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Data Collection for Mobile Group Consumption: An Asynchronous Distributed Approach ?

机译:用于移动组消费的数据收集:一种异步分布式方法?

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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.
机译:移动组消费是指基于移动通信的一群人的消费,例如一对夫妇,一家人,同事和朋友。由于小组成员之间的复杂关系,它不同于仅涉及个人的消费。现有的用于移动组消费的数据收集系统是集中式的,其缺点是存在性能瓶颈,单点故障并增加了业务和安全风险。而且,这些数据收集系统基于同步时钟,由于硬件限制,隐私问题或同步成本,这通常是不现实的。在本文中,我们提出了第一种异步分布式方法来收集由移动组消费生成的数据。我们正式建立了基于异步分布式通信的系统模型。然后,我们为模型设计了一个仿真系统,为此我们提出了一个三层解决方案框架。之后,我们描述如何基于收集的数据来检测系统中发生的两次/三个收集事件的因果关系。支持基于异步分布式通信的因果关系的各种定义。大量的仿真结果表明,该方法对于与移动用户消费相关的数据收集是有效的。

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