An effective approach of creation of virtual machine in cloud computing

Kapse, Poonam V.; Dharmik, R. C.

doi:10.1109/i-smac.2017.8058326

Cited by 4 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The author proposed the VM relocation methodology, which significantly improves energy effectiveness. The proposed approach is improved using the Knapsack algorithm [8], which achieves the resource management for clustering of the Cloud.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms

Supreeth

Patil

2022

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

Cloud computing is expanding gradually as the number of educational applications is rapidly increasing. To get Educational cloud services, internet connectivity is predominantly important and Cloud Environment uses one of the basic technology to manage the Physical servers effectively ie; Virtualization Technology. In Cloud Computing, the data centers host numerous Virtual Machines (VMs) on top of the Servers. Due to the rapid growth of Educational platforms, the workload of the VM is computationally getting increased. In the Cloud Educational platforms, to execute the jobs IT resources are provisioned over the network. Since the data generated from the client-side is dynamic in nature, it is difficult to allocate the computational resources efficiently. So to enhance the energy efficiency and to provide the resources in an optimized way, a VM Scheduling mechanism with Hybrid Genetic Algorithm-Modified Particle Swarm Optimization (GA-MPSO) is proposed in this work to achieve QoS parameters like reduced Energy consumption, SLA violation, and cost reduction over the heterogeneous environments. The Hybrid G-MPSO develops the optimal range and improves the best range of scheduling the Virtual resources to VMs from Physical Machines (PMs). The proposed approach, when compared to other VM scheduling algorithms, it intensifies the energy consumption to 105KWH, SLA violation rate of 0.08%, reduces the migrations count to 2122, and consumes the overall cost of 2567.68$. The different scheduling methods for VMs are evaluated against the results, which show that the Hybrid GA-MPSO method is far better than the existing algorithms.

show abstract

Section: Related Workmentioning

confidence: 99%

Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms

Supreeth

Patil

2022

Int. J. Emerg. Technol. Learn.

View full text Add to dashboard Cite

show abstract

“…It is the creation and orchestration of small virtual computational chunks in the form of an abstract computing platform. Virtualization technologies are widely used in cloud computing [4,5], which can offer an efficient method to harness the cloud power by fragmenting a cloud physical host into small manageable virtual portions [6]. They make cloud computing services simple, convenient, and cost-effective.…”

Section: Introductionmentioning

confidence: 99%

Evolving Container to Unikernel for Edge Computing and Applications in Process Industry

Chen

Zhou

2021

Processes

View full text Add to dashboard Cite

Industry 4.0 promotes manufacturing and process industry towards digitalization and intellectualization. Edge computing can provide delay-sensitive services in industrial processes to realize intelligent production. Lightweight virtualization technology is one of the key elements of edge computing, which can implement resource management, orchestration, and isolation services without considering heterogenous hardware. It has revolutionized software development and deployment. The scope of this review paper is to present an in-depth analysis of two such technologies, Container and Unikernel, for edge computing. We discuss and compare their applicability in terms of migration, security, and orchestration for edge computing and industrial applications. We describe their performance indexes, evaluation methods and related findings. We then discuss their applications in industrial processes. To promote further research, we present some open issues and challenges to serve as a road map for both researchers and practitioners in the areas of Industry 4.0, industrial process automation, and advanced computing.

show abstract

“…It is also difficult to create a globally scalable MQTT network. A few among the available automation systems [1][2][3][4][5] are Home Automation, Industrial Automation [14], and Building Automation. By using IOT 4.0, the machines are controlled in real time with various control mechanism algorithms.…”

Section: Introductionmentioning

confidence: 99%

Real Time Remote Monitoring, Control and Reporting Dashboard System to Avoid Industrial Disasters Using Industrial IOT

Lokku¹,

Reddy²,

Sai³

et al. 2021

Advances in Science and Technology

View full text Add to dashboard Cite

In today’s global scenario, with the evolution of new technologies and robust ideas, the world gets more involved and embed the advancements of wireless communication with information technology. An ongoing Gartner report assesses that, by 2021, there will be 25.1 billion web associated gadgets, developing at a pace of 32% every year. Bounties of automation are minimizing the human assistance, intervention and reduced risk factor in industry. Here Industrial Automation is used to control systems or things such as computers or robots or machines or sensors with the help of Internet protocol and cloud computing. In this paper six parameters viz., vibration, temperature, humidity, air quality, sound rate and pressure are monitored and controlled remotely using cloud computing. The system performance automatically changes on the basis of sensor data being collected at regular intervals with a feedback mechanism, thereby allowing the system to control or monitor various devices using internet protocols. The threshold values for all the sensors are set as per the industrial standards. These automation techniques find extensive applications in various control mechanisms to operate the equipment under production processes like boilers and heat-treating ovens, steering and stabilization, pressure exerted by ideal gases in confined containers, vibrations by machinery, air pollution released from chemical composites etc.,

show abstract

An effective approach of creation of virtual machine in cloud computing

Cited by 4 publications

References 11 publications

Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms

Hybrid Genetic Algorithm and Modified-Particle Swarm Optimization Algorithm (GA-MPSO) for Predicting Scheduling Virtual Machines in Educational Cloud Platforms

Evolving Container to Unikernel for Edge Computing and Applications in Process Industry

Real Time Remote Monitoring, Control and Reporting Dashboard System to Avoid Industrial Disasters Using Industrial IOT

Contact Info

Product

Resources

About