Dejan Kovachev

Adaptive Computation Offloading from Mobile Devices into the Cloud

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.

Mobile Community Cloud Computing: Emerges and Evolves

With the advent of mobile smart phones, new types of virtual communities arrived, i.e. mobile communities. Mobile communities, with respect to their IT needs, introduce new requirements compared to traditional online web communities. On the other hand, cloud computing is emerging as computing concept that promises provision of computational resources on demand and abstraction of technical details from the clients. We propose Mobile Community Cloud Platform (MCCP) as a cloud computing system that can leverage the full potential of mobile community growth. An analysis of the core requirements of common mobile communities is provided before we present the design of our cloud computing architecture that supports building and evolving of mobile communities.

Framework for Computation Offloading in Mobile Cloud Computing

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.

Learn-as-you-go: new ways of cloud-based micro-learning for the mobile web

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.

Building mobile multimedia services: a hybrid cloud computing approach

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.

Beyond the client-server architectures: A survey of mobile cloud techniques

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.

Enhancing Academic Event Participation with Context-aware and Social Recommendations

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.

Augmenting Pervasive Environments with an XMPP-Based Mobile Cloud Middleware

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.

Mobile Multimedia Management for Community-Aware Storytelling

Storytelling is a natural and effective approach to human communication. The enrichment of stories using multimedia technologies has been established in knowledge sharing for professional communities since long ago. However, mobile multimedia production and consumption for storytelling raises several issues for mobile data management. We start with a requirements analysis for various application scenarios ranging from business to common life with mobile multimedia storytelling. A mobile multimedia data management model is proposed based on the presented scenarios. A test bed for the measurement of mobile multimedia community information system success is briefly described for the evaluation of our approach.

Mobile Real-Time Collaboration for Semantic Multimedia

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.