis, Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2016. http://www.theses.fr/2016ESMA0016/document.

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De nos jours, nous assistons à une énorme avancée des applications collaboratives mobiles. Ces applications tirentparti de la disponibilité croissante des réseaux de communication et de l’évolution impressionnante des dispositifsmobiles. Cependant, même avec un développement en accélération, ils demeurent toujours pauvres en ressources(une courte durée de vie des batteries et une connexion réseau instable) et moins sécurisés. Dans le cadre de notretravail, nous proposons une nouvelle approche basée sur le déploiement des tâches de collaboration mobile versle cloud. La gestion d’une virtualisation efficace assurant la continuité de la collaboration pour des réseaux pairà-pair est une tâche très difficile. En effet, l’aspect dynamique des groupes (où les utilisateurs peuvent joindre,quitter ou changer de groupes) ainsi qu’une vulnérabilité aux pannes peuvent affecter la collaboration. En outre,la conception de telles applications doit prendre en compte l’hétérogénéité des environnements cloud et mobile.Contrairement aux travaux existants , nous proposons une architecture réutilisable de haut niveau basée sur les patronsde conception et qui peut être facilement adaptée à plusieurs environnements clouds et mobiles hétérogènes.Nos modèles ont été utilisés comme base pour la conception de : (i) MidBox, une plate-forme virtuelle pour exécuterdes applications collaboratives mobiles sur un cloud privé et (ii) MobiRDF, un service de cloud décentralisépour la manipulation en temps réel des connaissances via des documents RDF partagés
Nowadays we assist to an enormous progress of mobile collaborative applications. These applications take advantage of the increasing availability of communication networks and the impressive evolution of mobile devices. However, even with a developing acceleration, they are still poor in resources (short life of batteries andunstable network connections) and less secure. In the context of our work, we propose a new approach based on the deployment of mobile collaboration tasks to the cloud. The management of efficient virtualization ensuring continuity of collaboration in peer-to-peer networks is a very difficult task. Indeed, the dynamic aspect of the groups (where users can join, leave or change groups) and a vulnerability to failures can affect the collaboration.In addition, the design of such applications must consider the heterogeneity of cloud and mobile environments.Unlike existing works, we propose a reusable high-level architecture based on patterns design, which can be easily adapted to heterogeneous clouds and mobile environments. Our models have been used as basis for the design of:(i) MidBox, a virtual platform for running mobile collaborative applications on a private cloud and (ii) MobiRDFa decentralized cloud service for real-time manipulation of knowledge via shared RDF documents
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Yu, Shuai. "Multi-user computation offloading in mobile edge computing." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS462.

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Mobile Edge Computing (MEC) est un modèle informatique émergent qui étend le cloud et ses services à la périphérie du réseau. Envisager l'exécution d'applications émergentes à forte intensité de ressources dans le réseau MEC, le déchargement de calcul est un paradigme éprouvé réussi pour activer des applications gourmandes en ressources sur les appareils mobiles. De plus, compte tenu de l'émergence de l'application collaborative mobile (MCA), les tâches déchargées peuvent être dupliquées lorsque plusieurs utilisateurs se trouvent à proximité. Cela nous motive à concevoir un schéma de déchargement de calcul collaboratif pour un réseau MEC multi-utilisateurs. Dans ce contexte, nous étudions séparément les schémas de déchargement par calcul collaboratif pour les scénarios de déchargement de MEC, de déchargement de périphérique à périphérique (D2D) et de déchargement hybride, respectivement. Dans le scénario de déchargement de MEC, nous supposons que plusieurs utilisateurs mobiles déchargent des tâches de calcul dupliquées sur les serveurs de périphérie du réseau et partagent les résultats de calcul entre eux. Notre objectif est de développer les stratégies optimales de déchargement collaboratif avec des améliorations de mise en cache afin de minimiser le délai d'exécution global du côté du terminal mobile. À cette fin, nous proposons un déchargement optimal avec un schéma d'amélioration de la mise en cache (OOCS) pour le scénario femto-cloud et le scénario d'informatique mobile, respectivement. Les résultats de la simulation montrent que comparé à six solutions alternatives dans la littérature, notre OOCS mono-utilisateur peut réduire les délais d'exécution jusqu'à 42,83% et 33,28% respectivement pour le femto-cloud mono-utilisateur et l'informatique mobile mono-utilisateur. D'un autre côté, notre système OOCS multi-utilisateur peut encore réduire le délai de 11,71% par rapport à l'OOCS mono-utilisateur grâce à la coopération des utilisateurs. Dans le scénario de déchargement D2D, nous supposons que lorsque des tâches de calcul en double sont traitées sur des utilisateurs mobiles spécifiques et que les résultats de calcul sont partagés via le canal de multidiffusion Device-to-Device (D2D). Notre objectif ici est de trouver une partition réseau optimale pour le déchargement multicast D2D, afin de minimiser la consommation d'énergie globale du côté du terminal mobile. À cette fin, nous proposons d'abord un cadre de déchargement de calcul basé sur la multidiffusion D2D où le problème est modélisé comme un problème d'optimisation combinatoire, puis résolu en utilisant les concepts de correspondance bipartite pondérée maximale et de jeu de coalition. Notez que notre proposition considère la contrainte de délai pour chaque utilisateur mobile ainsi que le niveau de la batterie pour garantir l'équité. Pour évaluer l'efficacité de notre proposition, nous simulons trois composants interactifs typiques. Les résultats de la simulation montrent que notre algorithme peut réduire considérablement la consommation d'énergie et garantir l'équité de la batterie entre plusieurs utilisateurs en même temps. Nous étendons ensuite le déchargement du D2D au déchargement hybride en tenant compte des relations sociales. Dans ce contexte, nous proposons un cadre d'exécution de tâches hybride multicast pour l'informatique mobile, où une foule d'appareils mobiles à la périphérie du réseau s'appuient sur la collaboration D2D assistée par réseau pour l'informatique distribuée sans fil et le partage des résultats. Le cadre est socialement conscient afin de construire des liens D2D efficaces. Un objectif clé de ce cadre est de mettre en place une politique d'attribution de tâches écoénergétique pour les utilisateurs mobiles. Pour ce faire, nous introduisons d'abord le modèle de système de déchargement de calcul hybride social-aware, puis nous formulons le problème d'affectation de tâches économe en énergie en prenant en compte les contraintes nécessaires [...]
Mobile 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 [...]
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Demigha, Oualid. "Energy Conservation for Collaborative Applications in Wireless Sensor Networks." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0058/document.

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Les réseaux de capteurs sans fil est une technologie nouvelle dont les applications s'étendent sur plusieurs domaines: militaire, scientifique, médicale, industriel, etc. La collaboration entre les noeuds capteurs, caractérisés par des capacités minimales en termes de capture, de transmission, de traitement et d'énergie, est une nécessité pour réaliser des tâches aussi complexes que la collecte des données, le pistage des objets mobiles, la surveillance des zones sensibles, etc. La contrainte matérielle sur le développement des ressources énergétiques des noeuds capteurs est persistante. D'où la nécessité de l'optimisation logicielle dans les différentes couches de la pile protocolaire et du système d'exploitation des noeuds. Dans cette thèse, nous approchons le problème d'optimisation d'énergie pour les applications collaboratives via les méthodes de sélection des capteurs basées sur la prédiction et la corrélation des données issues du réseau lui-même. Nous élaborons plusieurs méthodes pour conserver les ressources énergétiques du réseau en utilisant la prédiction comme un moyen pour anticiper les actions des noeuds et leurs rôles afin de minimiser le nombre des noeuds impliqués dans la tâche en question. Nous prenons l'application de pistage d'objets mobiles comme un cas d'étude. Ceci, après avoir dresser un état de l'art des différentes méthodes et approches récentes utilisées dans ce contexte. Nous formalisons le problème à l'aide d'un programme linéaire à variables binaires dans le but de trouver une solution générale exacte. Nous modélisons ainsi le problème de minimisation de la consommation d'énergie des réseaux de capteurs sans fil, déployé pour des applications de collecte de données soumis à la contrainte de précision de données, appelé EMDP. Nous montrons que ce problème est NP-Complet. D'où la nécessité de solutions heuristiques. Comme solution approchée, nous proposons un algorithme de clustering dynamique, appelé CORAD, qui adapte la topologie du réseau à la dynamique des données capturées afin d'optimiser la consommation d'énergie en exploitant la corrélation qui pourrait exister entre les noeuds. Toutes ces méthodes ont été implémentées et testées via des simulations afin de montrer leur efficacité
Wireless 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
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Golchay, Roya. "From mobile to cloud : Using bio-inspired algorithms for collaborative application offloading." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI009.

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Actuellement les smartphones possèdent un grand éventail de fonctionnalités. Ces objets tout en un, sont constamment connectés. Il est l'appareil favori plébiscité par les utilisateurs parmi tous les dispositifs de communication existants. Les applications actuelles développées pour les smartphones doivent donc faire face à une forte augmentation de la demande en termes de fonctionnalités tandis que - dans un même temps - les smartphones doivent répondre à des critères de compacité et de conception qui les limitent en énergie et à un environnement d'exécution pauvre en ressources. Utiliser un système riche en ressource est une solution classique introduite en informatique dans les nuages mobiles (Mobile Cloud Computing), celle-ci permet de contourner les limites des appareils mobiles en exécutant à distance, toutes ou certaines parties des applications dans ces environnements de nuage. Certaines architectures émergent, mais peu d'algorithmes existent pour traiter les propriétés dynamiques de ces environnements. Dans cette thèse, nous focalisons notre intérêt sur la conception d'ACOMMA (Ant-inspired Collaborative Offloading Middleware for Mobile Applications), un interlogiciel d'exécution déportée collaborative inspirée par le comportement des fourmis, pour les applications mobiles. C'est une architecture orientée service permettant de décharger dynamiquement des partitions d'applications, de manière simultanée, sur plusieurs clouds éloignés ou sur un cloud local créé spontanément, incluant les appareils du voisinage. Les principales contributions de cette thèse sont doubles. Si beaucoup d'intergiciels traitent un ou plusieurs défis relatifs à l'éxecution déportée, peu proposent une architecture ouverte basée sur des services qui serait facile à utiliser sur n'importe quel support mobile sans aucun exigence particulière. Parmi les principaux défis il y a les questions de quoi et quand décharger dans cet environnement très dynamique. A cette fin, nous développons des algorithmes de prises de décisions bio-inspirées : un processus de prise de décision bi-objectif dynamique avec apprentissage et un processus de prise de décision en collaboration avec les autres dispositifs mobiles du voisinage. Nous définissons un mécanisme de dépôt d'exécution avec une méthode de partitionnement grain fin de son graphe d'appel. Nous utilisons les algorithmes des colonies de fourmis pour optimiser bi-objectivement la consommation du CPU et le temps total d'exécution, en incluant la latence du réseau. Nous montrons que les algorithmes des fourmis sont plus facilement re-adaptables face aux modifications du contexte, peuvent être très efficaces en ajoutant des algorithmes de cache par comparaison de chaîne (string matching caching) et autorisent facilement la dissémination du profil de l'application afin de créer une exécution déportée collaborative dans le voisinage
Not 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
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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.

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Geographic information is increasingly being touted for use in research and industrial projects. While the technology is now available and affordable, there is a lack of easy to use software that takes advantage of geographic information. This is an important problem because users are often researchers or scientists who have insufficient software skills, and by providing applications that are easier to use, time and financial resources can be taken from training and be better applied to the actual research and development work. A solution for this problem must cater for the user and research needs. In particular it must allow for mobile operation for fieldwork, flexibility or customisability of data input, sharing of data with other tools and collaborative capabilities for the usual teamwork environment. This thesis has developed a new architecture and data model to achieve the solution. The result is the Mobile Collaborative Annotation framework providing an implementation of the new architecture and data model. Mobile Collaborative Mapping implements the framework as a Web 2.0 mashup rich internet application and has proven to be an effective solution through its positive application to a case study with fieldwork scientists. This thesis has contributed to research into mobile computing, collaborative computing and geospatial systems by creating a simpler entry point to mobile geospatial applications, enabling simplified collaboration and providing tangible time savings.
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Kheiravar, Salma. "MACL, a mobile application for Collaborative Learning." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45568.

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Collaborative Learning actively engages students in group activities and is known as a very effective teaching and learning technique. Collaborative Learning emphases student-instructor and student-student collaboration during the learning process. Tablets can be used in a variety of ways to maximize the effectiveness of Collaborative Learning. Currently, the existing solutions focus on student-instructor in-class collaboration because of their physical features (lightness, screen size, easy to carry, touch interactions, etc.). This thesis explores the use of tablets to help instructors and students collaborate in real-time both during the class and outside the class. In this thesis, I propose a real-time collaborative approach for student-student and student-instructor interaction and present a prototype with emphasis on student-student interaction. The developed prototype allows students to solve flowchart problems individually or collaboratively either in a face-to-face or an on-line environment. A study is conducted to evaluate the usability of the system and to determine its effectiveness for Collaborative Learning. During the study, students were randomly assigned to 3 groups (individual group work, face-to-face group work, on-line group work). All groups solved 2 flowchart problems both on paper and using the prototype. The results suggest that the prototype is motivating and easy to use. It also increases the amount of in-group discussion and provides an equivalent opportunity for students to contribute to the problem in comparison to a paper version of the exercise.
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Shurtz, Richard S. "Application Sharing from Mobile Devices with a Collaborative Shared Display." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/4084.

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With the increasing ubiquity of smartphones, tablets, and large pixel-rich displays, there are many exciting new possibilities for using these devices for collaborative work. While there already exist hardware and software that support communication and interaction between mobile devices and shared displays, application sharing in these scenarios is still limited and inflexible. We present a new method of application sharing which allows collaborators to download clips or snapshots of each other's applications. These snapshots can be used to re-launch and resume the shared application back to the state it was in when it was shared. We have built a system that supports sharing, annotating, organizing, and downloading these applications to and from a LearnSpace server. We have built an application framework which allows Android applications to be built for this system while only requiring minimal changes to the program. We also describe solutions for extending our solution to new types of collaborative displays and to other application platforms.
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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.

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Hommerberg, 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.

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The thesis investigates the possibility to enrich standard mobile phone calls with cooperative web applications. Originating from the research field know as Computer Supported Cooperative Work (CSCW) this thesis report introduces and describes the implementation of several applications which can be used by the calling parties together during a phone call. Additionally, the report describes a proof-of-concept prototype for the Android platform, and discusses the performance of cooperative web application running on mobile devices in terms of network and CPU use. The conclusions of the thesis describe a prototype application addressing and implementing the requirements as described by the theory of computer supported collaborated work. The performance of the running application showed to be satisfactory, both regarding to network demand and processor use.
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Elvander, Adam. "Developing a Recommender System for a Mobile E-commerce Application." Thesis, Uppsala universitet, Avdelningen för datalogi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256747.

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This thesis describes the process of conceptualizing and developing a recommendersystem for a peer-to-peer commerce application. The application in question is calledPlick and is a vintage clothes marketplace where private persons and smaller vintageretailers buy and sell secondhand clothes from each other. Recommender systems is arelatively young field of research but has become more popular in recent years withthe advent of big data applications such as Netflix and Amazon. Examples ofrecommender systems being used in e-marketplace applications are however stillsparse and the main contribution of this thesis is insight into this sub-problem inrecommender system research. The three main families of recommender algorithmsare analyzed and two of them are deemed unfitting for the e-marketplace scenario.Out of the third family, collaborative filtering, three algorithms are described,implemented and tested on a large subset of data collected in Plick that consistsmainly of clicks made by users on items in the system. By using both traditional andnovel evaluation techniques it is further shown that a user-based collaborative filteringalgorithm yields the most accurate recommendations when compared to actual userbehavior. This represents a divergence from recommender systems commonly usedin e-commerce applications. The paper concludes with a discussion on the cause andsignificance of this difference and the impact of certain data-preprocessing techniqueson the results.
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Book chapters on the topic "Applications collaboratives mobiles"

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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.

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Guo, 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.

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Cruz 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.

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Shrira, 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.

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Yang, 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.

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Reverte, 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.

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Tripathi, Anand, Tanvir Ahmed, Vineet Kakani, and Shremattie Jaman. "Distributed Collaborations Using Network Mobile Agents." In Agent Systems, Mobile Agents, and Applications, 126–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-540-45347-5_11.

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Nandi, Enakshmi, Ranjan Kumar Mondal, Payel Ray, and Debabrata Sarddar. "Secured Mobile Collaborative Application in Cloud Environments." In Methodologies and Application Issues of Contemporary Computing Framework, 167–76. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2345-4_13.

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Bourimi, 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.

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Herskovic, 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.

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Conference papers on the topic "Applications collaboratives mobiles"

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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.

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Nowadays, there is little support for developers to transform single user applications to collaborative ones in the mobile domain. We present Lacomo, a new software layer to build collaborative mobile applications with accessibility, screen sharing, and application rewriting technologies that reduce costs to prototype collaboration features, thereby increasing the range of supported applications without deep application knowledge. We compare it to an ad hoc approach. Users using Lacomo performed a testing task faster, with less effort and errors at a higher completion time.
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Wang, 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.

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Gallardo-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.

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Killijian, 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.

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Worship, 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.

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Nair, 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.

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Kheiravar, Salma, Patricia Lasserre, and Robert Campbell. "A mobile application for collaborative learning." In the 14th international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2371664.2371690.

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Mtibaa, 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.

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Chen, Qian, Yunfei Chen), Ziyue Huang, and Lei Tang. "Research on Key Elements of UI Design of Image Editing System Based on CSCW." In Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001068.

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In the post-epidemic era, the application of computer-supported collaborative work (CSCW) in graphics and image software has become increasingly urgent. Collaborative image editing software allows users who are geographically distributed in different locations to view and edit the same shared image object through the network. The interaction of the CSCW system includes human-computer interaction and human-to-human interaction, and human-to-human interaction expands the time and space of interaction, and also strengthens the freedom of interaction between user groups. The research object of this article is the interactive key elements of the graphics and image software on the mobile terminal in the collaborative editing state, that is, the current operating state of the system and related information. By analyzing the interactive elements of collaborative office software and image and image software on the PC and mobile terminals by competing products, the three key elements of interactive design in cscw-based graphics and image software are extracted: editor information, selected status, and Information display location. This paper redesigned these three elements to obtain a high-fidelity model of the graphics configuration of the mobile graphics and image software during collaborative editing operations. Through the usability test and QUIS questionnaire, we verified its usability and got good user satisfaction. Finally, the design guidelines for the optimal interactive graphics configuration of the mobile graphics and image software in the collaborative editing state are obtained. The interactive design guidelines proposed in this paper can be used as a design reference for the collaborative editing image software on the mobile terminal.
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Bajaj, 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.

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Reports on the topic "Applications collaboratives mobiles"

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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.

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The article analyzes the phenomenon of augmented reality (AR) in education. AR is a new technology that complements the real world with the help of computer data. Such content is tied to specific locations or activities. Over the last few years, AR applications have become available on mobile devices. AR becomes available in the media (news, entertainment, sports). It is starting to enter other areas of life (such as e-commerce, travel, marketing). But education has the biggest impact on AR. Based on the analysis of scientific publications, the authors explored the possibilities of using augmented reality in education. They identified means of augmented reality for teaching computer science at school. Such programs and services allow students to observe the operation of computer systems when changing their parameters. Students can also modify computer hardware for augmented reality objects and visualize algorithms and data processes. The article describes the content of author training for practicing teachers. At this event, some applications for training in AR technology were considered. The possibilities of working with augmented reality objects in computer science training are singled out. It is shown that the use of augmented reality provides an opportunity to increase the realism of research; provides emotional and cognitive experience. This all contributes to engaging students in systematic learning; creates new opportunities for collaborative learning, develops new representations of real objects.
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