Qualitative Characterization of Quality of Service Interference between Virtual Machines

2012 ◽  
Vol 30 (1) ◽  
pp. 47-54
Author(s):  
Ágnes Sálanki ◽  
Imre Kocsis ◽  
András Pataricza ◽  
Zsolt Kocsis
Keyword(s):  
Quality Of Service ◽  
Virtual Machines

scholarly journals An Attribute-Oriented Task Scheduling Strategy for Improvement of Quality of Service in Cloud Computing

2021 ◽  
Author(s):  
Jianying Miao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Simulation Environment ◽  
Attribute Matching ◽  
Resource Allocation Strategy ◽  
And Task

This thesis describes an innovative task scheduling and resource allocation strategy by using thresholds with attributes and amount (TAA) in order to improve the quality of service of cloud computing. In the strategy, attribute-oriented thresholds are set to decide on the acceptance of cloudlets (tasks), and the provisioning of accepted cloudlets on suitable resources represented by virtual machines (VMs,). Experiments are performed in a simulation environment created by Cloudsim that is modified for the experiments. Experimental results indicate that TAA can significantly improve attribute matching between cloudlets and VMs, with average execution time reduced by 30 to 50% compared to a typical non-filtering policy. Moreover, the tradeoff between acceptance rate and task delay, as well as between prioritized and non-prioritized cloudlets, may be adjusted as desired. The filtering type and range and the positioning of thresholds may also be adjusted so as to adapt to the dynamically changing cloud environment.

scholarly journals Priority-Based Virtual Machine Selection Algorithm in Cloud Computing

2019 ◽  
Vol 8 (3) ◽  
pp. 1457-1462
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Cloud Service Provider

Cloud computing technology has gained the attention of researchers in recent years. Almost every application is using cloud computing in one way or another. Virtualization allows running many virtual machines on a single physical computer by sharing its resources. Users can store their data on datacenter and run their applications from anywhere using the internet and pay as per service level agreement documents accordingly. It leads to an increase in demand for cloud services and may decrease the quality of service. This paper presents a priority-based selection of virtual machines by cloud service provider. The virtual machines in the cloud datacenter are configured as Amazon EC2 and algorithm is simulated in cloud-sim simulator. The results justify that proposed priority-based virtual machine algorithm shortens the makespan, by 11.43 % and 5.81 %, average waiting time by 28.80 % and 24.50%, and cost of using the virtual machine by 21.24% and 11.54% as compared to FCFS and ACO respectively, hence improving quality of service.

scholarly journals Randomized routing of virtual machines in IaaS data centers

2019 ◽  
Vol 5 ◽  
pp. e211
Author(s):  
Hadi Khani ◽  
Hamed Khanmirza
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Power Consumption ◽  
Analytical Model ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Virtual Machines ◽  
General Distribution

Cloud computing technology has been a game changer in recent years. Cloud computing providers promise cost-effective and on-demand resource computing for their users. Cloud computing providers are running the workloads of users as virtual machines (VMs) in a large-scale data center consisting a few thousands physical servers. Cloud data centers face highly dynamic workloads varying over time and many short tasks that demand quick resource management decisions. These data centers are large scale and the behavior of workload is unpredictable. The incoming VM must be assigned onto the proper physical machine (PM) in order to keep a balance between power consumption and quality of service. The scale and agility of cloud computing data centers are unprecedented so the previous approaches are fruitless. We suggest an analytical model for cloud computing data centers when the number of PMs in the data center is large. In particular, we focus on the assignment of VM onto PMs regardless of their current load. For exponential VM arrival with general distribution sojourn time, the mean power consumption is calculated. Then, we show the minimum power consumption under quality of service constraint will be achieved with randomize assignment of incoming VMs onto PMs. Extensive simulation supports the validity of our analytical model.

Adaptation and Dependability and Their Key Role in Modern Software Engineering

2012 ◽  
pp. 145-158
Author(s):  
Vincenzo De Florio ◽  
Chris Blondia
Keyword(s):  
Quality Of Service ◽  
Software Engineering ◽  
Software Systems ◽  
Software Performance ◽  
Client Software ◽  
Precise Characterization ◽  
Effective System ◽  
The Face

Current software systems and the environments such systems are meant for requiring a precise characterization of the available resources and provisions to constantly re-optimize in the face of endogenous and exogenous changes and failures. This paper claims that it is simply not possible today to conceive software design without explicitly addressing adaptability and dependability. As an example, the authors remark on how mobile computing technologies call for effective software engineering techniques to design, develop and maintain services that are prepared to continue the distribution of a fixed, agreed-upon quality of service despite of the changes in the location of the client software, performance failures, and the characteristics of the environment. This paper concludes that novel paradigms are required for software engineering so as to provide effective system structures for adaptive and dependable services while keeping the design complexity under control. In this paper, the authors discuss this problem and propose one such structure, also briefly surveying the major milestones in the state of the art in this domain.

scholarly journals A Heuristic Research of the Designing and Evaluation of Energy Efficiency using Dynamic VM Consolidation in Green Cloud Data Centres

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1532-1540
Keyword(s):  
Carbon Dioxide ◽  
Energy Efficiency ◽  
Quality Of Service ◽  
Virtual Machines ◽  
Web Based ◽  
Cloud Data ◽  
The Earth ◽  
Data Centres ◽  
Vm Consolidation

Allotted computing is a blasting innovation that tenders effective assets, and smooth accessibility through web based processing. however, the growing wishes of clients for such administrations are convincing the cloud professional corporations to send huge portions of strength hungry server farms which element awful effect to the earth with the aid of the usage of plenteous Carbon Dioxide discharge. To limit control usage and strengthen the quality of service (QoS) inside the server farm assesses the strength usage in an assortment of plans in IaaS of dispensed computing situation. Dynamic Virtual Machines’ Consolidation and Placement(DVMCP) is an in a position strategies for enhancing using assets and proficient power usage in Cloud DataCenters. in this exploration, we proposed a calculation, Energy Conscious Greeny Cloud Dynamic (ECGCD) set of rules that accomplishes live VM relocation that is turning off the inert has or located it to lowcontrol mode (i.e., rest or hibernation),that builds up power productivity and succesful usage of property in the dynamic hosts. The take a look at stop result confirmations with duplicate that, the proposed calculation achieves good sized diploma of lower in electricity usage in correlation with the modern-day-day VM combination calculations.

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