Auric: using data-driven recommendation to automatically generate cellular configuration
Auric: using data-driven recommendation to automatically generate cellular configuration
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Auric：使用数据驱动的推荐自动生成蜂窝配置
DOI：
10.1145/3452296.3472906
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Karunasish Biswas
中科院分区：
文献类型：
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作者：
A. Mahimkar;A. Sivakumar;Zihui Ge;Shomik Pathak;Karunasish Biswas
蜂窝服务提供商在网络中添加载波，以便支持语音和数据业务的增长需求，并向用户提供良好的服务质量。新载波的添加要求网络运营商针对期望的行为准确地配置其参数。这是一个具有挑战性的问题，因为大量的参数与各种功能，如用户移动性，干扰管理和负载平衡。此外，相同的参数可以在不同的位置上具有不同的值，以按计划管理用户和业务行为，并适当地响应不同的信号传播模式和干扰。手动配置耗时、繁琐且容易出错，可能导致服务质量下降。在本文中，我们提出了一种新的数据驱动的建议方法Auric自动和准确地生成配置参数的蜂窝网络中添加的新载波。我们的方法采用了新的算法，基于协同过滤和地理邻近自动确定现有运营商之间的相似性。我们使用真实的LTE网络数据进行了全面的评估，并在大量载波和配置参数中观察到高准确性（96%）。我们还分享了在生产环境中部署和使用Auric的经验。
Cellular service providers add carriers in the network in order to support the increasing demand in voice and data traffic and provide good quality of service to the users. Addition of new carriers requires the network operators to accurately configure their parameters for the desired behaviors. This is a challenging problem because of the large number of parameters related to various functions like user mobility, interference management and load balancing. Furthermore, the same parameters can have varying values across different locations to manage user and traffic behaviors as planned and respond appropriately to different signal propagation patterns and interference. Manual configuration is time-consuming, tedious and error-prone, which could result in poor quality of service. In this paper, we propose a new data-driven recommendation approach Auric to automatically and accurately generate configuration parameters for new carriers added in cellular networks. Our approach incorporates new algorithms based on collaborative filtering and geographical proximity to automatically determine similarity across existing carriers. We conduct a thorough evaluation using real-world LTE network data and observe a high accuracy (96%) across a large number of carriers and configuration parameters. We also share experiences from our deployment and use of Auric in production environments.
DOI：
10.1145/3132747.3132753
发表时间：
2017-10
期刊：
Proceedings of the 26th Symposium on Operating Systems Principles
影响因子：
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作者：
Aaron Gember;Aditya Akella;Ratul Mahajan;H. Liu
通讯作者：
Aaron Gember;Aditya Akella;Ratul Mahajan;H. Liu
AED：逐步综合符合策略且可管理的配置
DOI：
10.1145/3386367.3431304
发表时间：
2020
期刊：
Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
影响因子：
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作者：
Abhashkumar, Anubhavnidhi;Gember-Jacobson, Aaron;Akella, Aditya
通讯作者：
Akella, Aditya
影响因子：
8.3
作者：
de Simone, G;Verdecchia, P;Maggioni, AP
通讯作者：
Maggioni, AP