Research and Realization of I/O Monitoring Based on Xen Cloud Platform

2013 ◽  
Vol 791-793 ◽  
pp. 931-935
Author(s):  
Fa Gui Liu ◽  
Wen Yang Wang ◽  
Zhi Xiong ◽  
Jun Lin
Keyword(s):  
Mobile Technology ◽  
Virtual Machines ◽  
Operation Management ◽  
Functional Testing ◽  
Cloud Platform ◽  
Monitoring Tools ◽  
Monitoring Framework ◽  
Virtualization Technology ◽  
Client Side ◽  
It Enterprises

With the wide application of cloud platform, how to better utilize virtualization technology has become a great challenge for many IT enterprises. This paper proposed an I/O monitoring framework for XCP-based platform. Combining mobile technology, monitoring tools on both server and client side are developed respectively. Functional testing is carried out on the I/O monitoring tools, whose effectiveness and reliability are verified. The XCP-based I/O monitor platform is able to supervise the I/O of virtual machines, which provides a great way for cloud platform operation management.

Design on Framework for Dynamic Monitoring of Virtual Machines

2014 ◽  
Vol 530-531 ◽  
pp. 667-670
Author(s):  
Ke Ming Chen
Keyword(s):  
Operating System ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Dynamic Monitoring ◽  
Cloud Platform ◽  
Monitoring Framework ◽  
New Framework

In order to ensure that the cloud platform client runtime kernel virtual machine security, this paper proposes a new framework for dynamic monitoring of virtual machines, it is for the kernel rootkit attacks, study the cloud client virtual machine operating system kernel safety, presented Hyperchk virtual machine dynamic monitoring framework. This framework mainly for kernel rootkit attacks, ensure that customers running virtual machine kernel security.

An Empirical Performance Evaluation of Docker Container, Openstack Virtual Machine and Bare Metal Server

2017 ◽  
Vol 7 (1) ◽  
pp. 205 ◽  
Author(s):  
Jyoti Shetty ◽  
Sahana Upadhaya ◽  
Rajarajeshwari H S ◽  
Shobha G ◽  
Jayant Chandra
Keyword(s):  
Virtual Machines ◽  
Bare Metal ◽  
Server Virtualization ◽  
Additional Layer ◽  
Virtualization Technology ◽  
Empirical Performance ◽  
Series Of Experiments ◽  
Almost All ◽  
It Enterprises ◽  
Metal Machine

<p>Server virtualization is a fundamental technological innovation that is used extensively in IT enterprises. Server virtualization enables creation of multiple virtual machines on single underlying physical machine. It is realized either in form of hypervisors or containers. Hypervisor is an extra layer of abstraction between the hardware and virtual machines that emulates underlying hardware. In contrast, the more recent container-based virtualization technology runs on host kernel without additional layer of abstraction.Thus container technology is expected to provide near native performance compared to hypervisor based technology. We have conducted a series of experiments to measure and compare the performance of workloads over hypervisor based virtual machines, Docker containers and native bare metal machine. We use a standard benchmark workload suite that stress CPU, memory, disk IO and system. The results obtained show that Docker containers provide better or similar performance compared to traditional hypervisor based virtual machines in almost all the tests. However as expected the native system still provides the best performance as compared to either containers or hypervisors.</p>

A Defense Mechanism Based on Improved Allocation Strategy of VMs Co-Resident Attack in Power Cloud Platform

2020 ◽  
Vol 13 ◽  
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Daoxing Li ◽  
Jing Zeng
Keyword(s):  
Virtual Machine ◽  
Simulation Experiment ◽  
Virtual Machines ◽  
Defense Mechanism ◽  
Security Threats ◽  
Allocation Strategy ◽  
Cloud Platform ◽  
Deployment Strategy ◽  
Dbscan Algorithm ◽  
Maximum Minimum

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.

PMHE:A Wearable Medical Sensor Assisted Framework For Health Care Based On Blockchain And Privacy Computing

2021 ◽  
Author(s):  
Jindong Zhao ◽  
Wenshuo Wang ◽  
Dan Wang ◽  
Chunxiao Mu
Keyword(s):  
Prediction Model ◽  
Homomorphic Encryption ◽  
Physiological Data ◽  
Disease Prediction ◽  
Smart Contracts ◽  
Cloud Platform ◽  
User Privacy ◽  
Fully Homomorphic Encryption ◽  
Client Side ◽  
Medical Cloud

Abstract Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy protection framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged; Besides, it use fully homomorphic encryption method to design a disease prediction model, which was implemented using smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping; Smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too, so it avoids privacy and security issues caused by platform data leakage. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.

scholarly journals eTPM: A Trusted Cloud Platform Enclave TPM Scheme Based on Intel SGX Technology

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3807 ◽  
Author(s):  
Haonan Sun ◽  
Rongyu He ◽  
Yong Zhang ◽  
Ruiyun Wang ◽  
Wai Hung Ip ◽  
...  
Keyword(s):  
Virtual Machines ◽  
Trusted Computing ◽  
Information Leakage ◽  
Research Topic ◽  
Cloud Environment ◽  
Cloud Platform ◽  
Computing Technology ◽  
Security Issues ◽  
Runtime Environment ◽  
Cloud Users

Today cloud computing is widely used in various industries. While benefiting from the services provided by the cloud, users are also faced with some security issues, such as information leakage and data tampering. Utilizing trusted computing technology to enhance the security mechanism, defined as trusted cloud, has become a hot research topic in cloud security. Currently, virtual TPM (vTPM) is commonly used in a trusted cloud to protect the integrity of the cloud environment. However, the existing vTPM scheme lacks protections of vTPM itself at a runtime environment. This paper proposed a novel scheme, which designed a new trusted cloud platform security component, ‘enclave TPM (eTPM)’ to protect cloud and employed Intel SGX to enhance the security of eTPM. The eTPM is a software component that emulates TPM functions which build trust and security in cloud and runs in ‘enclave’, an isolation memory zone introduced by SGX. eTPM can ensure its security at runtime, and protect the integrity of Virtual Machines (VM) according to user-specific policies. Finally, a prototype for the eTPM scheme was implemented, and experiment manifested its effectiveness, security, and availability.

scholarly journals Practice the Mobile Imaging Reading Relay on Virtualization Technology

2017 ◽  
Vol 2 (1) ◽  
pp. 38
Author(s):  
Junyi Yuan ◽  
Jiajin Le
Keyword(s):  
Mobile Technology ◽  
Rapid Development ◽  
Local Computer ◽  
Virtualization Technology ◽  
Mobile Imaging ◽  
Pacs System

<em>In recent years, with the rapid development of the virtualization and mobile technology, it is coming true to realize the mobile imaging reading by using mobile equipment and virtualization technology. When doctor access the imaging reading application, the doctor will only need to send a simple message to server, the server will establish an independent session for the doctor; the imaging reading application will run on the session and show images on the user’s mobile equipment like running on the local computer. It not only can improve pacs system <a href="http://dict.cn/performance">performance</a>, but also can predigest maintenance by using virtualization technology.</em>

scholarly journals Scalable Fog Computing Orchestration for Reliable Cloud Task Scheduling

2021 ◽  
Vol 11 (22) ◽  
pp. 10996
Author(s):  
Jongbeom Lim
Keyword(s):  
Internet Of Things ◽  
Task Scheduling ◽  
Industrial Revolution ◽  
Virtual Machines ◽  
Fog Computing ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Virtualization Technology ◽  
Computing Environments ◽  
One Machine

As Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices are becoming increasingly popular in the era of the Fourth Industrial Revolution, the orchestration and management of numerous fog devices encounter a scalability problem. In fog computing environments, to embrace various types of computation, cloud virtualization technology is widely used. With virtualization technology, IoT and IIoT tasks can be run on virtual machines or containers, which are able to migrate from one machine to another. However, efficient and scalable orchestration of migrations for mobile users and devices in fog computing environments is not an easy task. Naïve or unmanaged migrations may impinge on the reliability of cloud tasks. In this paper, we propose a scalable fog computing orchestration mechanism for reliable cloud task scheduling. The proposed scalable orchestration mechanism considers live migrations of virtual machines and containers for the edge servers to reduce both cloud task failures and suspended time when a device is disconnected due to mobility. The performance evaluation shows that our proposed fog computing orchestration is scalable while preserving the reliability of cloud tasks.

A Two-Phase Load Balancing Algorithm for Cloud Environment

2021 ◽  
Vol 13 (1) ◽  
pp. 38-55
Author(s):  
Archana Singh ◽  
Rakesh Kumar
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Virtual Machines ◽  
Second Phase ◽  
Cloud Environment ◽  
Cloud Platform ◽  
Efficient Utilization ◽  
Two Phase ◽  
Excessive Load ◽  
Load Balancing Algorithm

Load balancing is the phenomenon of distributing workload over various computing resources efficiently. It offers enterprises to efficiently manage different application or workload demands by allocating available resources among different servers, computers, and networks. These services can be accessed and utilized either for home use or for business purposes. Due to the excessive load on the cloud, sometimes it is not feasible to offer all these services to different users efficiently. To solve this excessive load issue, an efficient load balancing technique is used to offer satisfactory services to users as per their expectations also leading to efficient utilization of resources and applications on the cloud platform. This paper presents an enhanced load balancing algorithm named as a two-phase load balancing algorithm. It uses a two-phase checking load balancing approach where the first phase is to divide all virtual machines into two different tables based on their state, that is, available or busy while in the second phase, it equally distributes the loads. The various parameters used to measure the performance of the proposed algorithm are cost, data center processing time, and response time. Cloud analyst simulation tool is used to simulate the algorithm. Simulation results demonstrate superiority of the algorithm with existing ones.

A Hybrid Heuristic for QoS Aware Matching of User's Job and Virtual Machines in Cloud Environment

2018 ◽  
Vol 11 (2) ◽  
pp. 88-109
Author(s):  
Devki Nandan Jha ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Virtual Machines ◽  
Service Providers ◽  
Cloud Provider ◽  
Technological Advancement ◽  
Cloud Platform ◽  
Analytical Hierarchical Process ◽  
Hybrid Heuristic ◽  
Proposed Model

Cloud computing is a technological advancement that provides services in the form of utility on a pay-per-use basis. As the cloud market is expanding, numerous service providers are joining the cloud platform with their services. This creates an indecision amongst the users to choose an appropriate service provider especially when the cloud provider provisions diverse type of virtual machines. The problem becomes more challenging when the user has different jobs requiring specific quality of service. To address the aforementioned problem, this article applies a hybrid heuristic using College Admission Problem and Analytical Hierarchical Process for stable matching of the users' job with the cloud's virtual machines. The case study depicts the effectiveness of the proposed model.

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