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Melbourne, Australia

Duckham M.,University of Melbourne | Winter S.,University of Melbourne | Robinson M.,Telstra Corporation Ltd
Journal of Location Based Services

This article addresses the problem of incorporating cognitively salient landmarks in computer-generated navigation instructions. On the basis of a review of the existing literature in the domain of navigation with landmarks, the article develops algorithms for generating routing instructions that include references to landmarks. The most basic algorithm uses a new weighting model to annotate simple routes with references to landmarks. A key novel feature of this algorithm is that it depends only on commonly available data and generic capabilities of existing web mapping environments. A suite of extensions are also proposed for improving the cognitive ergonomics of the basic landmark instructions. A case study, implemented within a national online routing system, demonstrates practicality of the approach. The article then concludes by reviewing a range of further issues for future work. © 2010 Taylor & Francis. Source

Fortino G.,University of Calabria | Pathan M.,Telstra Corporation Ltd | Di Fatta G.,University of Reading
CloudCom 2012 - Proceedings: 2012 4th IEEE International Conference on Cloud Computing Technology and Science

Spatially distributed sensor nodes can be used to monitor systems and humans conditions in a wide range of application domains. A network of body sensors in a community of people generates large amounts of contextual data that requires a scalable approach for storage and processing. Cloud computing can provide a powerful, scalable storage and processing infrastructure to perform both online and offline analysis and mining of body sensor data streams. This paper presents BodyCloud, a system architecture based on Cloud Computing for the management and monitoring of body sensor data streams. It incorporates key concepts such as scalability and flexibility of resources, sensor heterogeneity, and the dynamic deployment and management of user and community applications. © 2012 IEEE. Source

Fortino G.,University of Calabria | Di Fatta G.,University of Reading | Pathan M.,Telstra Corporation Ltd | Vasilakos A.V.,National Technical University of Athens
Wireless Networks

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed. © 2014, Springer Science+Business Media New York. Source

Fortino G.,University of Calabria | Pathan M.,Telstra Corporation Ltd
Future Generation Computer Systems

The 2014 Special Issue of Future Generation Computer Systems includes high quality papers from experts in this Body Sensor Networks (BSN)-Cloud domain. Fortino and co-researchers in their paper, 'BodyCloud: A SaaS Approach for Community Body Sensor Networks' propose a SaaS approach for community BSN that supports the development and deployment of Cloud assisted BSN applications. In 'Authentication of Lossy Data in Body-Sensor Networks for Cloud-based Healthcare Monitoring', Ali and co-workers propose, analyze, and validate a practical, lightweight robust authentication scheme suitable for health-monitoring. Ibaida and researchers in their paper 'Cloud Enabled Fractal Based ECG Compression in Wireless Body Sensor Networks', presented a new fractal based ECG lossy compression technique. In the paper 'A Platform for Secure Monitoring and Sharing of Generic Health Data in the Cloud', Thilakanathan addressed the issues of privacy and security in the domain of mobile telecare and Cloud computing. Source

Telstra Corporation Ltd | Date: 2013-12-10

A process for dimensioning a cellular telecommunications network, including, for each of one or more network elements of the network: accessing network element environment data representing a configuration and environment of the network element; accessing QoS data representing quality of service criteria for users of the network; and processing the network element environment data and the QoS data to generate network element capacity data representing combinations of loads of network services corresponding to capacities of the network element that meet the quality of service criteria.

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