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Adaptive service discovery on service-oriented and spontaneous sensor systems

Liu, Lu; Xu, Jie; Antonopoulos, Nikolaos; Li, Jianxin; Wu, Kaigu

Authors

Lu Liu

Jie Xu

Profile image of Nick Antonopoulos

Prof Nick Antonopoulos N.Antonopoulos@napier.ac.uk
Deputy Vice Chancellor and Vice Principal of Research & Innovation

Jianxin Li

Kaigu Wu



Abstract

Natural and man-made disasters can significantly impact both people and environments. Enhanced effect can be achieved through dynamic networking of people, systems and procedures and seamless integration of them to fulfil mission objectives with service-oriented sensor systems. However, the benefits of integration of services will not be realised unless we have a dependable method to discover all required services in dynamic environments. In this paper, we propose an Adaptive and Efficient Peer-to-peer Search (AEPS) approach for dependable service integration on service-oriented architecture based on a number of social behaviour patterns. In the AEPS network, the networked nodes can autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly discover and self-configure any services available on the disaster area and deliver a real-time capability by self-organising themselves in spontaneous groups to provide higher flexibility and adaptability for disaster monitoring and relief.

Citation

Liu, L., Xu, J., Antonopoulos, N., Li, J., & Wu, K. (2012). Adaptive service discovery on service-oriented and spontaneous sensor systems. Adhoc and Sensor Wireless Networks, 14(1-2), 107-132

Journal Article Type Article
Publication Date Mar 6, 2012
Deposit Date Feb 13, 2019
Journal Adhoc & Sensor Wireless Networks
Print ISSN 1551-9899
Electronic ISSN 1552-0633
Publisher Old City Publishing
Peer Reviewed Peer Reviewed
Volume 14
Issue 1-2
Pages 107-132
Keywords Service-oriented architecture, spontaneous networks, self-organization, self-configuration, sensor systems, social patterns
Public URL http://researchrepository.napier.ac.uk/Output/1557185