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Magus: minimizing cellular service disruption during network upgrades

Published: 01 December 2015 Publication History

Abstract

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.

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cover image ACM Conferences
CoNEXT '15: Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies
December 2015
483 pages
ISBN:9781450334129
DOI:10.1145/2716281
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 December 2015

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Author Tags

  1. cellular network
  2. network reconfiguration
  3. performance modeling

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  • (2024)Heartbeating with LTE Networks for Ambient BackscatterIEEE Transactions on Mobile Computing10.1109/TMC.2023.3290298(1-12)Online publication date: 2024
  • (2023)Resilient Baseband Processing in Virtualized RANs with SlingshotProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604841(654-667)Online publication date: 10-Sep-2023
  • (2023)Enabling Resilience in Virtualized RANs with AtlasProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613276(1-15)Online publication date: 2-Oct-2023
  • (2023)Chroma: Learning and Using Network Contexts to Reinforce Performance Improving ConfigurationsProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613256(1-16)Online publication date: 2-Oct-2023
  • (2022)AuroraProceedings of the 22nd ACM Internet Measurement Conference10.1145/3517745.3561455(83-97)Online publication date: 25-Oct-2022
  • (2017)Predictive Impact Analysis for Designing a Resilient Cellular Backhaul NetworkProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/31544881:2(1-33)Online publication date: 19-Dec-2017
  • (2017)Reflection: Automated test location selection for cellular network upgrades2017 IEEE 25th International Conference on Network Protocols (ICNP)10.1109/ICNP.2017.8117553(1-10)Online publication date: Oct-2017
  • (2017)Coordinating rolling software upgrades for cellular networks2017 IEEE 25th International Conference on Network Protocols (ICNP)10.1109/ICNP.2017.8117537(1-10)Online publication date: Oct-2017
  • (2017)DeepOpp: Context-Aware Mobile Access to Social Media Content on Underground Metro Systems2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2017.269(1219-1229)Online publication date: Jun-2017

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