Software-defined networking (SDN) has generated increased interest due to the rapid growth in the amount of data generated by the development of the Internet and communications, the commercialization of 5G, and increasingly complex networks. While SDN is more advantageous than traditional networks in terms of efficient network management, rapid deployment, and dynamic scalability, the correctness of a network configuration must be ensured in advance. In other words, SDN components such as network devices, SDN controllers, and applications need to be deployed correctly and must be free of rule conflicts, particularly between various application policies; otherwise, it may result in network paralysis in the worst case. This paper assumes that the SDN network is free of rule conflicts when the rules in the SDN switches correctly obey firewall application or policies. To solve this problem, this paper proposes a verification framework for SDN using TLA+. We show that the firewall rule behavior of switches can be formalized using TLA+, and this is verified with the TLC model checker that uses TLA+ as the model description language. We check two different types of topology models through our verification framework to ensure that the same firewall rules are maintained even if the topology changes. The findings show that the firewall rules may be inconsistent as the topology changes. INDEX TERMS Firewall, formal methods, software-defined networking, TLA+.
ABSTRACT:The empirical relationships used to estimate rainfall amounts from polarimetric radar observations were developed and tested by using long-period drop size distribution (DSD) data and monitoring of rainfall events prior to operational use in Korea. Rainfall associated with Typhoon Meari in 2011 was selected to assess the performance of these relationships for point and areal rainfall amounts. Data quality was checked in regions of light rain to enable the quantitative use of polarimetric variables. The distributions of the cross-correlation co-efficient and standard deviation of the differential phase shift agreed with those established in a previous study, but the absolute average deviation of differential reflectivity (Z DR ) was a little distorted. Biases in reflectivity (Z ) and differential reflectivity were calculated following established methods and found to be -0.18 and 0.47 dB, respectively. The accuracy of rainfall amounts calculated from R(K DP ) and R(K DP , Z DR ) was poor. The best estimates of rainfall were obtained using R(Z, Z DR ) based on DSDs from Oklahoma (OKC) in the USA and Busan (BSC) for both the point and areal mean cases. Correlation co-efficients of R(Z, Z DR ) using the BSC DSDs were better than those using the OKC DSDs for areal mean rainfall amounts. Rainfall amounts in this particular case in Korea were estimated more accurately using the Brandes drop shape for R(Z, Z DR ) than the equilibrium drop shape.
To assess the performance of rainfall estimation using specific differential phase observed by Bislsan radar, the first polarimetric radar in Korea, three rainfall cases occurring in 2011 were selected, each caused by different conditions: the first is the Changma front and typhoon, the second is only the Changma front, and the third is only a typhoon. For quantitative use of specific differential phase (KDP), a data quality algorithm was developed for differential phase shift (ΦDP), composed of two steps; the first involves removal of scattered noise and the second is unfolding ofΦDP. This order of the algorithm is necessary so as not to remove unfolded areas, which are the real meteorological target. All noise was removed and the foldedΦDPwere unfolded successfully for this study.RKDPrelations for S-band radar were calculated for 84,754 samples of observed drop size distribution (DSD) using different drop shape assumptions. The relation for the Bringi drop shape showed the best statistics: 0.28 for normalized error, and 6.7 mm for root mean square error for rainfall heavier than 10 mm h-1. Because the drop shape assumption affects the accuracy of rainfall estimation differently for different rainfall types, such characteristics should be taken into account to estimate rainfall more accurately using polarimetric variables.
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