Fast and space-efficient virtual machine checkpointing

Park, Eunbyung; Egger, Bernhard; Lee, Jaejin

doi:10.1145/1952682.1952694

Cited by 44 publications

(21 citation statements)

References 17 publications

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“…The argument that supported para-virtualization was that HW cannot run fast enough using the emulation paradigm. Later on, Intel and AMD added an extra feature for the hypervisor and closed the gap between fully virtualized and para-virtualized systems [66].…”

Section: Brief Virtualization Technologies Surveymentioning

confidence: 99%

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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CLOUD COMPUTING COST AND ENERGY OPTIMIZATION THROUGH FEDERATED CLOUD SOSThe two most significant differentiators amongst contemporary Cloud Computing service providers have increased green energy use and datacenter resource utilization. This work addresses these two issues from a system's architectural optimization viewpoint. The proposed approach herein, allows multiple cloud providers to utilize their individual computing resources in three ways by:(1) cutting the number of datacenters needed, (2) scheduling available datacenter grid energy via aggregators to reduce costs and power outages, and lastly by (3) utilizing, where appropriate, more renewable and carbon-free energy sources. Altogether our proposed approach creates an alternative paradigm for a Federated Cloud SoS approach. The proposed paradigm employs a novel control methodology that is tuned to obtain both financial and environmental advantages. It also supports dynamic expansion and contraction of computing capabilities for handling sudden variations in service demand as well as for maximizing usage of time varying green energy supplies. Herein we analyze the core SoS requirements, concept synthesis, and functional architecture with an eye on avoiding inadvertent cascading conditions. We suggest a physical architecture that diminishes unwanted outcomes while encouraging desirable results. Finally, in our approach, the constituent cloud services retain their independent ownership, objectives, funding, and sustainability means.This work analyzes the core SoS requirements, concept synthesis, and functional architecture.It suggests a physical structure that simulates the primary SoS emergent behavior to diminish unwanted outcomes while encouraging desirable results. The report will analyze optimal computing generation methods, optimal energy utilization for computing generation as well as a procedure for building optimal datacenters using a unique hardware computing system design based on the openCompute community as an illustrative collaboration platform. Finally, the research concludes with ii security features cloud federation requires to support to protect its constituents, its constituents tenants and itself from security risks.iii ACKNOWLEDGEMENTS

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Section: Brief Virtualization Technologies Surveymentioning

confidence: 99%

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

2017

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“…The main drawbacks of VM checkpointing are the synchronization overhead and the storage space required for a larger number of VMs. In this regard, similarity compression (SC) [76] reduces the storage space by using a compression algorithm, while fast and capacity-efficient VM checkpoint (FVMCheck) [68] reduces the storage space and synchronization overhead using page-caching technique. More recently, an extension of Remus, RemusDB [69], has been proposed to reduce synchronization and checkpoint overhead (see Table I).…”

Section: Techniques and Approachesmentioning

confidence: 99%

A Survey on Resiliency Techniques in Cloud Computing Infrastructures and Applications

Colman-Meixner

Develder

Tornatore

et al. 2016

IEEE Commun. Surv. Tutorials

130

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Abstract-Today's businesses increasingly rely on cloud computing, which brings both great opportunities and challenges. One of the critical challenges is resiliency: disruptions due to failures (either accidental or because of disasters or attacks) may entail significant revenue losses (e.g., US$ 25.5 billion in 2010 for North America). Such failures may originate at any of the major components in a cloud architecture (and propagate to others): (i) the servers hosting the application, (ii) the network interconnecting them (on different scales, inside a data center, up to wide-area connections), or (iii) the application itself. We comprehensively survey a large body of work focusing on resilience of cloud computing, in each (or a combination) of the server, network, and application components.First, we present the cloud computing architecture and its key concepts. We highlight both the infrastructure (servers, network) and application components. A key concept is virtualization of infrastructure (i.e., partitioning into logically separate units), and thus we detail the components in both physical and virtual layers. Before moving to the detailed resilience aspects, we provide a qualitative overview of the types of failures that may occur (from the perspective of the layered cloud architecture), and their consequences.The second major part of the paper introduces and categorizes a large number of techniques for cloud computing infrastructure resiliency. This ranges from designing and operating the facilities, servers, networks, to their integration and virtualization (e.g., also including resilience of the middleware infrastructure).The third part focuses on resilience in application design and development. We study how applications are designed, installed, and replicated to survive multiple physical failure scenarios as well as disaster failures.

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“…Park et al [10] present a technique for fast and space-efficient checkpointing of virtual machines. Modern operating systems (OSs) use the better part of the available memory for a page cache that caches data recently read from or written to disk.…”

Section: Related Workmentioning

confidence: 99%

FITDOC: fast virtual machines checkpointing with delta memory compression

Shi

Jin

et al. 2015

J Supercomput

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Virtualization provides the function of saving the entire status of the execution environment of a running virtual machine (VM), which makes checkpointing flexible and practical for HPC servers or data center servers. However, the systemlevel checkpointing needs to save a large number of data to the disk. Moreover, the overhead grows linearly with the increasing size of virtual machine memory, which leads to disk I/O consumption disaster along with poor system scalability. To target this, we propose a novel fast VM checkpointing approach, named Fast Incremental checkpoinTing with Delta memOry Compression (FITDOC). By studying the runtime memory characteristics of different workloads, FITDOC counts the dirty pages in a fine-granularity manner (i.e., the number of 8 bytes), instead of in the conventional method (i.e., the number of pages). FITDOC utilises a dirty page logging mechanism to record the dirty pages. Accordingly, a delta memory compression mechanism is implemented to eliminate redundant memory data in checkpointing files. To locate the dirty data in dirty pages, FITDOC utilizes two mechanisms: by analyzing the distribution characteristics of dirty pages in the dirty bitmap, we propose a fast dirty bitmap scanning method to locate the dirty pages, and take a multi-threading data comparison mechanism to locate the real dirty data in one page. The experimental results show that compared with Xen's default system-level checkpointing algorithm, FITDOC can on average reduce checkpointing time 70.54 % with a 1 GB memory size A preliminary version containing some of the results in this paper has been published in the CSE 2014. 123Y. Du et al. and achieve better improvement for VMs with larger memory configurations. FITDOC can reduce the size of checkpointing data 52.88 % on average compared with Remus's incremental solution, which is in page granularity. Compared with the default dirty bitmap scanning method in Xen, the scanning time of FITDOC is decreased by 91.13 % on average.

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Fast and space-efficient virtual machine checkpointing

Cited by 44 publications

References 17 publications

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

Cloud Computing Cost and Energy Optimization through Federated Cloud SoS

A Survey on Resiliency Techniques in Cloud Computing Infrastructures and Applications

FITDOC: fast virtual machines checkpointing with delta memory compression

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