scholarly journals Effective Cost Mechanism for Cloudlet Retransmission and Prioritized VM Scheduling Mechanism Over Broker Virtual Machine Communication Framework

2012 ◽  
Vol 2 (3) ◽  
pp. 41-50 ◽  
Author(s):  
Gaurav Raj
Keyword(s):  
Virtual Machine ◽  
Communication Framework ◽  
Vm Scheduling ◽  
Effective Cost ◽  
Machine Communication

scholarly journals Using a vision cognitive algorithm to schedule virtual machines

2014 ◽  
Vol 24 (3) ◽  
pp. 535-550 ◽  
Author(s):  
Jiaqi Zhao ◽  
Yousri Mhedheb ◽  
Jie Tao ◽  
Foued Jrad ◽  
Qinghuai Liu ◽  
...  
Keyword(s):  
Global Optimization ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Optimization Problem ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Primary Concern ◽  
Global Optimization Problem ◽  
Vm Scheduling ◽  
Operation Cost

Abstract Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption

scholarly journals An Effective Method for Scheduling Virtual Machines in Cloud

2018 ◽  
Vol 7 (2.32) ◽  
pp. 481
Author(s):  
T Gunasekhar ◽  
V Vinaykumar ◽  
J Laharipriya ◽  
P Raghubabu
Keyword(s):  
Virtual Machine ◽  
Virtual Machines ◽  
Vm Scheduling ◽  
Ideal Position ◽  
Cloud Framework

With the rise of cloud figuring, processing assets (i.e., systems, servers, stockpiling, applications, and so forth.) are provisioned as metered on-request benefits over systems, and can be quickly dispensed and discharged with negligible management exertion. In the cloud registering worldview, the virtual machine (VM) is a standout amongst the most usually utilized asset units in which business administrations are epitomized. VM scheduling advancement, i.e., finding ideal position plans for VMs and reconfigurations as indicated by the evolving conditions, winds up testing issues for cloud framework suppliers and their clients.

scholarly journals Research on New Virtualization Security Protection Management System Based on Cloud Platform

2022 ◽  
Vol 2146 (1) ◽  
pp. 012010
Author(s):  
Zhihong Li ◽  
Guangxu Liu ◽  
Yijie Dang ◽  
Zhijie Shang ◽  
Nan Lin
Keyword(s):  
Business Model ◽  
Virtual Machine ◽  
Management System ◽  
Security Threats ◽  
Cloud Platform ◽  
Virtual Machine Migration ◽  
It Resources ◽  
The Stability ◽  
Machine Communication ◽  
New Situation

Abstract As an emerging product under the condition of informatization, the utilization of cloud platform in many industries has brought fundamental changes to the production and business model in related fields. The cloud platform provides rich and diverse utilization services to terminals through multi-dimensional integration of different IT resources. With the in-depth utilization of cloud platform, the security problems it faces are becoming more and more prominent. The traditional network security protection means have been difficult to effectively adapt to and deal with the security threats under the new situation of cloud platform utilization. As a prominent part of building cloud platform, the construction level of virtualization security protection system will have an intuitive impact on the security of cloud platform. At present, the virtualization security protection management system under cloud platform is facing direct threats from virtual machine deployment, virtual machine communication and virtual machine migration. Based on this, this paper studies the virtualization security protection management system of cloud platform from the perspective of virtualization security tech, so as to ameliorate the stability, reliability and security of cloud platform.

scholarly journals QoS-aware and Multi-Objective Virtual Machine Dynamic Scheduling for Big Data Centers in Clouds

2021 ◽  
Author(s):  
Jirui Li ◽  
Rui Zhang ◽  
Yafeng Zheng
Keyword(s):  
Load Balancing ◽  
Virtual Machine ◽  
Cost Estimation ◽  
Dynamic Scheduling ◽  
Supply And Demand ◽  
Estimation Method ◽  
Multi Objective ◽  
Vm Scheduling ◽  
Conflicting Objectives ◽  
Migration Cost

Abstract Efficient resource scheduling is one of the most critical issues for big datacenters in clouds to provide continuous services for users. Many existing scheduling schemes based on tasks on virtual machine (VM), pursued either load balancing or migration cost under certain response time or energy efficiency, which cannot meet the true balance of the supply and demand between users and cloud providers. The paper focuses on the following multi-objective optimization problem: how to pay little migration cost as much as possible to keep system load balancing under meeting certain quality of service (QoS) via dynamic VM scheduling between limited physical nodes in a heterogeneous cloud cluster. To make these conflicting objectives coexist, a joint optimization function is designed for an overall evaluation on the basis of a load balancing estimation method, a migration cost estimation method and a QoS estimation method. To optimize the consolidation score, an array mapping and a tree crossover model are introduced, and an improved genetic algorithm (GA) based on them is proposed. Finally, empirical results based on Eucalyptus platform demonstrate the proposed scheme outperforms exiting VM scheduling models.

scholarly journals Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Supriya Kinger ◽  
Rajesh Kumar ◽  
Anju Sharma
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Early Stage ◽  
Operating Cost ◽  
Maximum Temperature ◽  
Threshold Temperature ◽  
Carbon Footprints ◽  
Vm Scheduling ◽  
Computing Paradigm ◽  
Better Than

Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

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