Magus: minimizing cellular service disruption during network upgrades
Magus: minimizing cellular service disruption during network upgrades
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Magus：最大限度地减少网络升级期间的蜂窝服务中断
DOI：
10.1145/2716281.2836106
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Jia Wang
中科院分区：
文献类型：
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作者：
Xing Xu;Ioannis Broustis;Zihui Ge;R. Govindan;A. Mahimkar;N. K. Shankaranarayanan;Jia Wang
蜂窝网络中的计划升级每天都会发生，可能经常需要在工作日执行，并且可能会降低对客户的服务。在这篇文章中，我们探讨了调整网络配置的问题，以减轻由于计划中的升级使基站停播而产生的任何潜在影响。其目标是挽回在没有任何修改的情况下可能会发生的服务性能或覆盖范围的损失。据我们所知，规划基站停机时间的影响缓解在以前的文献中还没有被探索过。这项工作的主要贡献是基于预测模型的主动方法，该模型使用用户密度分布和路径损耗的操作数据(而不是这些的理想化分析模型)来快速估计实现高恢复的相邻基站的最佳功率和倾斜配置。次要贡献是最小化同步切换的方法。这些想法体现在一种名为MAGUS的功能中，使我们能够在某些情况下恢复因大型美国移动网络的计划升级而造成的潜在性能损失的76%，并且这种恢复随基站密度的不同而不同。此外，Magus能够将同步切换减少到原来的1/8。
Planned upgrades in cellular networks occur every day, may often need to be performed on weekdays, and can potentially degrade service for customers. In this paper, we explore the problem of tuning network configurations in order to mitigate any potential impact due to a planned upgrade which takes the base station off-air. The objective is to recover the loss in service performance or coverage which would have occurred without any modifications. To our knowledge, impact mitigation for planned base station downtimes has not been explored before in the literature. The primary contribution of this work is a proactive approach based on a predictive model that uses operational data of user density distributions and path loss (rather than idealized analytical models of these) to quickly estimate the best power and tilt configuration of neighboring base stations that enables high recovery. A secondary contribution is an approach to minimize synchronized handovers. These ideas, embodied in a capability called Magus, enables us to recover up to 76% of the potential performance loss due to planned upgrades in some cases for a large US mobile network, and this recovery varies as a function of base station density. Moreover, Magus is able to reduce synchronized handovers by a factor of 8.