CloudSpider: Combining Replication with Scheduling for Optimizing Live Migration of Virtual Machines across Wide Area Networks

Bose, Saswata; Brock, Scott; Skeoch, Ronald; Rao, Shrisha

doi:10.1109/ccgrid.2011.16

Cited by 39 publications

(17 citation statements)

References 10 publications

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“…Dynamic resource allocation using live migration has been studied in a number of works [33][34][35][36][37]. Integrating live migration with replication has been tackled in [23,24,41]. A performance model for concurrent live migrations is constructed in [32].…”

Section: Related Workmentioning

confidence: 99%

Reducing the Migration Times of Multiple VMs on WANs Using a Feedback Controller

Kang

Tsugawa

Fortes

et al. 2013

2013 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum

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Virtual machine (VM) migration is affected by network latency and throughput, which are highly fluctuating and unpredictable in wide-area networks (WANs). Hence, it is difficult to statically minimize the time required to transfer a large number of VMs across WAN. The goal of this work is to migrate as many VMs as possible during a given period of time and it is motivated by disaster recovery scenarios. One approach is to migrate a large number of VMs in parallel, but this leads to long migration times of each individual VM. Long migration times are problematic in catastrophic circumstances where resources are limited and can fail within a short period of time. Thus, it is important to shorten both the total time required to migrate multiple VMs and the migration time of individual VMs. Due to network performance fluctuations, the optimal number of parallel migrations changes over time. This work proposes a feedback-based controller that adapts to the number of parallel VM migrations in response to changes in a WAN. The controller implements an algorithm inspired by the TCP congestion avoidance algorithm in order to regulate the number of VMs in transit depending on the network conditions. Experiments using a prototype controller confirm that it is possible to control the migration of a set of VMs shortening both the total and individual migration times. The experiments show that the controller shortens the individual migration time by up to 5.7 fold compared to that of the static VM migrations where the number of parallel migrations does not change until all migrations are completed. The contributions of this work are 1) introducing migration strategies for multiple VMs on WANs and 2) proposing a hypervisor-independent controller that adapts to network bandwidth fluctuations in disaster scenarios.

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Section: Related Workmentioning

confidence: 99%

Reducing the Migration Times of Multiple VMs on WANs Using a Feedback Controller

Kang

Tsugawa

Fortes

et al. 2013

2013 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum

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“…In the recent study [14], VM migration is considered for dynamic resource management in cloud environments. In [15], VM replication and scheduling are intelligently combined for VM migration across wide area network environments. However, there are few studies on VM resource management in mobile cloud environments.…”

Section: Game-theoretical Approach For Resource Allocationmentioning

confidence: 99%

Toward cloud-based vehicular networks with efficient resource management

et al. 2013

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In the era of Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then, we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.Rong Yu [S05, M08] (yurong@ieee.org) received his Ph.D. from Tsinghua University, China, in 2007. After that, he worked in the School of Electronic and Information Engineering of South China University of Technology (SCUT). In 2010, he joined the Institute of Intelligent Information Processing at Guangdong University of Technology (GDUT), where he is now an associate professor. His research interest mainly focuses on wireless communications and networking, including cognitive radio, wireless sensor networks, and home networking. He is the co-inventor of over 10 patents and author or co-author of over 50 international journal and conference papers. Dr. Yu is currently serving as the deputy secretary general of the Internet of Things (IoT) Industry Alliance, Guangdong, China, and the deputy head of the IoT Engineering Center, Guangdong, China. He is the member of home networking standard committee in China, where he leads the standardization work of three standards. 9 Yan Zhang [SM10] (yanzhang@ieee.org) received a Ph.D. degree from Nanyang Technological University, Singapore. He is working with Simula Research Laboratory, Norway; and he is an adjunct Associate Professor at the University of Oslo, Norway. He is an associate editor or guest editor of a number of international journals. He serves as organizing committee chairs for many international conferences. His research interests include resource, mobility, spectrum, energy, and data management in wireless communications and networking. and the Head of the Network Convergence Laboratory (NCL) in Essex. His main research interests include wireless networks/communications, fixed mobile convergence, future Internet technology and network virtualization. He has published over 150 papers in the above research areas. He serves on the editorial boards of both IEEE and non-IEEE journals. He is a Senior Member of IEEE and a Fellow of IET.

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“…The work in [15] considers the inherent dependencies between VMs comprising a multi-tier application and introduces an efficient scheme for incorporating inter-VM dependencies and the underlying network topology into VM migration decisions. Bose et al [16] propose to combine VM replication with scheduling to minimize VM migration latencies. They propose an algorithm that factors in de-duplication ratios amongst pairs of images while deciding on the replica placement of VM images, and they show that their approach can judiciously place the replicas of VM images at multiple cloud sites to minimize the storage requirements.…”

Section: Related Workmentioning

confidence: 99%

A Cross-Entropy-Based Admission Control Optimization Approach for Heterogeneous Virtual Machine Placement in Public Clouds

Pan

Wang²

2016

Entropy

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Virtualization technologies make it possible for cloud providers to consolidate multiple IaaS provisions into a single server in the form of virtual machines (VMs). Additionally, in order to fulfill the divergent service requirements from multiple users, a cloud provider needs to offer several types of VM instances, which are associated with varying configurations and performance, as well as different prices. In such a heterogeneous virtual machine placement process, one significant problem faced by a cloud provider is how to optimally accept and place multiple VM service requests into its cloud data centers to achieve revenue maximization. To address this issue, in this paper, we first formulate such a revenue maximization problem during VM admission control as a multiple-dimensional knapsack problem, which is known to be NP-hard to solve. Then, we propose to use a cross-entropy-based optimization approach to address this revenue maximization problem, by obtaining a near-optimal eligible set for the provider to accept into its data centers, from the waiting VM service requests in the system. Finally, through extensive experiments and measurements in a simulated environment with the settings of VM instance classes derived from real-world cloud systems, we show that our proposed cross-entropy-based admission control optimization algorithm is efficient and effective in maximizing cloud providers' revenue in a public cloud computing environment.

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CloudSpider: Combining Replication with Scheduling for Optimizing Live Migration of Virtual Machines across Wide Area Networks

Cited by 39 publications

References 10 publications

Reducing the Migration Times of Multiple VMs on WANs Using a Feedback Controller

Reducing the Migration Times of Multiple VMs on WANs Using a Feedback Controller

Toward cloud-based vehicular networks with efficient resource management

A Cross-Entropy-Based Admission Control Optimization Approach for Heterogeneous Virtual Machine Placement in Public Clouds

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