A socioecological model for advanced service discovery in machine-to-machine communication networks
Abstract
The new development of embedded systems has the potential to revolutionize our lives and will have a significant impact on future Internet of Thing (IoT) systems if required services can be automatically discovered and accessed at runtime in Machine-to-Machine (M2M) communication networks. It is a crucial task for devices to perform timely service discovery in a dynamic environment of IoTs. In this article, we propose a Socioecological Service Discovery (SESD) model for advanced service discovery in M2M communication networks. In the SESD network, each device can perform advanced service search to dynamically resolve complex enquires and autonomously support and co-operate with each other to quickly discover and self-configure any services available in M2M communication networks to deliver a real-time capability. The proposed model has been systematically evaluated and simulated in a dynamic M2M environment. The experiment results show that SESD can self-adapt and self-organize themselves in real time to generate higher flexibility and adaptability and achieve a better performance than the existing methods in terms of the number of discovered service and a better efficiency in terms of the number of discovered services per message.Citation
Liu, L. et al, (2016) 'A Socioecological Model for Advanced Service Discovery in Machine-to-Machine Communication Networks' , ACM Transactions on Embedded Computing Systems, 15 (2):1. DOI: 10.1145/2811264Publisher
Association for Computing MachineryJournal
ACM Transactions on Embedded Computing SystemsDOI
10.1145/2811264Additional Links
http://dl.acm.org/citation.cfm?doid=2888407.2811264Type
ArticleLanguage
enISSN
15399087ae974a485f413a2113503eed53cd6c53
10.1145/2811264
Scopus Count
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Except where otherwise noted, this item's license is described as Archived with thanks to ACM Transactions on Embedded Computing Systems