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Sensors 2016, 16(11), 1982; doi:10.3390/s16111982

Service Demand Discovery Mechanism for Mobile Social Networks

1
Information and Communication Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2
Electrical and Computer Engineering, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Dongkyun Kim, Houbing Song, Juan-Carlos Cano, Wei Wang, Waleed Ejaz and Qinghe Du
Received: 12 October 2016 / Revised: 16 November 2016 / Accepted: 17 November 2016 / Published: 23 November 2016
View Full-Text   |   Download PDF [2031 KB, uploaded 23 November 2016]   |  

Abstract

In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation. In order to maximize the utilization of limited network resources, a hybrid service demand discovery architecture, such as a Virtual Dictionary User (VDU) is proposed in this paper. Based on the historical data of movement, users can discover their relationships with others. Subsequently, according to the users activity, VDU is selected to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through the Global Active User (GAU) to support the service selection. To provide the Quality of Service (QoS), the Service Providing User (SPU) is chosen among multiple candidates. Numerical results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service demand discovery ratio by 25% under reduced overheads. View Full-Text
Keywords: mobile social networks; service demand discovery; social attribute; virtual directory user mobile social networks; service demand discovery; social attribute; virtual directory user
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MDPI and ACS Style

Wu, D.; Yan, J.; Wang, H.; Wang, R. Service Demand Discovery Mechanism for Mobile Social Networks. Sensors 2016, 16, 1982.

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