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Adaptive Dissemination of Data in Time-Critical Asymmetric Communication Environments

机译：关键时间不对称通信环境中的数据自适应分发

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The proliferation of new data-intensive applications in asymmetric communication environments has led to an increasing interest in the development of push-based techniques, in which the information is broadcast to a large population of clients in order to achieve the most efficient use of the limited server and communication resources. It is important to note that quite often the data that is broadcast is time-critical in nature. Most of the related current research focuses on a pure push-based approach (Broadcast Disks model), where the transmission of data is done without allowing explicit requests from the users. More recently, some bidirectional models incorporating a low-capacity uplink channel have been proposed in order to increase the functionality of the Broadcast Disks model. However, the impact of integration of the uplink channel has been investigated using only static client profiles or ignoring the existence of time-sensitive data. None of the existing models integrates all the characteristics needed to perform effectively in a real-world, dynamic time-critical asymmetric communication environment. In this paper we present an adaptive data dissemination model and the associated on-line scheduling algorithms. These improve the functionality and performance of bidirectional broadcast models, maximizing the total number of satisfied users in asymmetric communication environments with dynamic client profiles and time requirements (e.g., mobile systems). This is achieved by means of dynamic adaptation of the broadcast program to the needs of the users, taking into account the bandwidth constraints inherent in asymmetric communication environments and the deadline requirements of the user requests. Performance is evaluated by simulation of a real-time asymmetric communication environment.
机译：非对称通信环境中新的数据密集型应用程序的激增，导致人们对基于推送技术的发展越来越感兴趣，在该技术中，将信息广播给大量客户，以实现对有限用户的最有效利用。服务器和通信资源。重要的是要注意，广播的数据通常是时间关键的。当前大多数相关研究集中在基于纯推式的方法（广播磁盘模型）上，该方法在不允许用户明确请求的情况下进行数据传输。最近，为了增加广播磁盘模型的功能，已经提出了一些结合了低容量上行链路信道的双向模型。但是，仅使用静态客户端配置文件或忽略了对时间敏感的数据的存在，已经研究了上行链路信道集成的影响。现有模型都没有集成在现实世界中动态，时间紧迫的非对称通信环境中有效执行所需的所有特征。在本文中，我们提出了一种自适应数据分发模型和相关的在线调度算法。这些改善了双向广播模型的功能和性能，从而在具有动态客户端配置文件和时间要求的非对称通信环境（例如，移动系统）中最大化了满意的用户总数。这是通过考虑到非对称通信环境中固有的带宽限制和用户请求的截止时间要求，通过使广播节目动态适应用户需求来实现的。通过实时非对称通信环境的仿真来评估性能。

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