Peeking over the Cellular Walled Gardens - A Method for Closed Network Diagnosis -. Hong, B., Park, S., Kim, H., Kim, D., Hong, H., Choi, H., Seifert, J., Lee, S., & Kim, Y.
abstract   bibtex   
A cellular network is a closed system, and each network operator has built a unique “walled garden” for their network by combining different operation policies, network configurations, and implementation optimizations. Unfortunately, some of these combinations can induce performance degradation due to misconfiguration or unnecessary procedures. To detect such degradation, a thorough understanding of even the minor details of the standards and operator-specific implementations is important. However, it is difficult to detect such problems, as the control plane is complicated by numerous procedures. This paper introduces a simple yet powerful method that diagnoses these problems by exploiting the operator-specific implementations of cellular networks. We develop a signaling collection and analysis tool that collects control plane messages from operators and finds problems through comparative analysis. The analysis process consists of three different control plane comparison procedures that can find such problems effectively. These individual procedures use a time threshold, control flow sequence, and signaling failure as the basis for comparison. To this end, we collect approximately 3.1 million control-plane messages from 13 major cellular operators worldwide. As a case study, we analyze the circuit-switched fallback technology that triggers generation crossover between third generation and long-term evolution technologies.
@article{hong_peeking_nodate,
	title = {Peeking over the {Cellular} {Walled} {Gardens} - {A} {Method} for {Closed} {Network} {Diagnosis} -},
	abstract = {A cellular network is a closed system, and each network operator has built a unique “walled garden” for their network by combining different operation policies, network configurations, and implementation optimizations. Unfortunately, some of these combinations can induce performance degradation due to misconfiguration or unnecessary procedures. To detect such degradation, a thorough understanding of even the minor details of the standards and operator-specific implementations is important. However, it is difficult to detect such problems, as the control plane is complicated by numerous procedures. This paper introduces a simple yet powerful method that diagnoses these problems by exploiting the operator-specific implementations of cellular networks. We develop a signaling collection and analysis tool that collects control plane messages from operators and finds problems through comparative analysis. The analysis process consists of three different control plane comparison procedures that can find such problems effectively. These individual procedures use a time threshold, control flow sequence, and signaling failure as the basis for comparison. To this end, we collect approximately 3.1 million control-plane messages from 13 major cellular operators worldwide. As a case study, we analyze the circuit-switched fallback technology that triggers generation crossover between third generation and long-term evolution technologies.},
	language = {en},
	author = {Hong, Byeongdo and Park, Shinjo and Kim, Hongil and Kim, Dongkwan and Hong, Hyunwook and Choi, Hyunwoo and Seifert, Jean-Pierre and Lee, Sung-Ju and Kim, Yongdae},
	pages = {14}
}
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