Research on code group routing allocation strategy based on soft defined multi-granular switching system

Author(s):  
Yubao Wang ◽  
xuran Liu ◽  
Zhaoman Jing
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Daoxing Li ◽  
Jing Zeng

Background: Cloud platform is widely used in electric power field. Virtual machine co-resident attack is one of the major security threats to the existing power cloud platform. Objective: This paper proposes a mechanism to defend virtual machine co-resident attack on power cloud platform. Method: Our defense mechanism uses the DBSCAN algorithm to classify and output the classification results through the random forest and uses improved virtual machine deployment strategy which combines the advantages of random round robin strategy and maximum/minimum resource strategy to deploy virtual machines. Results: we made a simulation experiment on power cloud platform of State Grid and verified the effectiveness of proposed defense deployment strategy. Conclusion: After the virtual machine deployment strategy is improved, the coverage of the virtual machine is remarkably reduced which proves that our defense mechanism achieves some effect of defending the virtual machine from virtual machine co-resident attack.


2021 ◽  
pp. 1-34
Author(s):  
Peter A. Forsyth ◽  
Kenneth R. Vetzal ◽  
Graham Westmacott

Abstract We extend the Annually Recalculated Virtual Annuity (ARVA) spending rule for retirement savings decumulation (Waring and Siegel (2015) Financial Analysts Journal, 71(1), 91–107) to include a cap and a floor on withdrawals. With a minimum withdrawal constraint, the ARVA strategy runs the risk of depleting the investment portfolio. We determine the dynamic asset allocation strategy which maximizes a weighted combination of expected total withdrawals (EW) and expected shortfall (ES), defined as the average of the worst 5% of the outcomes of real terminal wealth. We compare the performance of our dynamic strategy to simpler alternatives which maintain constant asset allocation weights over time accompanied by either our same modified ARVA spending rule or withdrawals that are constant over time in real terms. Tests are carried out using both a parametric model of historical asset returns as well as bootstrap resampling of historical data. Consistent with previous literature that has used different measures of reward and risk than EW and ES, we find that allowing some variability in withdrawals leads to large improvements in efficiency. However, unlike the prior literature, we also demonstrate that further significant enhancements are possible through incorporating a dynamic asset allocation strategy rather than simply keeping asset allocation weights constant throughout retirement.


Author(s):  
Valerianus Hashiyana ◽  
Martin Mabeifam Ujakpa ◽  
Nalina Suresh ◽  
Chisanga Nyambe
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