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  1. Abstract—Virtual Network Functions (VNFs) are software implementation of middleboxes (MBs) (e.g., firewalls and proxy servers) that provide performance and security guarantees for virtual machine (VM) cloud applications. In this paper, we study a new VM flow migration problem for dynamic VNF-enabled cloud data centers (VDCs). The goal is to migrate the VM flows in the dynamic VDCs to minimize the total network traffic while load-balancing VNFs with limited processing capabilities. We refer to the problem as FMDV: flow migration in dynamic VDCs. We propose an optimal and efficient minimum cost flow-based flow migration algorithm and two benefit-based efficient heuristic algorithms to solve the FMDV. Via extensive simulations, we show that our algorithms are effective in mitigating dynamic cloud traffic while achieving load balance among VNFs. In particular, all our algorithms reduce dynamic network traffic in all cases and our optimal algorithm always achieves the best traffic-mitigation effect, reducing the network traffic by up to 28% compared to the case without flow migration. 
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  2. Abstract

    Theβ-delayed neutron-emission probabilities of 28 exotic neutron-rich isotopes of Pm, Sm, Eu, and Gd were measured for the first time at RIKEN Nishina Center using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The existingβ-decay half-life (T1/2) database was significantly increased toward more neutron-rich isotopes, and uncertainties for previously measured values were decreased. The new data not only constrain the theoretical predictions of half-lives andβ-delayed neutron-emission probabilities, but also allow for probing the mechanisms of formation of the high-mass wing of the rare-earth peak located atA≈ 160 in ther-process abundance distribution through astrophysical reaction network calculations. An uncertainty quantification of the calculated abundance patterns with the new data shows a reduction of the uncertainty in the rare-earth peak region. The newly introduced variance-based sensitivity analysis method offers valuable insight into the influence of important nuclear physics inputs on the calculated abundance patterns. The analysis has identified the half-lives of168Sm and of several gadolinium isotopes as some of the key variables among the current experimental data to understand the remaining abundance uncertainty atA= 167–172.

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