Review
Optimization of live virtual machine migration in cloud computing: A survey and future directions

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Abstract

In the growing age of cloud computing, shared computing and storage resources can be accessed over the Internet. Conversely, the infrastructure cost of the cloud reaches an incredible limit. Therefore, virtualization concept is applied in cloud computing systems to help users and owners to achieve better usage and efficient management of the cloud with the least cost. Live migration of virtual machines(VMs) is an essential feature of virtualization, which allows migrating VMs from one location to another without suspending VMs. This process has many advantages for data centers such as load balancing, online maintenance, power management, and proactive fault tolerance. For enhancing live migration of VMs, many optimization techniques have been applied to minimize the key performance metrics of total transferred data, total migration time and downtime. This paper provides a better understanding of live migration of virtual machines and its main approaches. Specifically, it focuses on reviewing state-of-the-art optimization techniques devoted to developing live VM migration according to memory migration. It reviews, discusses, analyzes and compares these techniques to realize their optimization and their challenges. This work also highlights the open research issues that necessitate further investigation to optimize the process of live migration for virtual machines.

Introduction

Cloud computing depends basically on a major technology called virtualization. That technology was started in the 1960s by IBM as a transparent way to provide interactive access to mainframe computers, where time-sharing and resource-sharing allow to multiple users (and applications) to use huge size and highly expensive hardware concurrently (Rose, 2004; Nanda and cker Chiueh, 2005). Nowadays, rapid technological development of processing power and storage has made computing resources more and more abundant, cheaper and powerful than before. Thus, cloud computing trend has emerged due to this development, where computing and storage resources can be delivered to multiple users over the Internet in an on-demand fashion (Zhang et al., 2010a). Therefore, modern cloud computing environments can exploit virtualization technology to increase resources utilization and reduce both computational and energy costs. Virtualization technology allows running multiple operating systems (OSs) on a single physical machine with high performance. Each OS runs on a separate Virtual Machine (VM), which is controlled by a hypervisor.

Live migration of VMs is a major advantage of virtualization, which is a powerful tool to manage cloud environment resources. A VM can be migrated seamlessly and transparently from one physical machine (source host) to another (destination host), while the VM is still running during migration. Load balancing (Wood et al., 2007) is the main benefit for live VM migration to migrate VMs from over-loaded servers to light-loaded ones to relieve loads on congested hosts. Another benefit for live VM migration is power management (Nathuji and Schwan, 2007), where VMs that run light-load jobs can be consolidated into fewer numbers of servers to minimize IT operation expenses and power consumption by shutting down some servers after migration completion from these servers. Proactive fault tolerance and online maintenance (Nagarajan et al., 2007) are also benefits for live VM migration, where VMs can be migrated to another server to be able to make some upgrade or maintenance for physical machines or to avoid expected faults before their occurrence. VM migration can also increase application performance by migrating some VMs which need more resources from their limited resources servers to rich resources ones. Today, many hypervisors support live VM migration such as Xen (Barham et al., 2003), KVM (Kivity et al., 2007), VMware (Vmware) and Microsoft Hyper-V (Microsoft).

Live migration of VMs has solved the residual dependency problem, which process migration (Milojičíč et al., 2000) suffers from. In process migration, the source host must remain available and network-accessible after process migration. In contrast, the source host can be decommissioned after VM migration. Live VM migration has become a hot research topic since its appearance (Clark et al., 2005). Thus, optimization of live VM migration has attracted the attention of academic and industrial researchers. They try to improve migration process by minimizing total data transferred, total migration time and downtime. Most of the researches focus on local area network (LAN) domain where the source machine and the destination machine are on the same LAN with almost shared storage between the source host and the destination one. Thus, their main focus is to migrate memory with minimal time and without performance disruption. VM should also retain the same IP address after migration by generating unsolicited ARP reply to advertising that the IP has moved to another location (Clark et al., 2005). There are also many researches that focus on migrating VMs in Wide Area Network (WAN) domain (Travostino et al., 2006; Bradford et al., 2007; Harney et al., 2007; Mashtizadeh et al., 2014; Arif et al., 2016), where storage is not shared and must be transferred in addition to memory. These researches use some techniques such as dynamic DNS, IP tunneling, and mobile IP.

Although many kinds of literature have been devoted to VM migration area; we focus on studying optimization techniques that have been proposed in the context of memory migration. Storage is almost shared in data centers; thereby memory migration is the main bottleneck in live VM migration due to frequent dirtying of VM memory pages during migration. Therefore, the main contribution of this article is to review existing optimization techniques in memory migration. It explores pre-copy, post-copy and hybrid approach, which are the main approaches to live migrate VMs. The key performance metrics that used to evaluate the performance of migration are presented. We discuss the manner of each technique to minimize total data transferred, total migration time or downtime. We also classify the optimization techniques into compression techniques, deduplication techniques, checkpointing techniques and other ones. Optimization techniques in each category are discussed, analyzed and compared to understand their contribution and limitation better. This survey also seeks to introduce some hot research directions that deserve more research efforts and points out to challenges of these directions. These research directions include achieving more optimization in memory migration, facing challenges of migration over WAN links, studying power cost during live VM migration, live migration of multiple VMs and studying security issues to protect the migrated VMs against attacks.

The rest of the paper is organized as follows: Section 2 explores virtualization and VM migration process. This section also discusses the two main approaches to live VM migration process, which are pre-copy and post-copy, in addition to the hybrid one. Section 3 states the key performance metrics which used to assess live VM migration techniques. Then, different optimization techniques that seek more efficient migration are discussed. Section 4 introduces research direction issues. Finally, section 5 concludes this work.

Section snippets

Background

Live VM migration process depends basically on virtualization technology. This section will first briefly overview virtualization technology. Then, we will explore the process of live VM migration and its main approaches.

Optimization techniques

Before discussing the different techniques to optimize live VM migration process, we must mention the main performance metrics which used to evaluate the performance of migration techniques. There are three major metrics, which are used in the evaluation:

  • 1.

    Total migration time: It is the duration between starting the migration process and the time when the VM is no longer available on the source host. Migration techniques seek to reduce this duration as possible.

  • 2.

    Downtime: It is defined as the

Research directions

This section refers to the main research directions in live VM migration and their challenges. These research directions include memory migration optimization which is the major bottleneck in live migrating VMs over LAN links especially when migrating VMs with memory-intensive workloads, facing challenges of migration over WAN links to achieve more optimization in the migration process, studying power cost due to live VM migration which should be small as possible, live migration of multiple

Conclusion

Live VM migration is a powerful tool that helps administrators of cloud data centers to manage their resources effectively. This paper summarized the concept of live VM migration, its advantages, and its approaches. It introduced the main performance metrics to assess live VM migration. It focused on surveying the state-of-the-art optimization techniques according to memory migration, which in general try to minimize total migration time, total data transferred and downtime. It classified the

Mostafa Noshy is a teaching assistant at Computer Engineering and Control Systems Department, Mansoura University, Egypt. He received his B.Sc. in 2014 with an overall grade of excellent with honors from Mansoura University. His research interests include cloud computing, virtualization and live virtual machine migration.

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    Mostafa Noshy is a teaching assistant at Computer Engineering and Control Systems Department, Mansoura University, Egypt. He received his B.Sc. in 2014 with an overall grade of excellent with honors from Mansoura University. His research interests include cloud computing, virtualization and live virtual machine migration.

    Abdelhameed Ibrahim was born in Mansoura city, Egypt, in 1979. He attended the Faculty of Engineering, Mansoura University, in Mansoura, where he received Bachelor and Master Degrees in Engineering from the electronics (Computer Engineering and Systems) department in 2001 and 2005, respectively. He was with the Faculty of Engineering, Mansoura University, from 2001 through 2007. In April 2007, he joined the Graduate School of Advanced Integration Science, Faculty of Engineering, Chiba University, Japan, as a doctor student. He received Ph.D. Degree in Engineering in 2011. His research interests are in the fields of computer vision and pattern recognition, with a special interest in material classification based on reflectance information.

    Hesham Arafat Ali is a Prof. in Computer Eng. & Sys.; An assoc. Prof. in Info. Sys. and computer Eng. He was assistant prof. at the Univ. of Mansoura, Faculty of Computer Science in 1997 up to 1999. From January 2000 up to September 2001, he was joined as Visiting Professor to the Department of Computer Science, University of Connecticut. From 2002 to 2004 he was a vice dean for student affair the Faculty of Computer Science and Inf., Univ. of Mansoura. He was awarded with the Highly Commended Award from Emerald Literati Club 2002 for his research on network security. He is a founder member of the IEEE SMC Society Technical Committee on Enterprise Information Systems (EIS). He has many book chapters published by international press and about 150 published papers in international (conf. and journal). He has served as a reviewer for many high quality journals, including Journal of Engineering Mansoura University. His interests are in the areas of network security, mobile agent, Network management, Search engine, pattern recognition, distributed databases, and performance analysis.

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