scholarly journals Research on Educational Information Platform Based on Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ling Fan ◽  
Meiyi Xia ◽  
Ping Huang ◽  
Jianmin Hu
Keyword(s):  
Cloud Computing ◽  
Safety Factor ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Occupancy Rate ◽  
Information Platform ◽  
Data Safety ◽  
Network Bandwidth ◽  
External Interface ◽  
Educational Information

The traditional method only pays attention to hardware construction and ignores the data processing steps, which leads to high redundant resource occupancy rate, untimely resource sharing, and low platform data safety factor. In order to solve this problem, this paper establishes an educational information platform based on cloud computing. The platform gives the overall structure of the education information platform, including the business layer and the support layer. Then the external interface is designed. Based on the MySQL database interface, users are allowed to use custom data formats and storage management modes to ensure flexibility in using data resources and improve the compatibility between smart terminals and virtual machines through the remote desktop terminal architecture. Through the educational data compression and educational resource sharing model, the generation of redundant messages is reduced, thereby realizing the design of the educational information platform. Experimental results show that this method can effectively reduce the occupancy rate of redundant resources, save network bandwidth, and improve the data safety factor of the platform. The resource sharing time is always less than 2.0 s, which verifies the effectiveness of the method

The Research on University Librarys "Four-in-One" Cloud Computing Services Social System

2013 ◽  
Vol 791-793 ◽  
pp. 1297-1300 ◽  
Author(s):  
Xu Fu Peng ◽  
Shu Dong Shi
Keyword(s):  
Cloud Computing ◽  
Social Services ◽  
Resource Sharing ◽  
Social System ◽  
System Function ◽  
Computing Technique ◽  
Information Platform ◽  
Computing Services ◽  
Cloud Computing Service ◽  
Cloud Computing Services

Aiming at the problems on the management system, function orientation, resource sharing, information platform construction, technical support in university social services, the characteristics of cloud computing technique and its influence on the library informatization were carefully analyzed. The four-in-one cloud computing service society system structures of university library about reading, borrowing, selling, and service were designed and constructed .The problems of how the library serve the society in all directions were solved.

Auto-Scale Resource Provisioning In IaaS Clouds

2020 ◽  
Author(s):  
Zolfaghar Salmanian ◽  
Habib Izadkhah ◽  
Ayaz Isazadeh
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Queueing Systems ◽  
Threshold Value ◽  
Resource Provisioning ◽  
Death Process ◽  
New Host ◽  
Network Bandwidth ◽  
Computing Paradigm ◽  
Long Run

Abstract Users of cloud computing technology can lease resources instead of spending an excessive charge for their ownership. For service delivery in the infrastructure-as-a-service model of the cloud computing paradigm, virtual machines (VMs) are created by the hypervisor. This software is installed on a bare-metal server, called the host, and acted as a broker between the hardware of the host and its VMs. The host is responsible for the allocation of required resources, such as CPU, RAM and network bandwidth, for VMs. Therefore, allocating resources to a VM is equivalent to finding the location of the VM on the hosts. In this paper, we propose a model for resource allocation of a datacenter that includes clusters of hosts. This model is based on the birth–death process of queueing systems and continuous-time Markov chains. We will focus on RAM-intensive VMs and consider the allocation of RAM for a VM as a job in the queueing systems. The purpose of this modeling is to keep the number of running hosts minimum while guaranteeing the quality of service in terms of response. When the utilization of active hosts reaches a predefined threshold value, a new host is added to prevent response time violation, and when host utilization is reduced to a certain threshold, one of the hosts can be deactivated. The experimental results show that, in the long run, the odds of working with more jobs are increased.

scholarly journals Priority Based Mechanism for Resource Sharing in Cloud

2020 ◽  
Vol 9 (3) ◽  
pp. 311-316
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Open Source ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Service Providers ◽  
Priority Level ◽  
Lower Priority ◽  
Computing Technologies ◽  
Cloud Computing Service

Cloud computing technologies are getting matured day by day. Revolutions in underlying software, virtualization and hardware technologies related to storage, processing and computing technologies has helped cloud computing service providers to win trust of concerned stake holders. However, the exponentially increasing demand of cloud based resources has made task of resource management and utilization more and more challenging. A novel load balancing technique in cloud computing environment is presented in this paper. The virtual machines are implemented on an open source cloud computing platform on open source operating system. A virtual machines’ priorities based load balancing approach presented here indicates improvement in overall waiting time for load balancing. The mechanism prioritizes load balancing on same priority level virtual machines or lower priority level virtual machines.

scholarly journals Threshold based VM Placement Technique for Load Balanced Resource Provisioning using Priority Scheme in Cloud Computing

2021 ◽  
Vol 13 (5) ◽  
pp. 01-18
Author(s):  
Mayank Sohani ◽  
Dr. S. C. Jain
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Resource Scheduling ◽  
Resource Provisioning ◽  
Scheduling Model ◽  
Dynamic Resource Provisioning ◽  
Two Factors ◽  
Cloud Framework ◽  
Resource Cost

The unbalancing load issue is a multi-variation, multi-imperative issue that corrupts the execution and productivity of processing assets. Workload adjusting methods give solutions of load unbalancing circumstances for two bothersome aspects over-burdening and under-stacking. Cloud computing utilizes planning and workload balancing for a virtualized environment, resource partaking in cloud foundation. These two factors must be handled in an improved way in cloud computing to accomplish ideal resource sharing. Henceforth, there requires productive resource, asset reservation for guaranteeing load advancement in the cloud. This work aims to present an incorporated resource, asset reservation, and workload adjusting calculation for effective cloud provisioning. The strategy develops a Priority-based Resource Scheduling Model to acquire the resource, asset reservation with threshold-based load balancing for improving the proficiency in cloud framework. Extending utilization of Virtual Machines through the suitable and sensible outstanding task at hand modifying is then practiced by intensely picking a job from submitting jobs using Priority-based Resource Scheduling Model to acquire resource asset reservation. Experimental evaluations represent, the proposed scheme gives better results by reducing execution time, with minimum resource cost and improved resource utilization in dynamic resource provisioning conditions.

scholarly journals Fog-based Spider Web Algorithm to Overcome Latency in Cloud Computing

2020 ◽  
pp. 1781-1790
Author(s):  
ABDUL RASHID DAR ◽  
D Ravindran ◽  
Shahidul Islam
Keyword(s):  
Cloud Computing ◽  
Web Applications ◽  
Virtual Machines ◽  
Fog Computing ◽  
Network Reduction ◽  
Spider Web ◽  
Network Bandwidth ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Cloud Users

The cloud-users are getting impatient by experiencing the delays in loading the content of the web applications over the internet, which is usually caused by the complex latency while accessing the cloud datacenters distant from the cloud-users. It is becoming a catastrophic situation in availing the services and applications over the cloud-centric network. In cloud, workload is distributed across the multiple layers which also increases the latency. Time-sensitive Internet of Things (IoT) applications and services, usually in a cloud platform, are running over various virtual machines (VM’s) and possess high complexities while interacting. They face difficulties in the consolidations of the various applications containing heterogenetic workloads. Fog computing takes the cloud computing services to the edge-network, where computation, communication and storage are within the proximity to the end-user’s edge devices. Thus, it utilizes the maximum network bandwidth, enriches the mobility, and lowers the latency. It is a futuristic, convenient and more reliable platform to overcome the cloud computing issues. In this manuscript, we propose a Fog-based Spider Web Algorithm (FSWA), a heuristic approach which reduces the delays time (DT) and enhances the response time (RT) during the workflow among the various edge nodes across the fog network. The main purpose is to trace and locate the nearest f-node for computation and to reduce the latency across the various nodes in a network. Reduction of latency will enhance the quality of service (QoS) parameters, smooth resource distribution, and services availability. Latency can be an important factor for resource optimization issues in distributed computing environments. In comparison to the cloud computing, the latency in fog computing is much improved.

scholarly journals A Game Theory Approach to Fair and Efficient Resource Allocation in Cloud Computing

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Xin Xu ◽  
Huiqun Yu
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Utilization Rate ◽  
Resources Allocation ◽  
Theory Approach ◽  
On Demand ◽  
Efficient Resource ◽  
Game Theoretic

On-demand resource management is a key characteristic of cloud computing. Cloud providers should support the computational resource sharing in a fair way to ensure that no user gets much better resources than others. Another goal is to improve the resource utilization by minimizing the resource fragmentation when mapping virtual machines to physical servers. The focus of this paper is the proposal of a game theoretic resources allocation algorithm that considers the fairness among users and the resources utilization for both. The experiments with an FUGA implementation on an 8-node server cluster show the optimality of this algorithm in keeping fairness by comparing with the evaluation of the Hadoop scheduler. The simulations based on Google workload trace demonstrate that the algorithm is able to reduce resource wastage and achieve a better resource utilization rate than other allocation mechanisms.

Construction on Virtualized Environment for Digital Library Based on Cloud Computing Technology

2014 ◽  
Vol 687-691 ◽  
pp. 3019-3022 ◽  
Author(s):  
Jun Jun Liu
Keyword(s):  
Cloud Computing ◽  
Digital Library ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Computing Environment ◽  
Computing Technology ◽  
Cloud Computing Environment ◽  
Key Technology ◽  
Virtualization Technology

Cloud computing technology is emerging technology in the field of information technology, and its technical advantage has brought new opportunities and challenges for the development and service of digital library in the Internet era. Virtualization is the key technology of cloud computing, and the paper discusses the virtualization of digital library in the cloud computing environment from technical level. Firstly, the paper introduced cloud computing and virtualization technology; then created a virtualized environment for digital library based on the cloud computing technology, and described the function of various levels; finally, the capacity of virtual machines appointment scheduling can be calculated according to formulas. The paper has great significance in enhancing the efficiency and quality of library service, constructing resource sharing system of digital library.

scholarly journals Optimized Mechanism for Resource Sharing in Cloud

2019 ◽  
Vol 9 (2) ◽  
pp. 4889-4893
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Cloud Infrastructure ◽  
Cloud Computing Environment ◽  
Computing Paradigm ◽  
Suggested Technique ◽  
Computing Environments ◽  
Poor Management ◽  
Stable Stage

The cloud computing paradigm has settled to a stable stage. Due to its enormous advantages, services based on cloud computing are getting more and more attraction and adoption by diversified sectors of society. Because of its pay per use model, people prefer to execute various data crunching operations on high end virtual machines. Optimized resource management however becomes critical in such scenarios. Poor management of cloud resources may affect not only customer satisfaction but also wastage of available cloud infrastructure. An optimized resource sharing mechanism for collaborated cloud computing environments is suggested here. The suggested resource sharing technique solves starvation issue in inter cloud load balancing context. In case of occurrence of starvation problem, the suggested technique resolves the issue by switching under loaded and overloaded virtual machines between intra cloud and inter cloud computing environment.

A study on distributed transcoding using dynamic allocation of virtual machines in a cloud computing environment

2015 ◽  
Vol 17 (2) ◽  
pp. 113-120 ◽  
Author(s):  
Seokmo Gu ◽  
Aria Seo ◽  
Yei-chang Kim
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
High Efficiency ◽  
Virtual Machines ◽  
Dynamic Allocation ◽  
Computing Environment ◽  
High Efficiency Video Coding ◽  
Cloud Computing Environment ◽  
Content Type ◽  
Network Bandwidth

Purpose – The purpose of this paper is a transcoding system based on a virtual machine in a cloud computing environment. There are many studies about transmitting realistic media through a network. As the size of realistic media data is very large, it is difficult to transmit them using current network bandwidth. Thus, a method of encoding by compressing the data using a new encoding technique is necessary. The next-generation encoding technique high-efficiency video coding (HEVC) can encode video at a high compressibility rate compared to the existing encoding techniques, MPEG-2 and H.264. Yet, encoding the information takes at least ten times longer than existing encoding techniques. Design/methodology/approach – This paper attempts to solve the tome problem using a virtual machine in a cloud computing environment. Findings – In addition, by calculating the transcoding time of the proposed technique, it found that the time was reduced compared to existing techniques. Originality/value – To this end, this paper proposed transcoding appropriate for the transmission of realistic media by dynamically allocating the resources of the virtual machine.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

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