A Survey of Virtual Machine Migration Techniques in Cloud Computing

Cloud computing is an emerging computing technology that maintains computational resources on large data centers and accessed through internet, rather than on local computers. VM migration provides the capability to balance the load, system maintenance, etc. Virtualization technology gives power to cloud computing. The virtual machine migration techniques can be divided into two categories that is pre-copy and post-copy approach. The process to move running applications or VMs from one physical machine to another, is known as VM migration. In migration process the processor state, storage, memory and network connection are moved from one host to another.. Two important performance metrics are downtime and total migration time that the users care about most, because these metrics deals with service degradation and the time during which the service is unavailable. This paper focus on the analysis of live VM migration Techniques in cloud computing. Keywords: Cloud Computing, Virtualization, Virtual Machine, Live Virtual Machine Migration.

Zeroing memory deallocator to reduce checkpoint sizes in virtualized HPC environments

Virtualization has become an indispensable tool in data centers and cloud environments to flexibly assign virtual machines (VMs) to resources. Virtualization also becomes more and more attractive for high-performance computing (HPC). This is mainly due to the strong isolation of VMs which enables: (1) the sharing of cluster nodes and optimization of the system’s overall utilization; (2) load balancing by means of migrations due to the reduction of residual dependencies; and (3) the creation of system-level checkpoints increasing the fault tolerance in an application-transparent way. On the downside, the additional virtualization layer conceals information that is only available on the process level. This information has a direct influence on the checkpoint size which should be kept as small as possible. In this paper, we propose a novel technique for checkpoint size reduction in virtualized environments. We exploit the fact that the hypervisor detects zero pages which are omitted when capturing a checkpoint. Moreover, compression techniques are applied for a further reduction of the checkpoint size. We therefore fill freed memory regions with zeros supporting both the zero-page detection and the compression. We evaluate our approach by taking the example of HPC applications. The results reveal a reduction of the checkpoint size by up to 9% when compression is disabled in the hypervisor and up to 49% with compression enabled. Furthermore, memory zeroing is able to reduce VM migration time by up to 10% when compression is disabled and by up to 60% when compression is enabled

SimGrid VM: Virtual Machine Support for a Simulation Framework of Distributed Systems

International audienceAs real systems become larger and more complex, the use of simulator frameworks grows in our research community. By leveraging them, users can focus on the major aspects of their algorithm, run in-siclo experiments (i.e., simulations), and thoroughly analyze results, even for a large-scale environment without facing the complexity of conducting in-vivo studies (i.e., on real testbeds). Since nowadays the virtual machine (VM) technology has become a fundamental building block of distributed computing environments, in particular in cloud infrastructures, our community needs a full-fledged simulation framework that enables us to investigate large-scale virtualized environments through accurate simulations. To be adopted, such a framework should provide easy-to-use APIs as well as accurate simulation results. In this paper, we present a highly-scalable and versatile simulation framework supporting VM environments. By leveraging SimGrid, a widely-used open-source simulation toolkit, our simulation framework allows users to launch hundreds of thousands of VMs on their simulation programs and control VMs in the same manner as in the real world (e.g., suspend/resume and migrate). Users can execute computation and communication tasks on physical machines (PMs) and VMs through the same SimGrid API, which will provide a seamless migration path to IaaS simulations for hundreds of SimGrid users. Moreover, SimGrid VM includes a live migration model implementing the precopy migration algorithm. This model correctly calculates the migration time as well as the migration traffic, taking account of resource contention caused by other computations and data exchanges within the whole system. This allows user to obtain accurate results of dynamic virtualized systems. We confirmed accuracy of both the VM and the live migration models by conducting several micro-benchmarks under various conditions. Finally, we conclude the article by presenting a first use-case of one consolidation algorithm dealing with a significant number of VMs/PMs. In addition to confirming the accuracy and scalability of our framework, this first scenario illustrates the main interest of SimGrid VM: investigating through in-siclo experiments pros/cons of new algorithms in order to limit expensive in-vivo experiments only to the most promising ones

Doctor of Philosophy

dissertationAs the base of the software stack, system-level software is expected to provide ecient and scalable storage, communication, security and resource management functionalities. However, there are many computationally expensive functionalities at the system level, such as encryption, packet inspection, and error correction. All of these require substantial computing power. What's more, today's application workloads have entered gigabyte and terabyte scales, which demand even more computing power. To solve the rapidly increased computing power demand at the system level, this dissertation proposes using parallel graphics pro- cessing units (GPUs) in system software. GPUs excel at parallel computing, and also have a much faster development trend in parallel performance than central processing units (CPUs). However, system-level software has been originally designed to be latency-oriented. GPUs are designed for long-running computation and large-scale data processing, which are throughput-oriented. Such mismatch makes it dicult to t the system-level software with the GPUs. This dissertation presents generic principles of system-level GPU computing developed during the process of creating our two general frameworks for integrating GPU computing in storage and network packet processing. The principles are generic design techniques and abstractions to deal with common system-level GPU computing challenges. Those principles have been evaluated in concrete cases including storage and network packet processing applications that have been augmented with GPU computing. The signicant performance improvement found in the evaluation shows the eectiveness and eciency of the proposed techniques and abstractions. This dissertation also presents a literature survey of the relatively young system-level GPU computing area, to introduce the state of the art in both applications and techniques, and also their future potentials

User-activity aware strategies for mobile information access

Information access suffers tremendously in wireless networks because of the low correlation between content transferred across low-bandwidth wireless links and actual data used to serve user requests. As a result, conventional content access mechanisms face such problems as unnecessary bandwidth consumption and large response times, and users experience significant performance degradation. In this dissertation, we analyze the cause of those problems and find that the major reason for inefficient information access in wireless networks is the absence of any user-activity awareness in current mechanisms. To solve these problems, we propose three user-activity aware strategies for mobile information access. Through simulations and implementations, we show that our strategies can outperform conventional information access schemes in terms of bandwidth consumption and user-perceived response times.Ph.D.Committee Chair: Raghupathy Sivakumar; Committee Member: Chuanyi Ji; Committee Member: George Riley; Committee Member: Magnus Egerstedt; Committee Member: Umakishore Ramachandra

Memory Page Stability and its Application to Memory Deduplication

In virtualized environments, typically cloud computing environments, multiple virtual machines run on the same physical host. These virtual machines usually run the same operating systems and applications. This results in a lot of duplicate data blocks in memory. Memory deduplication is a memory optimization technique that attempts to remove this redundancy by storing one copy of these duplicate blocks in the machine memory which in turn results in a better utilization of the available memory capacity.In this dissertation, we characterize the nature of memory pages that contribute to memory deduplication techniques. We show how such characterization can give useful insights towards better design and implementation of software and hardware-assisted memory deduplication systems. In addition, we also quantify the performance impact of different memory deduplication techniques and show that even though memory deduplication allows for a better cache hierarchy performance, there is a performance overhead associated with copy-on-write exceptions that is associated with diverging pages.We propose a generic prediction framework that is capable of predicting the stability of memory pages based on the page flags available through the Linux kernel. We evaluate the proposed prediction framework and then discuss various applications that can benefit from it, specifically memory deduplication and live migration

Live migration of user environments across wide area networks

A complex challenge in mobile computing is to allow the user to migrate her highly customised environment while moving to a different location and to continue work without interruption. I motivate why this is a highly desirable capability and conduct a survey of the current approaches towards this goal and explain their limitations. I then propose a new architecture to support user mobility by live migration of a user’s operating system instance over the network. Previous work includes the Collective and Internet Suspend/Resume projects that have addressed migration of a user’s environment by suspending the running state and resuming it at a later time. In contrast to previous work, this work addresses live migration of a user’s operating system instance across wide area links. Live migration is done by performing most of the migration while the operating system is still running, achieving very little downtime and preserving all network connectivity. I developed an initial proof of concept of this solution. It relies on migrating whole operating systems using the Xen virtual machine and provides a way to perform live migration of persistent storage as well as the network connections across subnets. These challenges have not been addressed previously in this scenario. In a virtual machine environment, persistent storage is provided by virtual block devices. The architecture supports decentralized virtual block device replication across wide area network links, as well as migrating network connection across subnetworks using the Host Identity Protocol. The proposed architecture is compared against existing solutions and an initial performance evaluation of the prototype implementation is presented, showing that such a solution is a promising step towards true seamless mobility of fully fledged computing environments

Effectiveness of Cloud Services for Scientific and VoD Applications

Cloud platforms have emerged as the primary data warehouse for a variety of applications, such as DropBox, iCloud, Google Music, etc. These applications allow users to store data in the cloud and access it from anywhere in the world. Commercial clouds are also well suited for providing high-end servers for rent to execute applications that require computation resources sporadically. Cloud users only pay for the time they actually use the hardware and the amount of data that is transmitted to and from the cloud, which has the potential to be more cost effective than purchasing, hosting, and maintaining dedicated hardware. In this dissertation, we look into the efficiency of the cloud Infrastructure-as-a-Service (IaaS) model for two real time high bandwidth applications: A scientific application of short-term weather forecasting and Video on Demand services. We show that, cloud services are efficient in both network and computation for real time scientific application of weather forecasting. We present a related list reordering approach, which reduces the network traffic of serving videos from VoD services and improve the efficiency of caches deployed to serve them. Also, we present transcoding policies to reduce the transcoding workload and present prediction models to maintain performance of providing ABR streaming of VoD services at the client with online transcoding in the cloud

On the performance of QUIC over wireless mesh networks

The exponential growth in adoption of mobile phones and the widespread availability of wireless networks has caused a paradigm shift in the way we access the Internet. It has not only eased access to the Internet, but also increased users’ appetite for responsive services. New protocols to speed up Internet applications have naturally emerged. The QUIC transport protocol is one prominent case. Initially developed by Google as an experiment, the protocol has already made phenomenal strides, thanks to its support in Google’s servers and Chrome browser. Since QUIC is still a relatively new protocol, there is a lack of sufficient understanding about its behavior in real network scenarios, particularly in the case of wireless networks. In this paper we present a comprehensive study on the performance of QUIC in Wireless Mesh Networks (WMN). We perform a measurement campaign on a production WMN to compare the performance of QUIC against TCP when retrieving files from the Internet. Our results show that while QUIC outperforms TCP in wired networks, it exhibits significantly lower performance than TCP in the WMN. We investigate the reasons for this behavior and identify the root causes of the performance issues. We find that some design choices of QUIC may penalize the protocol in WiFi, e.g., uncovering sub-optimal interactions of QUIC with MAC layer features, such as frame aggregation. Finally, we implement and evaluate our solution and demonstrate up to 28% increase in throughput of QUIC.This work was supported by the Erasmus Mundus Joint Doctorate in Distributed Computing EMJD-DC program, the Spanish grant TIN2016-77836-C2-2-R, and Generalitat de Catalunya through 2017-SGR-990. This research was conducted as part of the PhD thesis which is available online at upcommons.upc.edu.Peer ReviewedPostprint (author's final draft