Experimental study of virtual machine migration in support of reservation of cluster resources (original) (raw)
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Virtual Machine Migration in Cloud Computing Environments
Advances in Systems Analysis, Software Engineering, and High Performance Computing
Recent developments in virtualization and communication technologies have transformed the way data centers are designed and operated by providing new tools for better sharing and control of data center resources. In particular, Virtual Machine (VM) migration is a powerful management technique that gives data center operators the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, mitigate performance hotspots, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. Despite these potential benefits, VM migration also poses new requirements on the design of the underlying communication infrastructure, such as addressing and bandwidth requirements to support VM mobility. Furthermore, devising efficient VM migration schemes is also a challenging problem, as it not only requires weighing the benefits of VM migration, but also considering migration costs,...
2011 IEEE International Conference on Cloud Computing (CLOUD), 2011
Virtualization technology is currently becoming increasingly popular and valuable in cloud computing environments due to the benefits of server consolidation, live migration, and resource isolation. Live migration of virtual machines can be used to implement energy saving and load balancing in cloud data center. However, to our knowledge, most of the previous work concentrated on the implementation of migration technology itself while didn't consider the impact of resource reservation strategy on migration efficiency. This paper focuses on the live migration strategy of multiple virtual machines with different resource reservation methods. We first describe the live migration framework of multiple virtual machines with resource reservation technology. Then we perform a series of experiments to investigate the impacts of different resource reservation methods on the performance of live migration in both source machine and target machine. Additionally, we analyze the efficiency of parallel migration strategy and workload-aware migration strategy. The metrics such as downtime, total migration time, and workload performance overheads are measured. Experiments reveal some new discovery of live migration of multiple virtual machines. Based on the observed results, we present corresponding optimization methods to improve the migration efficiency.
Network-aware migration control and scheduling of differentiated virtual machine workloads
2009
Server virtualization enables dynamic workload management for data centers. However, especially live migrations of virtual machines (VM) induce significant overheads on physical hosts and the shared network infrastructure possibly leading to host overloads and SLA violations of co-hosted applications. While some recent work addresses the impact of live migrations on CPUs of physical hosts, little attention has been given to the control and optimization of migration algorithms and migration-related network bandwidth consumption. In this paper we introduce network topology aware scheduling models for VM live migrations. We propose a scheme for classifying VMs based on their workload characteristics and propose adequate resource and migration scheduling models for each class, taking network bandwidth requirements of migrations and network topologies into account. We also underline the necessity for additional migration control parameters for efficient migration scheduling.
Virtual Machine Migration Enabled Cloud Resource Management: A Challenging Task
2016
Virtualization technology reduces cloud operational cost by increasing cloud resource utilization level. The incorporation of virtualization within cloud data centers can severely degrade cloud performance if not properly managed. Virtual machine (VM) migration is a method that assists cloud service providers to efficiently manage cloud resources while eliminating the need of human supervision. VM migration methodology migrates current-hosted workload from one server to another by either employing live or non-live migration pattern. In comparison to non-live migration, live migration does not suspend application services prior to VM migration process. VM migration enables cloud operators to achieve various resource management goals, such as, green computing, load balancing, fault management, and real time server maintenance. In this paper, we have thoroughly surveyed VM migration methods and applications. We have briefly discussed VM migration applications. Some open research issues...
Incorporating Migration Control in VM Selection Strategies to Enhance Performance
Int. J. Web Appl., 2014
In this work we have designed three algorithms, by doing amalgamation of heuristic method and migration control. Virtual Machine (VM) selection is the immediate step after the host overload is detected. Now decision needs to be made to choice the VM(s) to migrate. VM selection is an important task and the energy consumption depends on the selection. Three VM selection strategies have been proposed in literature and been incorporated in CloudSim, a simulation framework to simulate Cloud architecture, resource provisioning etc. Migration control could influence the VM selection mechanism as steady and resource consuming VMs not to be selected. Reason behind is that, a steady VM which is continuously consuming recourses has high probability of consuming resource in the same manner in future. So if we migrate such VM it will also overload the next datacenter in which we are migrating it to. In this proposed model, CPU usage has been considered to identify a VM to be steady or not. The V...
Migration, Assignment, and Scheduling of Jobs in Virtualized Environment
2011
Migration is an interesting issue for managing resource utilization and performance in clusters. Recent advances in server virtualization have made migration a practical method to achieve these goals. Especially, the live migration of virtualized servers made their pausing times negligible. However, migration of a virtual machine (VM) can slow down other collocated VMs in multiresource shared systems, where all the system resources are shared among collocated VMs. In parallel execution environment, such sudden slow-down phase of systems is called system noise; it may slow down overall systems while increasing the variability of system performance. When we consider the virtual machine assignment problem as resource allocation, those performance issues are hard to be properly treated. In this work, we address how to consider performance in assigning VMs. To achieve this goal, we model a migration process of a VM instance as a pair of jobs that run at the hosts of sender and receiver. We propose a method to analyze the migration time and the performance impact on multiresource shared systems for completing given VM assignment plan. This study may contribute to create more robust performance in virtualized environment.
Performance Framework for Virtual Machine Migration in Cloud Computing
Computers, Materials & Continua
In the cloud environment, the transfer of data from one cloud server to another cloud server is called migration. Data can be delivered in various ways, from one data centre to another. This research aims to increase the migration performance of the virtual machine (VM) in the cloud environment. VMs allow cloud customers to store essential data and resources. However, server usage has grown dramatically due to the virtualization of computer systems, resulting in higher data centre power consumption, storage needs, and operating expenses. Multiple VMs on one data centre manage share resources like central processing unit (CPU) cache, network bandwidth, memory, and application bandwidth. In multi-cloud, VM migration addresses the performance degradation due to cloud server configuration, unbalanced traffic load, resource load management, and fault situations during data transfer. VM migration speed is influenced by the size of the VM, the dirty rate of the running application, and the latency of migration iterations. As a result, evaluating VM migration performance while considering all of these factors becomes a difficult task. The main effort of this research is to assess migration problems on performance. The simulation results in Matlab show that if the VM size grows, the migration time of VMs and the downtime can be impacted by three orders of magnitude. The dirty page rate decreases, the migration time and the downtime grow, and the latency time decreases as network bandwidth increases during the migration time and post-migration overhead calculation when the VM transfer is completed. All the simulated cases of VMs migration were performed in a fuzzy inference system with performance graphs.
Analysis of requirements for virtual machine migration in dynamic clouds
Highly dynamic environments like clouds by nature cause a high degree of unpredictability of resource utilization and performance. Failures, latencies and heterogeneity should always be the main concern for affecting the scheduling decisions in distributed infrastructures. As a result, the scheduling efficiency of jobs before their submission is very difficult to be achieved or either forecasted. Even in the cases of the most complex schedulers a comprehensive dynamic view cannot always be predicted. Thus, the rescheduling concept takes advantage of the current scheduling status and performs a dynamic scheduling decision. In this paper we present a discussion of the virtual machine migration strategies that are currently available in distributed systems based on the need of migrating virtualized resources in order to achieve better resource utilization and performance such as improve load balancing, makespan and higher throughput of jobs. We conclude our study with a critical discussion of vital requirements for virtual machine migration.
Virtual machine migration in cloud data centers: a review, taxonomy, and open research issues
The Journal of Supercomputing, 2015
Virtualization efficiently manages the ever-increasing demand for storage, computing, and networking resources in large-scale Cloud Data Centers. Virtualization attains multifarious resource management objectives including proactive server maintenance, load balancing, pervasive service availability, power management, and fault tolerance by virtual machine (VM) migration. VM migration is a resource-intensive operation as it constantly requires adequate CPU cycles, memory capacity, system cache, and network bandwidth. Consequently, it adversely affects the performance of running applications and cannot be entirely overlooked in contemporary data centers, particularly when user SLA and critical business goals are to be met. The unavailability
IJERT-The Challenges in Virtual Machine Live Migration and Resource Management
International Journal of Engineering Research and Technology (IJERT), 2020
https://www.ijert.org/the-challenges-in-virtual-machine-live-migration-and-resource-management https://www.ijert.org/research/the-challenges-in-virtual-machine-live-migration-and-resource-management-IJERTCONV8IS11064.pdf Cloud computing is becoming increasingly popular and is hosted in huge data centres. Such huge data centres have a huge number of physical servers that are, in effect, virtualized into a large number of Virtual Machines (VMs) managed by cloud infrastructure such as open stack, cloud stack, etc. Virtual Machine migration has become an important criterion for saving resources, growing resource utilization, and maintaining the quality of service (QoS) in cloud data centres with the increasing growth of cloud environments. Different techniques for migration of VMs are established for the efficient use of resources. This paper addresses the live migration of the virtual machine, with its components, drawbacks and resource management.