Tagging is a prevalent practice in the Web 2.0. It has been widely used to annotate different media like video. However, in personal learning environments (PLEs), tagging is supporting not only content indexing but also the self-regulated learning process consisting of different phases like planning, learning, and reflecting. In particular, in the reflection phase, tags support the organization of learning outcomes. We have researched the interrelations of learning content, learning processes, and learning phases to provide a comprehensive overview about diverse tagging behavior in PLEs like using multi-granular tagging, semantic tagging, community-based tagging, and expert–amateur tagging. We have exemplified these behaviors by the design, realization, and evaluation of a PLE for classical Chinese poetry.

Mobile flash-card learning apps proliferate since the mobile platform is ideal for learning on small pieces of information, i.e. micro-learning. Using flash cards for acquiring domain knowledge facilitates memorization by cued recall repetition. However, existing systems impose functional constraints that hinder context-aware and frictionless micro-learning. In this paper, we present our μLearn prototype which addresses the issues of fast creating and seamless consuming of flash cards for ubiquitous micro-learning. The initial results yield to be promising for the chosen approach.

Web applications have overcome traditional desktop applications especially in collaborative settings. However, the bulk of Web applications still follow the "single user on a single device" computing model. Therefore, we created the DireWolf framework for rich Web applications with distributed user interfaces (DUIs) over a federation of heterogeneous commodity devices supporting modern Web browsers such as laptops, smart phones and tablet computers. The DUIs are based on widget technology coupled with cross-platform inter-widget communication (IWC) and seamless session mobility. Inter-widget communication technologies connect the widgets and enable real-time collaborative applications as well as runtime migration in our framework. We show that the DireWolf framework facilitates the use case of DUI-enabled semantic video annotation. For a single user it provides more flexible control over different parts of an application by enabling the simultaneous use of smart phones, tablets and computers. We conducted a technical evaluation and two user studies to validate the DireWolf approach. The work presented opens the way for creating distributed Web applications which can access device specific functionalities such as multi-touch, text input, etc. in a federated and usable manner. In this paper, we also sketch our ongoing work to integrate the WebRTC API into DireWolf, where we see opportunities for potential adoption of DUI Web applications by the majority of Web users.

Mobile multimedia services are in high demand, but their development comes at high costs. The emergent computing paradigm cloud computing has great potential to embrace these issues. In fact, we are at the early stage of the coalescence of cloud computing, mobile multimedia and the Web. Motivated by the tremendous success story of the Web based on its simplicity principles, we argue for a comprehensive review on current practices of web and mobile multimedia cloud computing techniques for avoiding frictions. We draw on experience from the development of advanced collaborative multimedia web applications utilizing multimedia metadata standards like MPEG-7 and real-time communication protocols like XMPP. We propose our i5CLoud, a hybrid cloud architecture, which serves as a substrate for scalable and fast time-to-market mobile multimedia services. This paper demonstrates the applicability of emerging cloud computing concepts for mobile multimedia.

Web applications have overcome traditional desktop applications especially in collaborative settings. However, the bulk of Web applications still follow the "single user on a single device" computing model. Therefore, we created the DireWolf framework for rich Web applications with distributed user interfaces (DUIs) over a federation of heterogeneous commodity devices supporting modern Web browsers such as laptops, smart phones and tablet computers. The DUIs are based on widget technology coupled with cross-platform inter-widget communication and seamless session mobility. Inter-widget communication technologies connect the widgets and enable real-time collaborative applications as well as runtime migration in our framework. We show that the DireWolf framework facilitates the use case of collaborative semantic video annotation. For a single user it provides more flexible control over different parts of an application by enabling the simultaneous use of smart phones, tablets and computers. The work presented opens the way for creating distributed Web applications which can access device specific functionalities such as multi-touch, text input, etc. in a federated and usable manner.

Advanced mobile applications that enable new ways of interaction with digital objects become increasingly important for on-site professional communities. These new ways of interaction, e.g. in Mobile Augmented Reality (MAR) via position and 3D movement, are real needs for fieldwork domains such as cultural heritage management and the construction industry. In addition, on-site professional communities generate shared knowledge bases with multimedia content and semantic annotations through collaboration. However, current MAR applications lack real-time collaboration features. In practice, blending multimedia semantics in mobile real-time collaboration is challenging due to the limitations of mobile devices, the lack of mature dedicated designed communication infrastructures and the constraints of the remote environments. This paper presents a mobile real-time collaboration system for semantic multimedia annotations with augmented reality features. We use XMPP as a real-time protocol for the secure, scalable and interoperable processing of XML-based semantic multimedia metadata described in MPEG-7. Our prototype was evaluated in the digital documentation of historical sites for cultural heritage management. The evaluation results indicate potential for increased productivity and enhanced mutual awareness in on-site professional communities.

Despite the popularity of mobile video sharing, mobile user experience (UX) is not comparable with traditional TV or desktop video productions. The issue of poor UX in mobile video sharing can be associated with the high development cost, since the creation and utilization of a multimedia processing and distribution infrastructure is a non-trivial task for small groups of developers. In this paper, we present our solution comprised of mobile video processing services based on standard libraries which augment the raw video streams. Our services utilize the cloud computing paradigm for fast and intelligent processing in near-real time. Video streams are split in chunks and then fed to the ``resource-unlimited'' distributed/cloud infrastructure which accelerate the processing phase. Application developers have the possibility to apply arbitrary computer vision algorithms on the video stream thus improving the quality of user experience depending on the application requirements. We providing navigation cues and content-based zooming of raw video streams. We evaluated the proposed solution from two perspectives - distributed chunk-based processing in the cloud and a user study by means of mental workload. Running experiments in mobile video applications demonstrate that our proposed techniques improve mobile user experience significantly.

Mobile applications nowadays are developed either for a local (native) or for a client-server execution. However, applications in the future will be developed with cloud in mind, i.e. act as native applications, but do the heavy processing and storage in the cloud, deliver only needed parts and data at runtime and able to run offline. In order to better understand how to facilitate the building of mobile cloud-based applications, we have surveyed existing work in mobile computing through the prism of cloud computing principles. We provide an overview of the results from this survey, in particular, models of mobile cloud applications. We also highlight research challenges in the area of mobile cloud computing.

Despite the rapid advances in mobile technology, many constraints still prohibit smartphones to run resource-demanding applications in pervasive environments. Emerging cloud computing opens an access to unlimited resources for mobile devices. However, the combination of both technologies to deliver sound mobile cloud applications and services raises new challenges and requirements. Based on a scenario-based requirement analysis and a comprehensive study on existing work for augmenting mobile devices, we propose a XMPP-based mobile cloud computing architecture employing module partitioning and adaptive offloading to nearby computing infrastructure. Research has also been done in the underlying offloading mechanism based on context-aware cost model. Further problems related to this approach are discussed as well, including selection of most optimal offloading plan, application partitioning and issues with XMPP on mobile systems.

The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS) middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also use remote computing resources transparently. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve costly computations, can benefit from offloading with around 95% energy savings and significant performance gains compared to local execution only.

The plethora of talks and presentations taking place at academic conferences makes it difficult, especially for young researchers to attend the right talks or discuss with participants and potential collaborators with similar interests. Participants may not have a priori knowledge that allows them to select the right talks or informal interactions with other participants. In this paper we present the context-aware mobile recommendation services (CAMRS) based on the current context (whereabouts at the venue, popularity and activities of talks and presentations) sensed at the conference venue. Additionally, we augment the current context with the academic community context of conference participants which is inferred by using social network analysis and link prediction on large-scale co-authorship and citation networks of participants. By combining the dynamic and social context of participants, we are able to recommend talks and people that may be interesting to a particular participant. We evaluated CAMRS using data from two large digital libraries - the DBLP and CiteSeerX, and participants from two conferences - ICWL 2010 and EC-TEL 2011. The result shows that the new approach can recommend novel talks and helps participants in establishing new connections at conference venue.

Mobile Augmented Reality (MAR) enables overlays of semantically-enriched multimedia on video streams of smart phone cameras. These new ways to interact with digital objects via position and 3D movement can be helpful for on-site professional communities. However, current MAR applications lack real-time collaborative features. Moreover, blending multimedia semantics in collaborative MAR is still challenging. In this paper, we present a mobile real-time semantic multimedia-based collaborative system with augmented reality features based on open standards like XMPP and MPEG-7. The prototype system is evaluated in the digital documentation of historical sites for cultural heritage management. The evaluation results indicate increased productivity and awareness within on-site professional communities.

The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS) middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also reach transparently remote computing resources. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve complicated algorithms and large computations, can benefit from offloading with around 95% energy savings and significant performance gains compared to local execution only.

The Web is a tremendous success story. Nowadays, even users without knowledge about web standards and protocols can create appealing web sites with lots of multimedia materials. Professional organizations and communities turn their businesses and collaboration needs into web applications. When it comes to mobile multimedia it is a different story. Highly specialized applications using the competitive advantage of newest device technologies programmed by specialists are dominating the scene. We argue that we need a comprehensive view on current practices of web and mobile multimedia development in order to create the next generation of mobile multimedia web applications. We draw on our experiences with the development of advanced multimedia web applications utilizing MPEG-7 for professional communities and the early development of respective mobile versions. Our approach uses mobile cloud computing and new standards and protocols like HTML5 and XMPP.

Cloud computing is an emerging concept combining many fields of computing. The foundation of cloud computing is the delivery of services, software and processing capacity over the Internet, reducing cost, increasing storage, automating systems, decoupling of service delivery from underlying technology, and providing flexibility and mobility of information. However, the actual realization of these benefits is far from being achieved for mobile applications and open many new research questions. In order to better understand how to facilitate the building of mobile cloud-based applications, we have surveyed existing work in mobile computing through the prism of cloud computing principles. We give a definition of mobile cloud coputing and provide an overview of the results from this review, in particular, models of mobile cloud applications. We also highlight research challenges in the area of mobile cloud computing. We conclude with recommendations for how this better understanding of mobile cloud computing can help building more powerful mobile applications.

Micro-learning refers to short-term learning activities on small learning units. In our contemporary mobile/web society, micro-learning pertains to small pieces of knowledge based on web resources. Micro-learning falls into the group of informal learning processes. The existing web and mobile services have great potential to support informal learning processes, especially micro-learning. However, several specific aspects need to be considered. In this paper, we propose a micro-learning model based on three technical aspects: (i) ubiquitous learning resource acquisition; (ii) cloud-based data management; and (iii) tag-based regulation of learning processes and content. A micro-learning prototype consisting of an Android application and a web browser add-on is evaluated in the use case of bilingual vocabulary learning. The initial prototype evaluation study shows promising results in enhanced flexibility in personal learning content creation and increased efficiency in filling knowledge gaps.