评估用户流量:基于流量的WiFi移动数据卸载

D. Ciullo, T. Spyropoulos, N. Nikaein, B. Jechoux, Giannis Sarantidis
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引用次数: 1

摘要

我们提出了一种智能卸载策略,动态地将数据流分配给WiFi和蜂窝接口,从而最小化给定的成本函数(与能源消耗和蜂窝计划使用有关),同时保持平均每流延迟有界。所提议的阈值策略的基本见解是将较大的流量分配给提供最佳速率的网络(通常是WiFi),并将较小的流量分配给其他网络,因为能量通常与发送/接收数据所需的时间有关。然而,选择最优的大小截止还必须考虑负载平衡和排队方面、WiFi可用性、流量大小统计和用户/应用程序首选项。我们根据模拟验证了我们的模型,并表明我们的策略优于其他标准或智能策略,实现了相当好的能源延迟权衡,同时只卸载了一小部分(大)流。在基于android的卸载原型上进行的初步测量进一步支持了我们的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sizing Up User Traffic: Flow-based Mobile Data Offloading Over WiFi
We propose a smart offloading policy that dynamically assigns data flows to the WiFi and cellular interfaces, so as to minimize a given cost function (related to energy consumption and cellular plan usage), while keeping the average per-flow delay bounded. The basic insight of the proposed Threshold Policy is to assign larger flows to the network that provides the best rate (often WiFi), and smaller flows to the other, since energy is generally related to the time needed to send/receive data. However, choosing the size cutoff optimally must also consider load-balancing and queueing aspects, WiFi availability, flow size statistics, and user/application preferences. We validate our model against simulations, and show that our policy outperforms other standard or smart policies, achieving considerably better energy-delay trade-offs, while only offloading a small percentage of (large)flows. Initial measurements performed on an Android-based offloading prototype further support our findings.
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