Tricube Weighted Linear Regression and Interquartile for Cloud Infrastructural Resource Optimization

Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.

The Effect of Global Smoothness on the Accuracy of Treecodes

Treecode algorithms are widely used in evaluation of N-body pairwise interactions in O(N)or O(NlogN)operations.While they can provide high accuracy approximations,a criticism leveled at the methods is that they lack global smoothness.In this work,we study the effect of smoothness on the accuracy of treecodes by comparing three tricubic interpolation based treecodes with differing smoothness properties:a global C^(1) continuous tricubic,and two new tricubic interpolants,one that is globally C^(0) continuous and one that is discontinuous.We present numerical results which show that higher smoothness leads to higher accuracy for properties dependent on the derivatives of the kernel,nevertheless the global C^(0) continuous and discontinuous treecodes are competitive with the C^(1) continuous treecode.One advantage of the discontinuous treecode over the C^(1) continuous is that,in addition to function evaluations,the discontinuous treecode only requires evaluations of the first derivatives of the kernel while the C^(1) continuous treecode requires evaluations up to third order derivatives.When the first derivatives are computed using finite differences,the discontinuous version can be viewed as kernel independent and of utility for a wider array of kernels with minimal effort.