http://homepage.cs.latrobe.edu.au/sloke/papers/1-s2.0-S0167739X12001318-main.pdf

Mobile cloud computing

Nowadays, numerous journals and conferences have published articles related to context-aware systems, indicating many researchers' interest. Therefore, the goal of this paper is to review the works that were published in journals, suggest a new classification framework of context-aware systems, and explore each feature of classification framework. This paper is based on a literature review of context-aware systems from 2000 to 2007 using a keyword index and article title search. The classification framework is developed based on the architecture of context-aware systems, which consists of the following five layers: concept and research layer, network layer, middleware layer, application layer and user infrastructure layer. The articles are categorized based on the classification framework. This paper allows researchers to extract several lessons learned that are important for the implementation of context-aware systems.

Context-aware systems

The capacity to gather and timely deliver to the service level any relevant information that can characterize the service-provisioning environment, such as computing resources/capabilities, physical device location, user preferences, and time constraints, usually defined as context-awareness, is widely recognized as a core function for the development of modern ubiquitous and mobile systems. Much work has been done to enable context-awareness and to ease the diffusion of context-aware services; at the same time, several middleware solutions have been designed to transparently implement context management and provisioning in the mobile system. However, to the best of our knowledge, an in-depth analysis of the context data distribution, namely, the function in charge of distributing context data to interested entities, is still missing. Starting from the core assumption that only effective and efficient context data distribution can pave the way to the deployment of truly context-aware services, this article aims at putting together current research efforts to derive an original and holistic view of the existing literature. We present a unified architectural model and a new taxonomy for context data distribution by considering and comparing a large number of solutions. Finally, based on our analysis, we draw some of the research challenges still unsolved and identify some possible directions for future work.

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A survey of context data distribution for mobile ubiquitous systems

A system and method for protecting user privacy using social inference protection techniques is provided. The system executes a plurality of software modules which model of background knowledge associated with one or more users of the mobile computing devices; estimate information entropy of a user attribute which could include identity, location, profile information, etc.; utilize the information entropy models to predict the social inference risk; and minimize privacy risks by taking a protective action after detecting a high risk.

System and method for protecting user privacy using social inference protection techniques

Ever since the beginning of civilization, travel for various causes exists as an essential part of human life so as travel recommendations, though the early form of recommendations were the accrued experiences shared by the community Modern recommender systems evolved along with the growth of Information Technology and are contributing to all industry and service segments inclusive of travel and tourism The journey started with generic recommender engines which gave way to personalized recommender systems and further advanced to contextualized personalization with advent of artificial intelligence Current era is also witnessing a boom in social media usage and the social media big data is acting as a critical input for various analytics with no exception for recommender systems This paper details about the study conducted on the evolution of travel recommender systems, their features and current set of limitations We also discuss on the key algorithms being used for classification and recommendation processes and metrics that can be used to evaluate the performance of the algorithms and thereby the recommenders

An extensive study on the evolution of context-aware personalized travel recommender systems

The Mobile Collaboration Architecture is a middleware architecture for developing and deploying context-aware collaborative applications for mobile users. MoCA comprises client and server APIs, a set of core services for registering applications, the ability to monitor and infer the execution context of mobile devices, and an object-oriented framework for instantiating and customizing server proxies according to applications specific adaptation and context-processing requirements. MoCA facilitates the development of distributed programs that require access to individual and group context to define application-specific and dynamic adaptations. MoCAs design focuses on simplicity, extensibility, scalability, protocol heterogeneity, and application customization.

/pdf/moca-a-middleware-for-developing-collaborative-applications-npykssbuz5.pdf

MoCA: A Middleware for Developing Collaborative Applications for Mobile Users

Privacy issues related to the access of context information are becoming increasingly important as we move toward ubiquitous and mobile computing environments. In this article, we describe the design and implementation of a privacy service, called Context Privacy Service (CoPS), to control how, when and to whom disclose a users context information. Based on the results of an end-user survey and experience reported by other research groups, we identified the main service requirements and designed CoPS aiming flexibility, generality, simplicity and fine-grained privacy control. CoPS is an optional service of our context-provisioning middleware MoCA and allows users of context- and location-aware applications to define and manage their privacy policies regarding disclosure of their context information. The main features supported by CoPS are group-based access control, pessimistic and optimistic approaches for access control, hierarchical privacy rules, mixed-initiative interaction, and rule specificity analysis.

/pdf/a-privacy-service-for-context-aware-mobile-computing-57jycq2nnu.pdf

A Privacy Service for Context-aware Mobile Computing

This paper describes a middleware architecture with its location inference service (LIS), and an application for context-aware mobile collaboration which is based on this architecture. The architecture, named Mobile Collaboration Architecture - MoCA comprises client and server APIs, a set of core services for registering applications, monitoring and inferring the execution context of mobile devices, in particular their location. This architecture is suited for the development of new kinds of collaborative applications in which the context information (connectivity, location) plays a central role in defining both the group of collaborators, and the communication mode.

/pdf/support-for-context-aware-collaboration-1ej6kxfx3x.pdf

Support for Context-Aware Collaboration

Privacy related to context information is becoming an increasingly important issue due to the wide range of new applications using computational, location and personal context information. In this article, we propose a privacy service, called Context Privacy Service (CoPS), to control how, when and to whom disclose a user’s context information. In order to identify the end-user privacy concerns, we carried out a survey where we asked approximately 100 people about their willingness to use context-aware services and to disclose their context information. Based on the results of this survey and experience reported by other research groups, we identified the main service requirements and designed CoPS aiming flexibility, generality, simplicity and fine-grained privacy control. CoPS is supposed to aid the end-user to define and manage his privacy policies regarding his context information.

/pdf/design-of-a-context-privacy-service-for-mobile-collaboration-3fdkktpigb.pdf

F.N. Nascimento

Papers

MoCA: A Middleware for Developing Collaborative Applications for Mobile Users

A Privacy Service for Context-aware Mobile Computing

Support for Context-Aware Collaboration

Design of a Context Privacy Service for Mobile Collaboration