I/O Workload in Virtualized Data Center Using Hypervisor

Cloud computing [10] is gaining popularity as it’s the way to virtualize the datacenter and increase flexibility in the use of computation resources. This virtual machine approach can dramatically improve the efficiency, power utilization and availability of costly hardware resources, such as CPU and memory. Virtualization in datacenter had been done in the back end of Eucalyptus software and Front end was installed on another CPU. The operation of performance measurement had been done in network I/O applications environment of virtualized cloud. Then measurement was analyzed based on performance impact of co-locating applications in a virtualized cloud in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. This project proposes the virtualization technology which uses the hypervisor to install the Eucalyptus software in single physical machine for setting up a cloud computing environment. By using the hypervisor, the front end and back end of eucalyptus software will be installed in the same machine. The performance will be measured based on the interference in parallel processing of CPU and network intensive workloads by using the Xen Virtual Machine Monitors. The main motivation of this project is to provide the scalable virtualized datacenter

Circadian pacemaker coupling by multi-peptidergic neurons in the cockroach Leucophaea maderae

Lesion and transplantation studies in the cockroach, Leucophaea maderae, have located its bilaterally symmetric circadian pacemakers necessary for driving circadian locomotor activity rhythms to the accessory medulla of the optic lobes. The accessory medulla comprises a network of peptidergic neurons, including pigment-dispersing factor (PDF)-expressing presumptive circadian pacemaker cells. At least three of the PDF-expressing neurons directly connect the two accessory medullae, apparently as a circadian coupling pathway. Here, the PDF-expressing circadian coupling pathways were examined for peptide colocalization by tracer experiments and double-label immunohistochemistry with antisera against PDF, FMRFamide, and Asn13-orcokinin. A fourth group of contralaterally projecting medulla neurons was identified, additional to the three known groups. Group one of the contralaterally projecting medulla neurons contained up to four PDF-expressing cells. Of these, three medium-sized PDF-immunoreactive neurons coexpressed FMRFamide and Asn13-orcokinin immunoreactivity. However, the contralaterally projecting largest PDF neuron showed no further peptide colocalization, as was also the case for the other large PDF-expressing medulla cells, allowing the easy identification of this cell group. Although two-thirds of all PDF-expressing medulla neurons coexpressed FMRFamide and orcokinin immunoreactivity in their somata, colocalization of PDF and FMRFamide immunoreactivity was observed in only a few termination sites. Colocalization of PDF and orcokinin immunoreactivity was never observed in any of the terminals or optic commissures. We suggest that circadian pacemaker cells employ axonal peptide sorting to phase-control physiological processes at specific times of the day

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05-1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4-7 days or ≥ 8 days of 1.25 (1.04-1.48), p = 0.015 and 1.31 (1.11-1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care

An Efficient Hybrid Block Chain -vibrant Neighborhood Partile Swarm Optimization (B- Vnpso) Algorithm for Enhancing Qos in Cloud Computing Services

Abstract As the digital era has progressed, so has the volume of digital data, making secure storage of this vast amount of data an increasingly important concern for data administrators. Cloud computing and the ease of storing and accessing data attracted a large number of IT professionals and administrators to migrate from physical infrastructure to cloud infrastructure. Cloud computing provides a wide range of services, but its primary functionality is the efficient distribution of resources among the many people who need to use the cloud. Effective resource allocation, decreased response time, and increased resource availability are all benefits of optimising cloud computing Quality of Service (QoS), which also helps to keep user data safe in the cloud infrastructure. Even though many studies have sought a high quality of service (QoS), no success has been found in combining efficient resource sharing with privacy protection. This paper uses Block chain technology and the Vibrant Neighborhood Particle Swarm Optimization (VNPSO) algorithm to overcome the aforementioned challenge of achieving better QoS with high levels of data security. While the Block chain has a reduced parameter, it is highly efficient in protecting cloud network storage data, while the Vibrant Neighborhood Particle Swarm Optimization (VNPSO) algorithm is an improvised version of Particle Swarm Optimization (PSO) and is efficient in resource allocation without any restrictions or boundaries in the neighbourhood available resources. Experimentation shows that the proposed meta-heuristic hybrid algorithm outperforms conventional algorithms in terms of Quality of Service.</jats:p

Local Pollination-Based Moth Search Algorithm for Task-Scheduling Heterogeneous Cloud Environment

Abstract Nowadays, Cloud computing is a new computing model in the field of information technology and research. Generally, the cloud environment aims in providing the resource that depends upon the user’s necessity. The major problem caused by cloud computing is task scheduling. Nevertheless, the previous scheduling methods concentrate only on the resource needs, memory, implementation time and cost. In this paper, we introduced an optimal task-scheduling algorithm of the local pollination-based moth search algorithm (LPMSA), which is the hybridization of moth search algorithm (MSA) and flower pollination algorithm (FPA). The proposed LPMSA chooses an optimal solution for proper task scheduling in the cloud. Moreover, the exploitation capacity of MSA is improved by using the local search of the FPA algorithm. In this work, we use 2-fold simulation processes that are implemented under the platform of JAVA. The proposed LPMSA for task-scheduling performance is evaluated using low and high heterogeneous machines with uniform and non-uniform parameters. The experimental analysis demonstrates that the proposed LPMSA approach is well suitable for cloud task scheduling thereby reducing the makespan and energy consumption during proper task scheduling.</jats:p