1 research outputs found
Service Discovery and Trust in Mobile Social Network in Proximity
Service-oriented Mobile Social Network in Proximity (MSNP) lets participants
establish new social interactions with strangers in public proximity using
heterogeneous platforms and devices. Such characteristic faces challenges in
discovery latency and trustworthiness. In a public service-oriented MSNP
environment, which consists of a large number of participants, a content
requester who searches for a particular service provided by other MSNP
participants will need to retrieve and process a large number of Service
Description Metadata (SDM) files, associated semantic metadata files and
identifying the trustworthiness of the content providers. Performing such tasks
on a resource constraint mobile device can be time consuming, and the overall
discovery performance will be affected and will result in high latency. This
paper analyses the service discovery models of MSNP and presents corresponding
solutions to improve the service discovery performance of MSNP. We firstly
present and analyse the basic service discovery models of service-oriented
MSNP. To follow up, we apply a context-aware user preference prediction scheme
to enhance the speed of the semantic service discovery process. Later, we
address the trustworthiness issue in MSNP and propose a scheme to reduce the
latency of the trustworthy service discovery for MSNP. The proposed scheme has
been tested and evaluated on MSNP application prototype operating on real
mobile devices and MSNP simulation environments.Comment: 40 pages, 14 figures, 3 table