Intelligent and context-aware mobile services require usersand applications to share information and utilize services from remotelocations. Thus, context information from the users must be structuredand be accessible to applications running in end-devices. In response tothis challenge, we present a shared object-oriented meta model for a persistentagent environment. The approach enables agents to be contextawarefacilitating the creation of ambient intelligence demonstrated bya sensor-based scenario. The agents are context-aware as agent actionsare based upon sensor information, social information, and the behaviorof co-agents.
This article analyzes the challenges of supportingcontinual changes of context information in Internetof-Things applications. These applications require aconstant flow of continuously changing information fromsensor based sources in order to ensure a high quality-ofexperience.However, an uncontrolled flow between sourcesand sinks on a global scale wastes resources, such ascomputational power, communication bandwidth, andbattery time. In response to these challenges we presenta general approach which focuses on four layers wherewe provide a proposed solution to each layer. We haverealized the general model into a proof-of-concept implementationrunning on devices with limited resources,where we can moderate the information exchange basedon relevance and sought after quality-of-experience bythe applications. In conclusion, we evaluate our solutionand present a summary of our experiences regardingthe impact of continuously changing information on theInternet-of-Things.
Context-aware applications require local access to current and relevant views of context information derived from global sensors. Existing approaches provide only limited support, because they either rely on a network broker service precluding open-ended searches, or they adopt a presence model which has scalability issues. To this end, we propose a fully distributed architecture employing context user-agents co-located with data-mining agents. These agents create and maintain local schemas using ranking of global context information based on context proximity. Continually evolving context information thus provides applications with current and relevant context views derived from global sensors. Furthermore, we present an evaluation model for assessing the effort required to present local applications with current and relevant contextual views. We show in a comparison with earlier work that the approach achieves the provisioning of evolving context information to applications within predictable time bounds, circumventing earlier limitations.
Existing sensor-assisted mHealth applications wouldbenefit from large-scale sharing of sensor information in realtime.Existing communication solutions are however limited inthis respect, because of centralized application-level communication.In response to this, we presents a distributed communicationsolution for mHealth applications which circumvents these limitations.Our Internet-of-Things architecture enables mHealth applicationsto utilize information from sensors and wireless sensornetworks via a peer-to-peer overlay, where sensor information isorganized in an information model which is stored in the overlayitself. We present a proof-of-concept application and evaluationresults regarding the architecture’s real-time capabilities. Theresults indicate that a fully distributed architecture can supportreal-time sensing in mHealth applications and the support isavailable as an open source platform, MediaSense. Current workis focused on evaluating scalability in very large scale scenariosusing field trials.
Intelligent artifacts are real-world objects enhancedwith capabilities in order to display relevant behavior in varioustypes of context-aware applications, such as in mHealth,commerce, or pervasive games. This can be achieved by attachingsensors and store associated information on the Internet.Interaction with such artifacts requires secure communication,to protect personal and private information. This mandatesresearch in how to safeguard interactions via heterogeneousmeans of communication involving interconnected local and nonlocalartifacts. In response to these challenges, this paper presentskey schemes to secure interaction via heterogeneous means ofcommunication. In conclusion, the architecture can securelyauthenticate an intelligent artifact as well as securely exchangesensor information with other authenticated artifacts attached inan overlay. Our proof-of-concept application demonstrated in anInternet-of-Things platform validates the approach.
Context-aware applications and services require ubiquitous access to context information of users. The limited scalability of centralized servers used in the provisioning of context information mandates the search for scalable peer-to-peer protocols. Furthermore, unnecessary signaling must be avoided in large-scale context networks, when location-based services only require nodes in a certain area with which to communicate context. To this end, we propose a lightweight model for composing and maintaining unstructured location-scoped networks of peer-to-peer nodes, which gossips in order to ensure quality of service for each user. The model is implemented in a prototype application running in a mobile environment, which is evaluated with respect to real-time properties. This model can also be extended to include more context dimensions, other than location.
The increasing ubiquity of context aware services and systems has been primarily underpinned by the use of centralised servers employing protocols that do no scale well for real time distribution and acquisition of neither sensor data nor dependent services.Any shift from this generic sensor framework mandated a new thinking where sensor data was capable of being propagated in real time using protocols and data models which serve to reduce unnecessary communication overhead. DCXP is proposed as an alternative architecture for the real time distribution of context information to ubiquitous mobile services.As a P2P based distributed protocol, it inherently poses the challenge of user anonymity across the system. In this paper we briefly present DCXP along with further work to enable the anonymised dissemination of sensor information within the architecture.Such a solution would have a negligible impact on the overall scalability and performance of DCXP.
Next generation context-aware mobile applicationswill require a continuous update of relevant information about auser’s surroundings, in order to create low latency notificationsand high quality of experience. Existing mobile devices alreadycontain a large number of built in sensors which are capableof producing huge amounts of sensor data, exceeding boththe capacity of the local storage and the Internet connection.Therefore, we will in this paper study the limits when sharingcontextual information from mobile devices, as well as finding theimpact of this information overload for the Internet-of-Things.Furthermore, we present an evaluation model for assessing theeffort required to present applications with relevant contextinformation. In conclusion, the model shows that one feasiblesolution for the future Internet-of-Things is a peer-to-peer basedsolution which can control the flow of information without anycentralized authority, to circumvent earlier limitations.
mHealth data provision focuses on providing health services to patients via mobile devices and presence technologies. It has great influence to the healthcare business today, especially in the developing countries. However, the mHealth presence might be sensitive; and it brings potential privacy issues. For controlling what presence information can be given to which watcher, and when in mHealth presence service, XML Configuration Access Protocol (XCAP) is introduced. Nevertheless, it is not enough if only XCAP is applied. It just controls the direct privacy leakage; indirect flow might still leak the privacy information. Thus, presence authorization policy and privacy filter, which are components of XCAP, are improved based on k-anonymity for stopping indirect privacy leakage.
Research in Internet-of-Things infrastructures hasso far mainly been focused on connecting sensors and actuatorsto the Internet, while associating these devices to applicationsvia web services. This has contributed to making the technologyaccessible in areas such as smart-grid, transport, health, etc.These early successes have hidden the lack of support forsensor-based applications to share information and limitationsin support for applications to access sensors and actuatorsglobally. We address these limitations in an novel open-sourceplatform, MediaSense. MediaSense offers scalable, seamless,real-time access to global sensors and actuators via hetero-geneous network infrastructure. This paper presents a setof requirements for Internet-of-Things applications support,an overview of our architecture, and application prototypescreated in order to verify the approach in a test bed withusers connected from heterogeneous networks.
Users require applications and services to be available everywhere, enabling users to focus on what is important to them. Therefore, context information from users (e.g., spatial data, preferences, available connectivity and devices, etc.) needs to be accessible to systems that deliver services via a heterogeneous infrastructure. We present a novel approach to support ubiquitous sensing and availability of context to services and applications. This approach offers a scalable, distributed storage of context derived from sensor networks wirelessly attached to mobile phones and other devices. The support handles frequent updates of sensor information and is interoperable with presence services in 3G mobile systems, thus enabling ubiquitous sensing applications. We demonstrate these concepts and the principle operation in a sample ubiquitous mobile awareness service. The importance of this contribution, in comparison to earlier work, lies in the availability of real-time ubiquitous sensing to both applications on the Internet as well as applications in mobile systems.
This paper describes research issues and work-in-progress concerning ubiquitous sensing. We present scenarios where the current approaches are deficient in addressing the needs for ubiquitous sensing in services and applications on the Future Internet, involving the massive sharing of information from sensors via heterogeneous networks. We propose an information-centric architecture for real-time ubiquitous sensing which capitalizes on the proposed locator/identifier split, thus extending the Network of Information (NetInf) approach. From this we identify the challenges for which we present work-in-progress within the framework of the EU-funded MediaSense project. Firstly, we integrate sensors as addressable objects, exposed by means of sensor gateways and relocatable abstract interfaces. Sensor information is thus made available to applications solely based on identity. Secondly, sensor information is made available in a distributed data model towards searching and browsing. Finally, we evaluate the effectiveness of the architecture in proof-of-concept applications for intelligent commuting, environmental monitoring and seamless media transfer, utilizing two different sensor platforms.