Skip navigation

Mobility status as dynamic context for behaviour optimisation in selforganised networks

Mobility status as dynamic context for behaviour optimisation in selforganised networks

Anthony, R.J. and Ghassemian, M. (2009) Mobility status as dynamic context for behaviour optimisation in selforganised networks. In: Complex, Intelligent and Software Intensive Systems. The Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ, USA., pp. 878-885. ISBN 978-0-7695-3575-3 (online), 978-1-4244-3569-2 (print) (doi:10.1109/CISIS.2009.98)

Full text not available from this repository.

Abstract

A novel technique by which wireless devices such as sensor nodes can deduce their own mobility status,based on analysis of patterns in their local neighbourhood, is described.For many systems in which a neighbour table is maintained through regular status messages or other interaction, the technique incurs no additional communication overhead. The technique does not require that nodes have additional information such as absolute or relative locations, or neighbourhood node density.The work considers systems with heterogeneous time-variant mobility models, in which a subset of nodes follows a random walk mobility model, another subset follows a random waypoint mobility model (i.e.have intermittent movement), some nodes have group mobility and there is a static subset.We simulate these heterogeneous mobility systems and evaluate the performance of the Self-Detection of Mobility Status algorithm (SDMS) against a number of metrics and in a wide variety of system configurations.

Item Type: Conference Proceedings
Title of Proceedings: Complex, Intelligent and Software Intensive Systems
Additional Information: [1] This paper appears in: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, 2009. CISIS '09, 16-19 March 2009, Fukuoka.
Uncontrolled Keywords: wireless devices, sensor nodes, communication overhead, heterogeneous time-variant mobility models, random walk mobility model, waypoint mobility model, Self-Detection of Mobility Status algorithm (SDMS)
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:19
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/7912

Actions (login required)

View Item View Item