Abstract
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.
Highlights
Group consumption refers to consumption by a group of people; for example, a couple having dinner at a restaurant, two friends watching a film at the cinema or a girl, accompanied by two of her colleagues, going shopping to buy a skirt
The results showed that the approach can effectively support data collection of mobile group consumption
We build the system model of mobile group consumption based on asynchronous message passing, i.e., it is not based on a centralized server or synchronized clock
Summary
Group consumption refers to consumption by a group of people; for example, a couple having dinner at a restaurant, two friends watching a film at the cinema or a girl, accompanied by two of her colleagues, going shopping to buy a skirt. Existing data collection systems [4,5,6] that can be used for mobile group consumption are based on centralized processing. We present an asynchronous distributed data collection approach designed to analyze mobile group consumption. The results showed that the approach can effectively support data collection of mobile group consumption. We build the system model of mobile group consumption based on asynchronous message passing, i.e., it is not based on a centralized server or synchronized clock. We propose a three-layer mechanism to collect data for mobile group consumption in an asynchronous distributed way. The remainder of the paper is organized as follows: Section 2 presents the system model of asynchronous distributed data collection that we built for mobile group consumption. We add the design of our simulation system, extend the approach to support more complex temporal relations for causality detection, support the message passing with arbitrary speed and provide more analytical details and simulation results
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