Smartphones, tablets and other mobile platforms typically accommodate bulk data storage with low-cost, FAT-formatted Secure Digital cards. When one uses a mobile device to run a full-system virtual machine (VM), there can be a mismatch between 1) the VM's I/O mixture, security and reliability requirements and 2) the properties of the storage media available for VM block storage and checkpoint images. To resolve this mismatch, this paper presents a new VM disk image format called the Logging Block Store (LBS). After motivating the need for a new format, LBS is described in detail with experimental results demonstrating its efficacy. As a result of this work, recommendations are made for future optimizations throughout the stack that may simplify and improve the performance of storage virtualization systems on mobile platforms.
{"title":"Block storage virtualization with commodity secure digital cards","authors":"Harvey Tuch, Cyprien Laplace, K. Barr, Bi Wu","doi":"10.1145/2151024.2151050","DOIUrl":"https://doi.org/10.1145/2151024.2151050","url":null,"abstract":"Smartphones, tablets and other mobile platforms typically accommodate bulk data storage with low-cost, FAT-formatted Secure Digital cards. When one uses a mobile device to run a full-system virtual machine (VM), there can be a mismatch between 1) the VM's I/O mixture, security and reliability requirements and 2) the properties of the storage media available for VM block storage and checkpoint images. To resolve this mismatch, this paper presents a new VM disk image format called the Logging Block Store (LBS). After motivating the need for a new format, LBS is described in detail with experimental results demonstrating its efficacy. As a result of this work, recommendations are made for future optimizations throughout the stack that may simplify and improve the performance of storage virtualization systems on mobile platforms.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129639313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Checkpoint-recovery based virtual machine (VM) replication is an attractive technique for accommodating VM installations with high-availability. It provides seamless failover for the entire software stack executed in the VM regardless the application or the underlying operating system (OS), it runs on commodity hardware, and it is inherently capable of dealing with shared memory non-determinism of symmetric multiprocessing (SMP) configurations. There have been several studies aiming at alleviating the overhead of replication, however, due to consistency requirements, network performance of the basic replication mechanism remains extremely poor., In this paper we revisit the replication protocol and extend it with speculative communication. Speculative communication silently acknowledges TCP packets of the VM, enabling the guest's TCP stack to progress with transmission without exposing the messages to the clients before the corresponding execution state is checkpointed to the backup host. Furthermore, we propose replication aware congestion control, an extension to the guest's TCP stack that aggressively fills up the VMM's replication buffer so that speculative packets can be backed up and released earlier to the clients. We observe up to an order of magnitude improvement in bulk data transfer with speculative communication, and close to native VM network performance when replication awareness is enabled in the guest OS. We provide results of micro-, as well as application-level benchmarks.
{"title":"Enhancing TCP throughput of highly available virtual machines via speculative communication","authors":"Balazs Gerofi, Y. Ishikawa","doi":"10.1145/2151024.2151038","DOIUrl":"https://doi.org/10.1145/2151024.2151038","url":null,"abstract":"Checkpoint-recovery based virtual machine (VM) replication is an attractive technique for accommodating VM installations with high-availability. It provides seamless failover for the entire software stack executed in the VM regardless the application or the underlying operating system (OS), it runs on commodity hardware, and it is inherently capable of dealing with shared memory non-determinism of symmetric multiprocessing (SMP) configurations. There have been several studies aiming at alleviating the overhead of replication, however, due to consistency requirements, network performance of the basic replication mechanism remains extremely poor.,\u0000 In this paper we revisit the replication protocol and extend it with speculative communication. Speculative communication silently acknowledges TCP packets of the VM, enabling the guest's TCP stack to progress with transmission without exposing the messages to the clients before the corresponding execution state is checkpointed to the backup host. Furthermore, we propose replication aware congestion control, an extension to the guest's TCP stack that aggressively fills up the VMM's replication buffer so that speculative packets can be backed up and released earlier to the clients. We observe up to an order of magnitude improvement in bulk data transfer with speculative communication, and close to native VM network performance when replication awareness is enabled in the guest OS. We provide results of micro-, as well as application-level benchmarks.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126266677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Geoffrey Lefebvre, Brendan Cully, Christopher C. D. Head, Mark Spear, N. Hutchinson, M. Feeley, A. Warfield
Operating systems represent large pieces of complex software that are carefully tested and broadly deployed. Despite this, developers frequently have little more than their source code to understand how they behave. This static representation of a system results in limited insight into execution dynamics, such as what code is important, how data flows through a system, or how threads interact with one another. We describe Tralfamadore, a system that preserves complete traces of machine execution as an artifact that can be queried and analyzed with a library of simple, reusable operators, making it easy to develop and run new dynamic analyses. We demonstrate the benefits of this approach with several example applications, including a novel unified source and execution browser.
{"title":"Execution mining","authors":"Geoffrey Lefebvre, Brendan Cully, Christopher C. D. Head, Mark Spear, N. Hutchinson, M. Feeley, A. Warfield","doi":"10.1145/2151024.2151044","DOIUrl":"https://doi.org/10.1145/2151024.2151044","url":null,"abstract":"Operating systems represent large pieces of complex software that are carefully tested and broadly deployed. Despite this, developers frequently have little more than their source code to understand how they behave. This static representation of a system results in limited insight into execution dynamics, such as what code is important, how data flows through a system, or how threads interact with one another. We describe Tralfamadore, a system that preserves complete traces of machine execution as an artifact that can be queried and analyzed with a library of simple, reusable operators, making it easy to develop and run new dynamic analyses. We demonstrate the benefits of this approach with several example applications, including a novel unified source and execution browser.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131461225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhenhao Pan, Yaozu Dong, Yu Chen, Lei Zhang, Zhijiao Zhang
Live migration is one of the most important features of virtualization technology. With regard to recent virtualization techniques, performance of network I/O is critical. Current network I/O virtualization (e.g. Para-virtualized I/O, VMDq) has a significant performance gap with native network I/O. Pass-through network devices have near native performance, however, they have thus far prevented live migration. No existing methods solve the problem of live migration with pass-through devices perfectly. In this paper, we propose CompSC: a solution of hardware state migration that will enable the live migration support of pass-through devices. We go on to apply CompSC to SR-IOV network interface controllers. We discuss the attributes of different hardware states in pass-through devices and migrate them with corresponding techniques. Our experiments show that CompSC enables live migration on an Intel 82599 VF with a throughput 282.66% higher than para-virtualized devices. In addition, service downtime during live migration is 42.9% less than para-virtualized devices.
{"title":"CompSC: live migration with pass-through devices","authors":"Zhenhao Pan, Yaozu Dong, Yu Chen, Lei Zhang, Zhijiao Zhang","doi":"10.1145/2151024.2151040","DOIUrl":"https://doi.org/10.1145/2151024.2151040","url":null,"abstract":"Live migration is one of the most important features of virtualization technology. With regard to recent virtualization techniques, performance of network I/O is critical. Current network I/O virtualization (e.g. Para-virtualized I/O, VMDq) has a significant performance gap with native network I/O. Pass-through network devices have near native performance, however, they have thus far prevented live migration. No existing methods solve the problem of live migration with pass-through devices perfectly.\u0000 In this paper, we propose CompSC: a solution of hardware state migration that will enable the live migration support of pass-through devices. We go on to apply CompSC to SR-IOV network interface controllers. We discuss the attributes of different hardware states in pass-through devices and migrate them with corresponding techniques. Our experiments show that CompSC enables live migration on an Intel 82599 VF with a throughput 282.66% higher than para-virtualized devices. In addition, service downtime during live migration is 42.9% less than para-virtualized devices.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133786872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Process virtualization provides a virtual execution environment within which an unmodified application can be monitored and controlled while it executes. The provided layer of control can be used for purposes ranging from sandboxing to compatibility to profiling. The additional operations required for this layer are performed clandestinely alongside regular program execution. Software dynamic instrumentation is one method for implementing process virtualization which dynamically instruments an application such that the application's code and the inserted code are interleaved together. DynamoRIO is a process virtualization system implemented using software code cache techniques that allows users to build customized dynamic instrumentation tools. There are many challenges to building such a runtime system. One major obstacle is transparency. In order to support executing arbitrary applications, DynamoRIO must be fully transparent so that an application cannot distinguish between running inside the virtual environment and native execution. In addition, any desired extra operations for a particular tool must avoid interfering with the behavior of the application. Transparency has historically been provided on an ad-hoc basis, as a reaction to observed problems in target applications. This paper identifies a necessary set of transparency requirements for running mainstream Windows and Linux applications. We discuss possible solutions to each transparency issue, evaluate tradeoffs between different choices, and identify cases where maintaining transparency is not practically solvable. We believe this will provide a guideline for better design and implementation of transparent dynamic instrumentation, as well as other similar process virtualization systems using software code caches.
{"title":"Transparent dynamic instrumentation","authors":"Derek Bruening, Qin Zhao, Saman P. Amarasinghe","doi":"10.1145/2151024.2151043","DOIUrl":"https://doi.org/10.1145/2151024.2151043","url":null,"abstract":"Process virtualization provides a virtual execution environment within which an unmodified application can be monitored and controlled while it executes. The provided layer of control can be used for purposes ranging from sandboxing to compatibility to profiling. The additional operations required for this layer are performed clandestinely alongside regular program execution. Software dynamic instrumentation is one method for implementing process virtualization which dynamically instruments an application such that the application's code and the inserted code are interleaved together. DynamoRIO is a process virtualization system implemented using software code cache techniques that allows users to build customized dynamic instrumentation tools. There are many challenges to building such a runtime system. One major obstacle is transparency. In order to support executing arbitrary applications, DynamoRIO must be fully transparent so that an application cannot distinguish between running inside the virtual environment and native execution. In addition, any desired extra operations for a particular tool must avoid interfering with the behavior of the application.\u0000 Transparency has historically been provided on an ad-hoc basis, as a reaction to observed problems in target applications. This paper identifies a necessary set of transparency requirements for running mainstream Windows and Linux applications. We discuss possible solutions to each transparency issue, evaluate tradeoffs between different choices, and identify cases where maintaining transparency is not practically solvable. We believe this will provide a guideline for better design and implementation of transparent dynamic instrumentation, as well as other similar process virtualization systems using software code caches.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121198951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Irene Zhang, Alex Garthwaite, Y. Baskakov, K. Barr
In order to make save and restore features practical, saved virtual machines (VMs) must be able to quickly restore to normal operation. Unfortunately, fetching a saved memory image from persistent storage can be slow, especially as VMs grow in memory size. One possible solution for reducing this time is to lazily restore memory after the VM starts. However, accesses to unrestored memory after the VM starts can degrade performance, sometimes rendering the VM unusable for even longer. Existing performance metrics do not account for performance degradation after the VM starts, making it difficult to compare lazily restoring memory against other approaches. In this paper, we propose both a better metric for evaluating the performance of different restore techniques and a better scheme for restoring saved VMs. Existing performance metrics do not reflect what is really important to the user -- the time until the VM returns to normal operation. We introduce the time-to-responsiveness metric, which better characterizes user experience while restoring a saved VM by measuring the time until there is no longer a noticeable performance impact on the restoring VM. We propose a new lazy restore technique, called working set restore, that minimizes performance degradation after the VM starts by prefetching the working set. We also introduce a novel working set estimator based on memory tracing that we use to test working set restore, along with an estimator that uses access-bit scanning. We show that working set restore can improve the performance of restoring a saved VM by more than 89% for some workloads.
{"title":"Fast restore of checkpointed memory using working set estimation","authors":"Irene Zhang, Alex Garthwaite, Y. Baskakov, K. Barr","doi":"10.1145/1952682.1952695","DOIUrl":"https://doi.org/10.1145/1952682.1952695","url":null,"abstract":"In order to make save and restore features practical, saved virtual machines (VMs) must be able to quickly restore to normal operation. Unfortunately, fetching a saved memory image from persistent storage can be slow, especially as VMs grow in memory size. One possible solution for reducing this time is to lazily restore memory after the VM starts. However, accesses to unrestored memory after the VM starts can degrade performance, sometimes rendering the VM unusable for even longer. Existing performance metrics do not account for performance degradation after the VM starts, making it difficult to compare lazily restoring memory against other approaches. In this paper, we propose both a better metric for evaluating the performance of different restore techniques and a better scheme for restoring saved VMs.\u0000 Existing performance metrics do not reflect what is really important to the user -- the time until the VM returns to normal operation. We introduce the time-to-responsiveness metric, which better characterizes user experience while restoring a saved VM by measuring the time until there is no longer a noticeable performance impact on the restoring VM. We propose a new lazy restore technique, called working set restore, that minimizes performance degradation after the VM starts by prefetching the working set. We also introduce a novel working set estimator based on memory tracing that we use to test working set restore, along with an estimator that uses access-bit scanning. We show that working set restore can improve the performance of restoring a saved VM by more than 89% for some workloads.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122513618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rebooting an operating system is a final but effective recovery technique. However, the system performance largely degrades just after the reboot due to the page cache being lost in the main memory. For fast performance recovery, we propose a new reboot mechanism called the warm-cache reboot. The warm-cache reboot preserves the page cache during the reboot and enables an operating system to restore it after the reboot, with the help of a virtual machine monitor (VMM). To perform correct recovery, the VMM guarantees that the reused page cache is consistent with the corresponding files on disks. We have implemented the warm-cache reboot mechanism in the Xen VMM and the Linux operating system. Our experimental results showed that the warm-cache reboot decreased performance degradation just after the reboot. In addition, we confirmed that the file cache corrupted by faults was not reused. The overheads for maintaining cache consistency were not usually large.
{"title":"Fast and correct performance recovery of operating systems using a virtual machine monitor","authors":"Kenichi Kourai","doi":"10.1145/1952682.1952696","DOIUrl":"https://doi.org/10.1145/1952682.1952696","url":null,"abstract":"Rebooting an operating system is a final but effective recovery technique. However, the system performance largely degrades just after the reboot due to the page cache being lost in the main memory. For fast performance recovery, we propose a new reboot mechanism called the warm-cache reboot. The warm-cache reboot preserves the page cache during the reboot and enables an operating system to restore it after the reboot, with the help of a virtual machine monitor (VMM). To perform correct recovery, the VMM guarantees that the reused page cache is consistent with the corresponding files on disks. We have implemented the warm-cache reboot mechanism in the Xen VMM and the Linux operating system. Our experimental results showed that the warm-cache reboot decreased performance degradation just after the reboot. In addition, we confirmed that the file cache corrupted by faults was not reused. The overheads for maintaining cache consistency were not usually large.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132493318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Virtualization is a powerful technique used for variety of application domains, including emerging cloud environments that provide access to virtual machines as a service. Because of the interaction of virtual machines with multiple underlying software and hardware layers, the analysis of the performance of applications running in virtualized environments has been difficult. Moreover, performance analysis tools commonly used in native environments were not available in virtualized environments, a gap which our work closes. This paper discusses the challenges of performance monitoring inherent to virtualized environments and introduces a technique to virtualize access to low-level performance counters on a per-thread basis. The technique was implemented in perfctr-xen, a framework for the Xen hypervisor that provides an infrastructure for higher-level profilers. This framework supports both accumulative event counts and interrupt-driven event sampling. It is light-weight, providing direct user mode access to logical counter values. perfctr-xen supports multiple modes of virtualization, including paravirtualization and hardware-assisted virtualization. perfctr-xen applies guest kernel-hypervisor coordination techniques to reduce virtualization overhead. We present experimental results based on microbenchmarks and SPEC CPU2006 macrobenchmarks that show the accuracy and usability of the obtained measurements when compared to native execution.
{"title":"Perfctr-Xen: a framework for performance counter virtualization","authors":"R. Nikolaev, Godmar Back","doi":"10.1145/1952682.1952687","DOIUrl":"https://doi.org/10.1145/1952682.1952687","url":null,"abstract":"Virtualization is a powerful technique used for variety of application domains, including emerging cloud environments that provide access to virtual machines as a service. Because of the interaction of virtual machines with multiple underlying software and hardware layers, the analysis of the performance of applications running in virtualized environments has been difficult. Moreover, performance analysis tools commonly used in native environments were not available in virtualized environments, a gap which our work closes.\u0000 This paper discusses the challenges of performance monitoring inherent to virtualized environments and introduces a technique to virtualize access to low-level performance counters on a per-thread basis. The technique was implemented in perfctr-xen, a framework for the Xen hypervisor that provides an infrastructure for higher-level profilers. This framework supports both accumulative event counts and interrupt-driven event sampling. It is light-weight, providing direct user mode access to logical counter values. perfctr-xen supports multiple modes of virtualization, including paravirtualization and hardware-assisted virtualization. perfctr-xen applies guest kernel-hypervisor coordination techniques to reduce virtualization overhead. We present experimental results based on microbenchmarks and SPEC CPU2006 macrobenchmarks that show the accuracy and usability of the obtained measurements when compared to native execution.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115209191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Cecchet, Rahul Singh, Upendra Sharma, P. Shenoy
Cloud computing platforms are becoming increasingly popular for e-commerce applications that can be scaled on-demand in a very cost effective way. Dynamic provisioning is used to autonomously add capacity in multi-tier cloud-based applications that see workload increases. While many solutions exist to provision tiers with little or no state in applications, the database tier remains problematic for dynamic provisioning due to the need to replicate its large disk state. In this paper, we explore virtual machine (VM) cloning techniques to spawn database replicas and address the challenges of provisioning shared-nothing replicated databases in the cloud. We argue that being able to determine state replication time is crucial for provisioning databases and show that VM cloning provides this property. We propose Dolly, a database provisioning system based on VM cloning and cost models to adapt the provisioning policy to the cloud infrastructure specifics and application requirements. We present an implementation of Dolly in a commercial-grade replication middleware and evaluate database provisioning strategies for a TPC-W workload on a private cloud and on Amazon EC2. By being aware of VM-based state replication cost, Dolly can solve the challenge of automated provisioning for replicated databases on cloud platforms.
{"title":"Dolly: virtualization-driven database provisioning for the cloud","authors":"E. Cecchet, Rahul Singh, Upendra Sharma, P. Shenoy","doi":"10.1145/1952682.1952691","DOIUrl":"https://doi.org/10.1145/1952682.1952691","url":null,"abstract":"Cloud computing platforms are becoming increasingly popular for e-commerce applications that can be scaled on-demand in a very cost effective way. Dynamic provisioning is used to autonomously add capacity in multi-tier cloud-based applications that see workload increases. While many solutions exist to provision tiers with little or no state in applications, the database tier remains problematic for dynamic provisioning due to the need to replicate its large disk state. In this paper, we explore virtual machine (VM) cloning techniques to spawn database replicas and address the challenges of provisioning shared-nothing replicated databases in the cloud. We argue that being able to determine state replication time is crucial for provisioning databases and show that VM cloning provides this property. We propose Dolly, a database provisioning system based on VM cloning and cost models to adapt the provisioning policy to the cloud infrastructure specifics and application requirements. We present an implementation of Dolly in a commercial-grade replication middleware and evaluate database provisioning strategies for a TPC-W workload on a private cloud and on Amazon EC2. By being aware of VM-based state replication cost, Dolly can solve the challenge of automated provisioning for replicated databases on cloud platforms.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125459157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With existing virtualized systems, hypervisor failures lead to overall system failure and the loss of all the work in progress of virtual machines (VMs) running on the system. We introduce ReHype, a mechanism for recovery from hypervisor failures by booting a new instance of the hypervisor while preserving the state of running VMs. VMs are stalled during the hypervisor reboot and resume normal execution once the new hypervisor instance is running. Hypervisor failures can lead to arbitrary state corruption and inconsistencies throughout the system. ReHype deals with the challenge of protecting the recovered hypervisor instance from such corrupted state and resolving inconsistencies between different parts of hypervisor state as well as between the hypervisor and VMs and between the hypervisor and the hardware. We have implemented ReHype for the Xen hypervisor. The implementation was done incrementally, using results from fault injection experiments to identify the sources of dangerous state corruption and inconsistencies. The implementation of ReHype involved only 880 LOC added or modified in Xen. The memory space overhead of ReHype is only 2.1MB for a pristine copy of the hypervisor code and static data plus a small reserved memory area. The fault injection campaigns used to evaluate the effectiveness of ReHype involved a system with multiple VMs running I/O and hypercall-intensive benchmarks. Our experimental results show that the ReHype prototype can successfully recover from over 90% of detected hypervisor failures.
{"title":"ReHype: enabling VM survival across hypervisor failures","authors":"Michael V. Le, Y. Tamir","doi":"10.1145/1952682.1952692","DOIUrl":"https://doi.org/10.1145/1952682.1952692","url":null,"abstract":"With existing virtualized systems, hypervisor failures lead to overall system failure and the loss of all the work in progress of virtual machines (VMs) running on the system. We introduce ReHype, a mechanism for recovery from hypervisor failures by booting a new instance of the hypervisor while preserving the state of running VMs. VMs are stalled during the hypervisor reboot and resume normal execution once the new hypervisor instance is running. Hypervisor failures can lead to arbitrary state corruption and inconsistencies throughout the system. ReHype deals with the challenge of protecting the recovered hypervisor instance from such corrupted state and resolving inconsistencies between different parts of hypervisor state as well as between the hypervisor and VMs and between the hypervisor and the hardware. We have implemented ReHype for the Xen hypervisor. The implementation was done incrementally, using results from fault injection experiments to identify the sources of dangerous state corruption and inconsistencies. The implementation of ReHype involved only 880 LOC added or modified in Xen. The memory space overhead of ReHype is only 2.1MB for a pristine copy of the hypervisor code and static data plus a small reserved memory area. The fault injection campaigns used to evaluate the effectiveness of ReHype involved a system with multiple VMs running I/O and hypercall-intensive benchmarks. Our experimental results show that the ReHype prototype can successfully recover from over 90% of detected hypervisor failures.","PeriodicalId":202844,"journal":{"name":"International Conference on Virtual Execution Environments","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125057508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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