Live Migration of Virtual Machine (VM) is an action of transferring a working VM from one host to another host on a different physical machine without disturbing the activities of the VM. Live migration enables flexibility in resource optimization, fault tolerance, and load balancing in data center networks. However, migration of VM's from failed or over-utilized hosts to available hosts is an important research issue. OpenStack uses worst-fit as the default migration technique, which does not consider the CPU utilization of hosts. Furthermore, the running instances may consume nearly the entire CPU, which impacts the performance of a particular host. This paper considers how CPU utilization aspects can be added to OpenStack. We calculate the CPU utilization of each host and dynamically migrate the instance from the over-utilized host to the under-utilized host. We observe variation in migration time and downtime considering the CPU utilization aspects for live migration of instances, which significantly impacts the host performance.
The present experimental examination was carried out to suggest a better fuel blend with an optimised dosage level of alumina nanoparticles (Al2O3)—in a mixture of Fish Oil Methyl Ester (FOME) biodiesel and diesel—and injection pressure, wherein enhanced performance and reduced emissions were obtained via a diesel engine. The aluminium nanoparticles were added to the mixture in 5 mg/l steps through varying concentrations from 5 to 20 mg/L. The experimental results showed that engine performance quietly reduces with increased emission characteristics with the addition of raw FOME biodiesel compared to diesel. Furthermore, the addition of aluminium nanoparticles (Al2O3) improved the performance as well as the emission characteristics of the engine. Among all the test blends, the B40D60A20 blend provided a maximum brake thermal efficiency of 30.7%, which is 15.63% superior to raw FOME and 3.90% inferior to diesel fuel. The blend also showed reduced emissions, for instance, a reduction of 48.38% in CO, 17.51% in HC, 16.52% in NOx, and 20.89% in smoke compared to diesel fuel. Lastly, it was concluded that B40D60A20 at 260 bar is the optimised fuel blend, and 20 mg/l is the recommended dose level of aluminium nanoparticles (Al2O3) in the FOME–diesel mixture biodiesels in order to enhance the performance and emission parameters of a diesel engine.
Synthetic aperture radar is an advanced remote sensing and imaging radar. It plays vital role in acquiring high resolution images of earth surface. The capturing of images by synthetic aperture radar is done in any season immaterial of weather conditions. This paper gives the details of the basic feature extraction for the snow images. The two sample images are analyzed to know the feature details of the object under consideration. Analytical details of variation in entropy and the polarization were considered. The scattering mechanism involved in the snow area is analyzed. The details of snow classification based on its layered structure along with its physical nature like moisture involved are presented. The results indicate a high value of entropy of 0.94 for the snow image. The reason for high entropy is because of more surface uniformity in the snow images. The flat surface structured snow basically exhibits the surface scattering mechanism.
The concept of supplying increased power demand at a load centre by a local distributed generation (DG) source has recently attracted much attention in power system research. The impact of DG source penetration on power system transient stability was the main issue studied by several researchers. In this present paper, the impacts of synchronous generator interfaced DGs employing micro turbine (MT) and diesel turbine (DT) on power system stability is investigated through the analysis of critical damping ratio obtained from state-space power system model. Further, Analysis of variance (ANOVA) test was used to determine the significance of DG source penetration levels and their interaction effects on system stability. ANOVA results indicated significant interaction effects between the two DG sources on the system stability.
The idea of meeting increased power demand at a load centre by a distributed generation (DG) source employing locally available energy resources has attracted much attention in power system research. The growth and development of DG is driven by environmental, regulatory and commercial factors. Although DG technology offers many technical benefits, there are certain issues that need to be addressed. The impact of DG penetration on power system stability is one such issue that requires further investigation. The main objective of this article is to analyze the impact of the rotational type of DGs on small-signal and transient stability of power system. The results of critical damping ratio and timedomain indicators are analyzed and discussed. The results indicate that increasing the DG penetration level beyond an optimum value can degrade the stability of the system.
