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Open AccessArticle

Data Collection for Mobile Group Consumption: An Asynchronous Distributed Approach

International School of Software, Wuhan University, Wuhan 430079, China
State Key Lab. for Novel Software Technology, Nanjing University, Nanjing 210046, China
Economics and Management School, Wuhan University, Wuhan 430079, China
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in “An Asynchronous Distributed Data Collection Approach for Mobile Group Consumption”. In Proceedings of the International Conference on Identification, Information & Knowledge in the Internet of Things (IIKI), Beijing, China, 22–23 October 2015.
Academic Editors: Yunchuan Sun, Antonio Jara and Shengling Wang
Sensors 2016, 16(4), 482;
Received: 29 January 2016 / Revised: 21 March 2016 / Accepted: 23 March 2016 / Published: 6 April 2016
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
Mobile group consumption refers to consumption by a group of people, such as a couple, a family, colleagues and friends, based on mobile communications. It differs from consumption only involving individuals, because of the complex relations among group members. Existing data collection systems for mobile group consumption are centralized, which has the disadvantages of being a performance bottleneck, having single-point failure and increasing business and security risks. Moreover, these data collection systems are based on a synchronized clock, which is often unrealistic because of hardware constraints, privacy concerns or synchronization cost. In this paper, we propose the first asynchronous distributed approach to collecting data generated by mobile group consumption. We formally built a system model thereof based on asynchronous distributed communication. We then designed a simulation system for the model for which we propose a three-layer solution framework. After that, we describe how to detect the causality relation of two/three gathering events that happened in the system based on the collected data. Various definitions of causality relations based on asynchronous distributed communication are supported. Extensive simulation results show that the proposed approach is effective for data collection relating to mobile group consumption. View Full-Text
Keywords: asynchronous; distributed; data collection; mobile group consumption asynchronous; distributed; data collection; mobile group consumption
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Zhu, W.; Chen, W.; Hu, Z.; Li, Z.; Liang, Y.; Chen, J. Data Collection for Mobile Group Consumption: An Asynchronous Distributed Approach. Sensors 2016, 16, 482.

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