Fumio Machida

Redundant virtual machine placement for fault-tolerant consolidated server clusters

Consolidated server systems using server virtualization involves serious risks of host server failures that induce unexpected downs of all hosted virtual machines and applications. To protect applications requiring high-availability from unpredictable host server failures, redundant configuration using virtual machines can be an effective countermeasure. This paper presents a virtual machine placement method for establishing a redundant configuration against host server failures with less host servers. The proposed method estimates the requisite minimum number of virtual machines according to the performance requirements of application services and decides an optimum virtual machine placement so that minimum configurations survive at any k host server failures. The evaluation results clarify that the proposed method achieves requested fault-tolerance level with less number of hosting servers compared to the conventional N+M redundant configuration approach.

Modeling and analysis of software rejuvenation in a server virtualized system

As server virtualization is used as an essential software infrastructure of various software services such as cloud computing, availability management of server virtualized system is becoming more significant. Although time-based software rejuvenation is useful to postpone/prevent failures due to software aging in a server virtualized system, the rejuvenation schedules for virtual machine (VM) and virtual machine monitor (VMM) need to be determined in a proper way for the VM availability, since VMM rejuvenation affects VMs running on the VMM. This paper presents analytic models using stochastic reward nets for three time-based rejuvenation techniques of VMM; (i) Cold-VM rejuvenation in which all VMs are shut down before the VMM rejuvenation, (ii) Warm-VM rejuvenation in which all VMs are suspended before the VMM rejuvenation and (iii) Migrate-VM rejuvenation in which all VMs are moved to the other host server during the VMM rejuvenation. We compare the three techniques in terms of steady-state availability and the number of transactions lost in a year. We find the optimal combination of rejuvenation trigger intervals for each rejuvenation technique by a gradient search method. The numerical analysis shows the interesting result that Warm-VM rejuvenation does not always outperform Cold-VM rejuvenation in terms of steady-state availability depending on rejuvenation trigger intervals. Migrate-VM rejuvenation is better than the other two as long as live VM migration rate is large enough and the other host server has a capacity to accept the migrated VM.

Candy: Component-based Availability Modeling Framework for Cloud Service Management Using SysML

High-availability assurance of cloud service is a critical and challenging issue for cloud service providers. To quantify the availability of cloud services from both architectural and operational points of views, availability modeling and evaluation are essential. This paper presents a component-based availability modeling framework, named Candy, which constructs a comprehensive availability model semi-automatically from system specifications described by Systems Modeling Language (SysML). SysML diagrams are translated into components of availability model and the components are assembled together to form the entire availability model in Stochastic Reward Nets (SRNs). In order to incorporate the maintenance operations of cloud services in availability models, Candy defines the translation rules from Activity diagram to SRN and synchronizes the related SRNs according to SysML allocation notations. The feasibility of the proposed modeling and availability evaluation process is studied by an illustrative example of a web application service hosted on a cloud infrastructure having multiple failure isolation zones and automatic scale-up function.

Sensitivity Analysis of Server Virtualized System Availability

Server virtualization is a technology used in many enterprise systems to reduce operation and acquisition costs, and increase the availability of their critical services. Virtualized systems may be even more complex than traditional nonvirtualized systems; thus, the quantitative assessment of system availability is even more difficult. In this paper, we propose a sensitivity analysis approach to find the parameters that deserve more attention for improving the availability of systems. Our analysis is based on Markov reward models, and suggests that host failure rate is the most important parameter when the measure of interest is the system mean time to failure. For capacity oriented availability, the failure rate of applications was found to be another major concern. The results of both analyses were cross-validated by varying each parameter in isolation, and checking the corresponding change in the measure of interest. A cost-based optimization method helps to highlight the parameter that should have higher priority in system enhancement.

Toward optimal virtual machine placement and rejuvenation scheduling in a virtualized data center

Virtualization enables data centers to consolidate servers to improve resource utilization and power consumption. This paper presents the issues of performability management in a virtualized data center that hosts multiple services using virtualization. One of main cause of performability degradation is software aging in both virtual machines (VMs) and virtual machine monitor (VMM) in virtualized data center (VDC). Software rejuvenation is a cost effective and a proactive method to counteract software aging. During software rejuvenation operations, there occurs down time, therefore, VM placement and the rejuvenation schedules for VMs and VMM need to be optimized so as to maximize the performability in a VDC. We introduce the state of the art technology on software aging and rejuvenation in virtualized data center and we formulate this problem and show our approach.

Job completion time on a virtualized server with software rejuvenation

This article analyzes the completion time of a job running on a virtualized server subject to software aging and rejuvenation in a virtual machine monitor (VMM). A job running on the server may be interrupted by virtual machine (VM) failure, VMM failure or VMM rejuvenation. The job interruption is categorized as either preemptive-repeat (prt), in which case the interrupted job needs to restart from the beginning, or preemptive-resume (prs), in which case the job resumes execution from the point of interruption. Using a semi-Markov process (SMP) to model the server behavior, the steady-state server availability is computed and the theory developed in Kulkarni et al. [1987] is used to obtain the Laplace-Stieltjes transform (LST) of the job completion time. In the numerical experiments, we introduce four types of aging behavior of VMM. The effectiveness of VMM rejuvenation on job completion time is discussed in association with the type of interruption it causes and the VMM aging type. With our parameter settings, VMM rejuvenation with prs job interruption improves the performance of job execution regardless of the aging type, with performance degradation is taken into account.

Just-in-Time Server Provisioning Using Virtual Machine Standby and Request Prediction

Server provisioning is a practical technique to reconfigure a shared server and to improve resource utilization of servers in datacenters and enterprise systems. For the complex systems, however, long process of server provisioning impedes prompt solutions to system problems. This paper proposes a technique to shorten the provisioning processing time after the occurrence of the provisioning request by speculative provisioning execution on a virtual machine as standby. In order to start the provisioning execution in advance, a prediction method for the provisioning request is required. This paper presents a prediction model based on the logistic regression model using system performance metrics. From the evaluation using the actual performance data of enterprise systems, for 50% of the server provisioning requests, the provisioning processing time after the request is shorten over 10 minutes by using the 20-minutes look-ahead request prediction model.

On the effectiveness of Mann-Kendall test for detection of software aging

Software aging (i.e. progressive performance degradation of long-running software systems) is difficult to detect due to the long latency until it manifests during program execution. Fast and accurate detection of aging is important for eliminating the underlying defects already during software development and testing. Also in a deployment scenario, aging detection is needed to plan mitigation methods like software rejuvenation. The goal of this paper is to evaluate whether the Mann-Kendall test is an effective approach for detecting software aging from traces of computer system metrics. This technique tests for existence of monotonic trends in time series, and studies of software aging often consider existence of trends in certain metrics as indication of software aging. Through an experimental study we show that the Mann-Kendall test is highly vulnerable to creating false positives in context of aging detection. By increasing the amount of data considered in the test, the false positive rate can be reduced; however, time to detect aging increases considerably. Our findings indicate that aging detection using the Mann-Kendall test alone is in general unreliable, or may require long measurement times.

Software Life-Extension: A New Countermeasure to Software Aging

This paper presents software life-extension, a new technique for counteracting software aging by preventive operation to extend the lifetime of software execution. Software aging is a phenomenon of progressive degradation of execution environment due to aging-related software faults and it might cause resource depletion resulting in system failures. To extend the lifetime of the software affected by aging, we use a virtual machine to execute the software and allocate additional memory to the virtual machine upon software aging detection. Although software life-extension is a temporal solution as it only postpones the occurrence of a failure, it provides a simple, cost-effective, and non-intrusive countermeasure to software aging. The feasibility and effectiveness of software life-extension are studied by the experiments on memcached, a widely adopted general-purpose in-memory cache server. From the experimental results, we present a Semi-Markov process (SMP) describing the general behavior of software life-extension and analyze the model which gives the prediction of the system availability as well as the user-perceived availability.

Performance and Availability Modeling of ITSystems with Data Backup and Restore

In modern IT systems, data backup and restore operations are essential for providing protection against data loss from both natural and man-made incidents. On the other hand, data backup and restore operations can be resource-intensive and lead to performance degradation, or may require the system to be offline entirely. Therefore, it is important to properly choose backup and restore techniques and policies to ensure adequate data protection while minimizing the impact on system availability and performance. In this paper, we present an analytical modeling approach for such a purpose. We study a file service system that undergoes periodic data backups, and investigate metrics concerning system availability, data loss and rejection of user requests. To obtain the metrics, we combine a variety of model types, including Markov chains, queuing networks and Stochastic Reward Nets, to construct a set of analytical models that capture the operational details of the system. We then compute the metrics of interest under different backup/restore techniques, policies, and workload scenarios. The numerical results allow us to compare the effects of different backup/restore techniques and policies in terms of the tradeoff between protective power and impact on system performance and availability.