A Stable Matching Algorithm for VM Migration to Improve Energy Consumption and QOS in Cloud Infrastructures

2014 ◽  
Vol 4 (2) ◽  
pp. 15-33
Author(s):  
Abdelaziz Kella ◽  
Ghalem Belalem
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Large Scale ◽  
Virtual Machines ◽  
Service Providers ◽  
Stable Matching ◽  
Coase Theorem ◽  
It Services ◽  
Deferred Acceptance

Cloud Computing is one of the fast spreading technologies for providing utility-based IT services to its users. Large-scale virtualized datacenters are established in order to provide these services. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, datacenters hosting Cloud applications consume huge amounts of electrical energy, contributing to high operational cost for the service providers as well as for the service users. Energy consumption can be reduced by live migration of virtual machines (VM) as required and by switching off idle physical machines (PM). Therefore, we propose an approach that finds a stable matching fair to both VMs and PMs, to improve the energy consumption without affecting the quality of service, instead of favoring either side because of a deferred acceptance procedure. The approach presumes two dynamics thresholds, and prepares those virtual machines on the physical machines that the load is over one of the two presumed values to be migrated. Before migrating all those VMs, we use the Coase theorem to determine the number of VMs to migrate for optimal costs. Our approach aims to improve energy consumption of the datacenters, while delivering an expected Quality of Service.

A Stable Matching Algorithm for VM Migration to Improve Energy Consumption and QOS in Cloud Infrastructures

2015 ◽  
pp. 606-623
Author(s):  
Abdelaziz Kella ◽  
Ghalem Belalem
Keyword(s):  
Quality Of Service ◽  
Energy Consumption ◽  
Large Scale ◽  
Virtual Machines ◽  
Electrical Energy ◽  
Stable Matching ◽  
Coase Theorem ◽  
It Services ◽  
Cloud Infrastructures

Cloud Computing is one of the fast spreading technologies for providing utility-based IT services to its users. Large-scale virtualized datacenters are established in order to provide these services. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, datacenters hosting Cloud applications consume huge amounts of electrical energy, contributing to high operational cost for the service providers as well as for the service users. Energy consumption can be reduced by live migration of virtual machines (VM) as required and by switching off idle physical machines (PM). Therefore, we propose an approach that finds a stable matching fair to both VMs and PMs, to improve the energy consumption without affecting the quality of service, instead of favoring either side because of a deferred acceptance procedure. The approach presumes two dynamics thresholds, and prepares those virtual machines on the physical machines that the load is over one of the two presumed values to be migrated. Before migrating all those VMs, we use the Coase theorem to determine the number of VMs to migrate for optimal costs. Our approach aims to improve energy consumption of the datacenters, while delivering an expected Quality of Service.

Quality of Experience (QoE) for Wireless Video Over Critical Communication Systems

2017 ◽  
pp. 132-167
Author(s):  
Emad Danish ◽  
Mazin I. Alshamrani
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Communication Systems ◽  
Quality Of Experience ◽  
Service Providers ◽  
Wireless Video ◽  
User Centric ◽  
Near Future

Video streaming is expected to acquire a massive share of the global internet traffic in the near future. Meanwhile, it is expected that most of the global traffic will be carried over wireless networks. This trend translates into considerable challenges for Service Providers (SP) in terms of maintaining consumers' Quality of Experience (QoE), energy consumption, utilisation of wireless resources, and profitability. However, the majority of Radio Resource Allocation (RRA) algorithms only consider enhancing Quality of Service (QoS) and network parameters. Since this approach may end up with unsatisfied customers in the future, it is essential to develop innovative RRA algorithms that adopt a user-centric approach based on users' QoE. This chapter focus on wireless video over Critical communication systems that are inspired by QoE perceived by end users. This chapter presents a background to introduce the reader to this area, followed by a review of the related up-to-date literature.

scholarly journals Green Metascheduler Architecture to Provide QoS in Cloud Computing

2015 ◽  
Author(s):  
Osvaldo Adilson De Carvalho Junior ◽  
Sarita Mazzini Bruschi ◽  
Regina Helena Carlucci Santana ◽  
Marcos José Santana
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Response Time ◽  
Large Scale ◽  
Quality Of Services ◽  
Average Response ◽  
Average Response Time ◽  
Private Cloud

The aim of this paper is to propose and evaluate GreenMACC (Green Metascheduler Architecture to Provide QoS in Cloud Computing), an extension of the MACC architecture (Metascheduler Architecture to provide QoS in Cloud Computing) which uses greenIT techniques to provide Quality of Service. The paper provides an evaluation of the performance of the policies in the four stages of scheduling focused on energy consumption and average response time. The results presented confirm the consistency of the proposal as it controls energy consumption and the quality of services requested by different users of a large-scale private cloud.

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.

Dynamic partner selection in Cloud Federation for ensuring the quality of service for cloud consumers

2017 ◽  
Vol 08 (03) ◽  
pp. 1750036 ◽  
Author(s):  
Manoj V. Thomas ◽  
K. Chandrasekaran
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Large Scale ◽  
Service Providers ◽  
Partner Selection ◽  
Cloud Service ◽  
Analytic Hierarchy ◽  
Cloud Federation ◽  
Global Coordination

Cloud Computing has become the popular paradigm for accessing the various scalable and on-demand computing services over the internet. Nowadays, individual Cloud Service Providers (CSPs) offering specialized services to the customers collaborate to form the Cloud Federation, in order to reap the real benefits of Cloud Computing. By collaboration, the member CSPs of the federation achieve better resource utilization and Quality of Service (QoS), thereby increasing their business prospects. When a CSP runs out of resources in the Cloud Federation, in order to offload the customer requests for resources to other CSP(s), identifying a suitable partner is a challenging task due to the lack of global coordination among them. In this paper, we propose the design and implementation of an efficient partner selection mechanism in the Cloud Federation, using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods, and also considering the trust values of various CSPs in the federation. The AHP method is used to calculate the weights of the QoS parameters used in the TOPSIS method which is used to rank the various CSPs in the Cloud Federation according to the user requirements. Simulation results show the effectiveness of this approach in order to efficiently select the trustworthy partners in large scale federations to ensure the required QoS to the cloud consumers.

Open Innovation in the Shared Mobility Market

2021 ◽  
Vol 7 (4) ◽  
pp. 212
Author(s):  
Katarzyna Turoń ◽  
Andrzej Kubik
Keyword(s):  
Quality Of Service ◽  
Open Innovation ◽  
Service Providers ◽  
Mutual Benefit ◽  
It Service ◽  
Mobility Service ◽  
Factors Influencing ◽  
Shared Mobility ◽  
Practical Recommendations

The market for shared mobility services is growing very quickly. New types of vehicles have been introduced, and the offer of available services and functionalities has expanded, the purpose of which is to improve the quality of service. Despite all the improvements, it is still not possible to speak of achieving full availability of systems that meet the needs of users. This is due to the reluctant involvement of operators of shared mobility systems in joining Mobility as a Service platforms based on the idea of open innovation. The aim of the article is to analyze the factors influencing the limitations in the development of open innovations in the form of Mobility as a Service (MaaS) services. The authors focus on identifying the challenges and concerns faced by shared mobility service providers. The article supports the development of the concept of open innovation in shared mobility services. It also contains practical recommendations for the development of MaaS systems. The results of the developed research can be used by operators of shared mobility services, transport authorities, or IT service providers providing MaaS services to strengthen cooperation and integration using the language of mutual benefit.

A Novel QoS Aware Shortest Path Algorithm for VSDN

2017 ◽  
Vol 6 (1) ◽  
pp. 1-14
Author(s):  
Amandeep Kaur Sandhu ◽  
Jyoteesh Malhotra
Keyword(s):  
Energy Consumption ◽  
Shortest Path ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Software Defined Networks ◽  
Shortest Path Algorithm ◽  
Internet Service ◽  
Decrease Energy Consumption

This article describes how a rapid increase in usage of internet has emerged from last few years. This high usage of internet has occurred due to increase in popularity of multimedia applications. However, there is no guarantee of Quality of Service to the users. To fulfill the desired requirements, Internet Service Providers (ISPs) establish a service level agreement (SLA) with clients including specific parameters like bandwidth, reliability, cost, power consumption, etc. ISPs make maximum SLAs and decrease energy consumption to raise their profit. As a result, users do not get the desired services for which they pay. Virtual Software Defined Networks are flexible and manageable networks which can be used to achieve these goals. This article presents shortest path algorithm which improves the matrices like energy consumption, bandwidth usage, successful allocation of nodes in the network using VSDN approach. The results show a 40% increase in the performance of proposed algorithms with a respect to existing algorithms.

scholarly journals A Load Balancing Per Connection Classifier Dengan Pengukuran Quality of Service Pada Jaringan LAN Lingkup Universitas

2020 ◽  
Vol 2 (2) ◽  
pp. 40-53
Author(s):  
Aulia Desy Aulia Nur Utomo
Keyword(s):  
Quality Of Service ◽  
Load Balancing ◽  
Packet Loss ◽  
Service Providers ◽  
Network Configuration ◽  
Network Connection ◽  
Before And After ◽  
Internet Connections ◽  
Use Of Internet

Abstract In the use of internet networks that are general in nature need to implement an appropriate network configuration to maximize the use of internet connections provided by service providers. This is important for the optimal use of internet services and in accordance with utilities that are basically general and shared can be achieved. Per Connection Classifier is a load balancing method for distributing traffic loads to more than one network connection point in a balanced way, so that traffic can run optimally. This research focuses on network configuration methods to maximize internet usage for all users. Quality of Service is used to see the performance of network traffic which is indicated by the value of the parameter delay, throughput, and packet loss. Based on the results of testing and research that have been carried out before and after using load balancing per connection clasifier, the delay value is decreased from 180.26 ms to 148.36 ms and throughput increased from 1.76% to 2.03%, then packet loss decreased from 25.37% to 18.59% according to the TIPHON standard. Keywords: Quality of Service, Per Connection Classification, load balancing, delay, throughput, packet loss

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