Jamie Walters

Distributed context support for ubiquitous mobile awareness services

Context-aware applications and services require ubiquitous access to context information about the users or sensors such as preferences, spatial & environmental data, available connectivity, and device capabilities. Systems for the brokering or the provisioning of context data via wireless networks do so with centralized servers or by employing protocols that do not scale well with real-time distribution capabilities. In other cases, such as the extending of presence systems, the data models are limited in expressive capabilities and consequently incur unnecessary signaling overhead. This paper presents a distributed protocol, the Distributed Context eXchange Protocol (DCXP), and an architecture for the real-time distribution of context information to ubiquitous mobile services: We present the architecture and its principle operation in a sample ubiquitous mobile awareness service. Preliminary results indicate that our approach scales well for the ubiquitous provision of context data in real-time to clients on the Internet via 3G wireless systems. Performed measurements show that DCXP can reduce the time to process context data with a factor of 20 compared to similar approaches.

The MediaSense Framework

Mobile telecommunication is evolving rapidly. People no longer only communicate with each other regardless of time and place, but also share other information that is important for tasks with which they are involved. In response to this growing trend the MediaSense framework addresses the intelligent delivery of any information to any host, anywhere, based on context-aware information regarding personal preferences, presence information, and sensor values. This includes another challenge to achieve seamless delivery, especially of multimedia content, and multimodal services via heterogeneous connections.

Location-Based Ubiquitous Context Exchange in Mobile Environments

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.

An Object-Oriented Model in Support of Context-Aware Mobile Applications

Intelligent and context-aware mobile services require users and applications to share information and utilize services from remote locations. Thus, context information from the users must be structured and be accessible to applications running in end-devices. In response to this challenge, we present a shared object-oriented meta model for a persistent agent environment. The approach enables agents to be context-aware facilitating the creation of ambient intelligence demonstrated by a sensor-based scenario. The agents are context-aware as agent actions are based upon sensor information, social information, and the behavior of co-agents.

The Updated MediaSense Framework

Mobile telecommunication is evolving rapidly. People no longer only communicate with each other regardless of time and place, but also share other information that is important for the tasks with which they are involved. In response to this growing trend, the Media Sense framework addresses the intelligent delivery of any information to any host, anywhere, based on context-aware information regarding personal preferences, presence information, and sensor values. The focus of this paper is the overall framework, the handling of user profiles, management of context information, real-time distribution and proof of concepts.

A Distributed Framework for Organizing an Internet of Things

Applications on a future Internet of Things require the provisioning of current, relevant and accurate context information to end-points. Context information existing globally require organization into object-oriented models available locally in APIs as current, relevant and accurate views. Moreover, such applications require support for the highly dynamic interactions influencing continual changes in global context information. Existing approaches, such as the web services, are unable to provide this support partly due to the presupposed existence of a network service brokering context information, relying on DNS; or adopting a presence model for context which does not adequately scale. To this end, we propose a distributed framework for the interconnection of end-points and co-located agent entities, whereby agents are provided with local views of a relevant subset of global context information. We show how to achieve relevant local current views of global context information via ranking in an object-oriented context model. The distributed approach realizes the provisioning of context information in real-time, i.e., with predictable time bounds. Finally, we demonstrate the feasibility of the approach in a prototype based on P-Grid.

Scenarios, Research Issues, and Architecture for Ubiquitous Sensing

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.

Evolving Presentity-Based Context Schemas by Estimating Context Proximity

The definition of what constitutes context proximity has remained largely unexplored but accepted as being a fundamental issue towards realising an architecture of connected things. Existing solutions aimed at enabling context awareness are often undermined by their dependencies on centralized architectures limited with respect to their scalability. Our previous work proposed the use of the so called Context Schema; an encapsulated representation of the information points constituting the context of a presentity. Building such a schema requires support for determining set members limited by some metric; a proximity metric. In this paper, we propose an algorithm for estimating the context proximity among presentities, enabling complete schemata of entities relevant to, and expressing the current context of a presentity. Secondly we propose an extension of a gossiping algorithm to optimize the ability create schemata as one traverses a vast and dynamic connected things infrastructure.

Distributed Context Models in Support of Ubiquitous Mobile Awareness Services

Real-time context aware applications require dynamic support reflecting the continual changes in context. Architectures that distribute and utilize the supporting sensor information within the constraints of publish-subscribe systems provide sensor information in primitive forms requiring extensive application-level transformations limiting the dynamic addition and removal of sources. Elevating sensors to first class objects in a meta-model addresses these issues by applying ontological dimensions in direct support of context. This paper proposes an extension of such a model into a distributed architecture co-located with context user agents. This arrangement provides clients with a model schema which is continually evolving over sensor domains. In addition, the evolving model schema represents an accurate temporal view of a userâĂŹs context with respect to the available sensors and actuators.

Dissemination of Anonymised Context Information by Extending the DCXP Framework

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.