Characterization of Inter-Body Interference in Context Aware Body Area Networking (CABAN)

The characterization and understanding of body to body communication channels is a pivotal step in the development of emerging wireless applications such as ad-hoc personnel localisation and context aware body area networks (CABAN). The latter is a recent innovation where the inherent mobility of body area networks can be used to improve the coexistence of multiple co-located BAN users. Rather than simply accepting reductions in communication performance, sensed changes in inter-network co-channel interference levels may facilitate intelligent inter-networking; for example merging or splitting with other BANs that remain in the same domain. This paper investigates the inter-body interference using controlled measurements of the full mesh interconnectivity between two ambulatory BANs operating in the same environment at 2.45 GHz. Each of the twelve network nodes reported received signal strength to allow for the creation of carrier to interference ratio time series with an overall entire mesh sampling period of 54 ms. The results indicate that even with two mobile networks, it is possible to identify the onset of co-channel interference as the BAN users move towards each other and, similarly, the transition to more favourable physical layer channel conditions as they move apart. © 2011 IEEE.

Context-Aware Body Area Networks (CABAN) for interactive smart environments:Interference characterization

Body Area Networks are unique in that the large-scale mobility of users allows the network itself to travel across a diverse range of operating domains or even to enter new and unknown environments. This network mobility is unlike node mobility in that sensed changes in inter-network interference level may be used to identify opportunities for intelligent inter-networking, for example, by merging or splitting from other networks, thus providing an extra degree of freedom. This paper introduces the concept of context-aware bodynets for interactive environments using inter-network interference sensing. New ideas are explored at both the physical and link layers with an investigation based on a 'smart' office environment. A series of carefully controlled measurements of the mesh interconnectivity both within and between an ambulatory body area network and a stationary desk-based network were performed using 2.45 GHz nodes. Received signal strength and carrier to interference ratio time series for selected node to node links are presented. The results provide an insight into the potential interference between the mobile and static networks and highlight the possibility for automatic identification of network merging and splitting opportunities. © 2010 ACM.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

A Framework for Context-Driven End-to-End QoS Control in Converged Next Generation Networks”

This paper presents a framework for context-driven policy-based QoS control and end-to-end resource management in converged next generation networks. The Converged Networks QoS Framework (CNQF) is being developed within the IU-ATC project, and comprises distributed functional entities whose instances co-ordinate the converged network infrastructure to facilitate scalable and efficient end-to-end QoS management. The CNQF design leverages aspects of TISPAN, IETF and 3GPP policy-based management architectures whilst also introducing important innovative extensions to support context-aware QoS control in converged networks. The framework architecture is presented and its functionalities and operation in specific application scenarios are described.

Measurement-based Policy-driven QoS Management in Converged Next Generation Networks

Policy-based management is considered an effective approach to address the challenges of resource management in large complex networks. Within the IU-ATC QoS Frameworks project, a policy-based network management framework, CNQF (Converged Networks QoS Framework) is being developed aimed at providing context-aware, end-to-end QoS control and resource management in converged next generation networks. CNQF is designed to provide homogeneous, transparent QoS control over heterogeneous access technologies by means of distributed functional entities that co-ordinate the resources of the transport network through policy-driven decisions. In this paper, we present a measurement-based evaluation of policy-driven QoS management based on CNQF architecture, with real traffic flows on an experimental testbed. A Java based implementation of the CNQF Resource Management Subsystem is deployed on the testbed and results of the experiments validate the framework operation for policy-based QoS management of real traffic flows.

Contextual anomaly detection in crowded surveillance scenes

This work addresses the problem of detecting human behavioural anomalies in crowded surveillance environments. We focus in particular on the problem of detecting subtle anomalies in a behaviourally heterogeneous surveillance scene. To reach this goal we implement a novel unsupervised context-aware process. We propose and evaluate a method of utilising social context and scene context to improve behaviour analysis. We find that in a crowded scene the application of Mutual Information based social context permits the ability to prevent self-justifying groups and propagate anomalies in a social network, granting a greater anomaly detection capability. Scene context uniformly improves the detection of anomalies in both datasets. The strength of our contextual features is demonstrated by the detection of subtly abnormal behaviours, which otherwise remain indistinguishable from normal behaviour.

Using location-aware technology for learning Geography in a real digital space outside the classroom

The use of new mobile technologies is still in its infancy in many secondary schools and there is limited evidence of the educational and pedagogical benefits on pupils’ learning in the formal school context. This qualitative study focuses on the use of handheld devices to teach a topic in geography to an examination class. Action research combined with pupil observations and focus group interviews are used to capture the pupils’ experiences of using mediascapes. Activity Theory is used as a lens to structure the analysis of the data and to report on the cognitive and affective impact of m-learning on pupils’ academic performance in the topic. Increased attainment and the development of wider skills for lifelong learning were identified in the study. The adaptability of the majority of pupils to the technology resulted in increased levels of willingness to learn in this novel context.

A Capabilities-Aware Framework for Using Computational Accelerators in Data-Intensive Computing

Multicore computational accelerators such as GPUs are now commodity components for highperformance computing at scale. While such accelerators have been studied in some detail as stand-alone computational engines, their integration in large-scale distributed systems raises new challenges and trade-offs. In this paper, we present an exploration of resource management alternatives for building asymmetric accelerator-based distributed systems. We present these alternatives in the context of a capabilities-aware framework for data-intensive computing, which uses an enhanced implementation of the MapReduce programming model for accelerator-based clusters, compared to the state of the art. The framework can transparently utilize heterogeneous accelerators for deriving high performance with low programming effort. Our work is the first to compare heterogeneous types of accelerators, GPUs and a Cell processors, in the same environment and the first to explore the trade-offs between compute-efficient and control-efficient accelerators on data-intensive systems. Our investigation shows that our framework scales well with the number of different compute nodes. Furthermore, it runs simultaneously on two different types of accelerators, successfully adapts to the resource capabilities, and performs 26.9% better on average than a static execution approach.

Making geography mobile: using location aware technology to improve student performance in physical geography

With the increased availability of new technologies, geography educators are revisiting their pedagogical approaches to teaching and calling for opportunities to share local and international practices which will enhance the learning experience and improve students’ performance. This paper reports on the use of handheld mobile devices, fitted with GPS, by secondary (high) school pupils in geography. Two location-aware activities were completed over one academic year (one per semester) and pre-test and post-test scores for both topics revealed a statistically significant increase in pupils’ performance as measured by the standard national assessments. A learner centred educational approach was adopted with the first mobile learning activity being created by the teacher as an exemplar of effective mobile learning design. Pupils built on their experiences of using mobile learning when they were required to created their own location aware learning task for peer use. An analysis of the qualitative data from the pupils’ journals, group diaries and focus group interviews revealed the five pillars of learner centred education are addressed when using location aware technologies and the use of handheld mobile devices offered greater flexibility and autonomy to the pupils thus altering the level of power and control away from the teacher. Due to the relatively small number of participants in the study, the results are more informative than generalisable however in light of the growing interest in geo-spatial technologies in geography education, this paper offers encouragement and insight into the use of location aware technology in a compulsory school context

Laugh-aware virtual agent and its impact on user amusement

In this paper we present a complete interactive system en- abled to detect human laughs and respond appropriately, by integrating the information of the human behavior and the context. Furthermore, the impact of our autonomous laughter-aware agent on the humor experience of the user and interaction between user and agent is evaluated by sub- jective and objective means. Preliminary results show that the laughter-aware agent increases the humor experience (i.e., felt amusement of the user and the funniness rating of the film clip), and creates the notion of a shared social experience, indicating that the agent is useful to elicit posi- tive humor-related affect and emotional contagion.