Control Protocol and Self-adaptive Mechanism for Live Virtual Machine Migration over XIA

Virtualization techniques effectively handle the growing demand for computing, storage, and communication resources in large-scale Cloud Data Centers (CDC). It helps to achieve different resource management objectives like load balancing, online system maintenance, proactive fault tolerance, power management, and resource sharing through Virtual Machine (VM) migration. VM migration is a resource-intensive procedure as VM’s continuously demand appropriate CPU cycles, cache memory, memory capacity, and communication bandwidth. Therefore, this process degrades the performance of running applications and adversely affects efficiency of the data centers, particularly when Service Level Agreements (SLA) and critical business objectives are to be met. Live VM migration is frequently used because it allows the availability of application service, while migration is performed. In this paper, we make an exhaustive survey of the literature on live VM migration and analyze the various proposed mechanisms. We first classify the types of Live VM migration (single, multiple and hybrid). Next, we categorize VM migration techniques based on duplication mechanisms (replication, de-duplication, redundancy, and compression) and awareness of context (dependency, soft page, dirty page, and page fault) and evaluate the various Live VM migration techniques. We discuss various performance metrics like application service downtime, total migration time and amount of data transferred. CPU, memory and storage data is transferred during the process of VM migration and we identify the category of data that needs to be transferred in each case. We present a brief discussion on security threats in live VM migration and categories them in three different classes (control plane, data plane, and migration module). We also explain the security requirements and existing solutions to mitigate possible attacks. Specific gaps are identified and the research challenges in improving the performance of live VM migration are highlighted. The significance of this work is that it presents the background of live VM migration techniques and an in depth review which will be helpful for cloud professionals and researchers to further explore the challenges and provide optimal solutions.

Impact of Factors Affecting Pre-copy Virtual Machine Migration Technique for Cloud Computing

In recent years, the adoption of multi-cloud environments has increased due to its ability to provide better performance, cost-effectiveness, and higher availability. However, managing resources in such environments is a challenging task. Load balancing and virtual machine (VM) migration are two critical techniques for resource management in multi-cloud environments. Load balancing helps to distribute the workload evenly among the cloud resources, while VM migration enables the dynamic allocation of resources based on the changing demands. This systematic review paper presents a comprehensive survey of load balancing and VM migration strategies in multi-cloud environments. The paper first introduces the concept of multicloud environments and the challenges of resource management in such environments. Then, the paper discusses the different load balancing and VM migration techniques that have been proposed for multi-cloud environments, including their advantages and limitations.

Cloud computing is a utility where compute resources are accessed on pay-per-use ground. It is enacted through virtualizationwhich is a central technology in cloud computing. Virtualization provides a secure and commendable environment for the functioning of cloud applications. Virtual machine (VM) plays a crucial role in the cloud data center when a host machine is exhausted due to tremendous network traffic, then the load is stabilized by shifting highly loaded VM to the under-utilized host machine. This review article recapitulates energy-efficient VM migration, VM migration techniques, objectives and issues related to it. The existing Swarm intelligence based VMmigration techniques are conferred and compared.

Virtualization has been shown to be an attractive path to increase overall system resource utilization. The use of live virtual machine (VM) migration has enabled more effective sharing of system resources across multiple physical servers, resulting in an increase in overall performance. Live VM migration can be used to load balance virtualized clusters. To drive live migration, we need to be able to measure the current load imbalance. Further, we also need to accurately predict the resulting load imbalance produced by any migration.In this paper we present a new metric that captures the load of the physical servers and is a function of the resident VMs. This metric will be used to measure load imbalance and construct a load-balancing VM migration framework. The algorithm for balancing the load of virtualized enterprise servers follows a greedy approach, inductively predicting which VM migration will yield the greatest improvement of the imbalance metric in a particular step. We compare our algorithm to the leading commercially available load balancing solution - VMware's Distributed Resource Scheduler (DRS). Our results show that when we are able to accurately measure system imbalance, we can also predict future system state. We find that we can outperform DRS and improve performance up to 5%. Our results show that our approach does not impose additional performance impact and is comparable to the virtual machine monitor overhead.

The article presents an efficient energy optimization framework based on dynamic resource scheduling for VM migration in cloud data centers. This increasing number of cloud data centers all over the world are consuming a vast amount of power and thus, exhaling a huge amount of CO2 that has a strong negative impact on the environment. Therefore, implementing Green cloud computing by efficient power reduction is a momentous research area. Live Virtual Machine (VM) migration, and server consolidation technology along with appropriate resource allocation of users' tasks, is particularly useful for reducing power consumption in cloud data centers. In this article, the authors propose algorithms which mainly consider live VM migration techniques for power reduction named “Power_reduction” and “VM_migration.” Moreover, the authors implement dynamic scheduling of servers based on sequential search, random search, and a maximum fairness search for convenient allocation and higher utilization of resources. The authors perform simulation work using CloudSim and the Cloudera simulator to evaluate the performance of the proposed algorithms. Results show that the proposed approaches achieve around 30% energy savings than the existing algorithms.

The rapid growth in cloud computing encourages the cloud provider to create more reliable, scalable and efficient cloud environment. For providing such a scalable environment, cloud provider develops large-scale Cloud Data Centers (CDC). Such CDCs consume a large amount of electrical energy for operational purpose and cooling purpose to keep the machines operating at a right temperature, but it also emits a large amount of carbon-dioxide. Thus to decrease the energy consumption, Virtual Machines (VMs) are consolidated to fewer numbers of active servers through VM migration techniques, this leads to Service Level Agreement (SLA) violation and performance degradation. Therefore to retain the energy-performance tradeoff, we should perform an optimum number of VM migrations. There are two cases when the VM migration performed: First when a hot spot is found and Second when a cold spot is found. But in both the cases we do not directly migrate the VM instead first we check whether it is required to migrate the VM. After that, the algorithm finds an appropriate destination host on which the VM will be migrated. In this paper, we implement three approaches to select destination host: First-fit, Best-fit, and Worst-fit. Finally compare the result of a number of VM migration performed, energy consumption and SLA violations with existing one.

Live Virtual Machine (VM) migration has significantly improved the flexibility of modern Data Centers (DC). However, seamless live migration of a VM between geo-distributed DCs faces several challenges due to difficulties in preserving the network configuration after the migration paired with a large network convergence time. Although SDN-based approaches can speed up network convergence time, these techniques have two limitations. First, they typically react to the new topology by installing new flow rules once the migration is finished. Second, because the WAN is typically not under SDN control, they result in sub-optimal routing thus severely degrading the network performance once the VM is attached at the new location. In this paper, we identify networking challenges for VM migration across geo-distributed DCs. Based on those observations, we design a novel long-haul VM migration scheme that overcomes those limitations. First, instead of reactively restoring connectivity after the migration, our SDN-based approach proactively restores flows across the WAN towards the new location with the help of EVPN and VXLAN overlay technologies. Second, the SDN controller accelerates the network convergence by announcing the migration to other controllers using MP-BGP control plane messages. Finally, the SDN controller resolves the sub-optimal routing problem that arises as a result of migration implementing a distributed anycast gateway. We implement our approach as extensions to the OpenDaylight controller. Our evaluation shows that our approach outperforms existing approaches in reducing the downtime by 400 ms and increasing the application performance up to 12 times.

With the consistent evolution of distributed networks and cloud computing, the communication process of existing Internet architecture are not at par to offer comprehensive security; thereby fails to cater up the dynamic web security demands of online users. This leads to the evolution of Future Internet Architecture (FIA) that claims of enhanced security system. However, a closer look into both existing web security and security of existing FIA projects shows that there are enough security loopholes in both that demands a novel security solution. Therefore, this paper contributes to investigate the effectiveness of existing web security approaches as well as security approaches of FIA in order to explore the open research issues. The finding of the study shows that there is a significant research gap that demands extreme improvement of existing web security in order to fit for secure communication in FIA.

Virtual machine (VM) migration is a technique for transferring the execution state of a VM from one physical host to another. While VM migration is critical for load balancing, consolidation, and server maintenance in virtualized data centers, it can also increase security risks. During VM migration, an attacker with sufficient privileges can compromise a VM by modifying its memory contents during transit to subvert its applications or the guest operating system. One could maintain dedicated, and presumably more secure, control networks to carry the migration traffic, but at significant hardware and administrative complexity. Alternatively, one could encrypt the migration traffic, which eliminates the need for dedicated control networks, but might introduce performance overheads. To date, there has been no systematic study of how encryption affects VM migration, especially in high-bandwidth low-delay networks that are common within data centers. In this paper, we present a study of the impact of AES and 3DES encryption algorithms on two widely used live VM migration approaches -- pre-copy and post-copy. Our key findings are as follows. The encryption algorithm used can have a significant impact on the total migration time. The impact of encryption on downtime varies with the type of the migration technique. The overhead of encryption also depends upon the relative speeds of source and target machines. Finally, an application's performance within a VM during encrypted migration varies with the type of the application and the migration mechanism.

Migration is one of the useful techniques that is used in cloud computing. This technique has been used by different purposes such as load balancing, fault tolerance, power management, reducing response time and increasing quality of service. Because the use of this technique is highly dependent on cloud computing infrastructure architecture, in some cloud infrastructures, such as Eucalyptus, the virtual machine migration technique has not been used yet. In this paper, we describe important challenges that are prevent to implementing migration technique in Eucalyptus, and then we propose a solution for overcome to these challenges. Through using the solution, we provided the field with further development and empowerment of the cloud environment.

CBase: Fast Virtual Machine storage data migration with a new data center structure

Future Internet is a general term that is used to refer to the study of new Internet architectures that emphasize the advancements that are paving the way for the next generation of internet. Today’s internet has become more complicated and arduous to manage due to its increased traffic. This traffic is a result of the transfer of 247 billion emails, the management of more than a billion websites and 735 active top-level domains, the viewing of at least one billion YouTube videos per day (which is the source of main traffic), and the uploading of more than 2.5 billion photos to Facebook every year. The internet was never anticipated to provide quality of service (QoS) support, but one can have a best effort service that provides support for video streams and downloaded media applications. Therefore, the future architecture of the internet becomes crucial. Furthermore, the internet as a service has witnessed many evolving conflicts among its stakeholders, leading to extensive research. This article presents a systematic review of the internet’s evolution and discusses the ongoing research efforts towards new internet architectures, as well as the challenges that are faced in increasing the network’s performance and quality. Moreover, as part of these anticipated future developments, this article draws attention to the Metaverse, which combines the emerging areas of augmented reality, virtual reality, mixed reality, and extended reality, and is considered to be the next frontier for the future internet. This article examines the key role of the blockchain in organizing and advancing the applications and services within the Metaverse. It also discusses the potential benefits and challenges of future internet research. Finally, the article outlines certain directions for future internet research, particularly in the context of utilizing blockchains in the Metaverse.

A Service Sustainable Live Migration Strategy for Multiple Virtual Machines in Cloud Data Centers

Virtualization is the key technology running behind the cloud servers to deploy users services efficiently. So, when a user requests for cloud services, resources are allocated in the form of VM instance. With the tremendous growth in cloud services, the number of applications running over cloud servers is increasing. Therefore, the chances of server overloading and maintenance are quite often. This scenario is handled by live VM migration, that allows migration of VMs from one host to another with minimum disruption to cloud user services. Cloud hypervisors use pre-copy technique to perform the VM migration task. However, it suffers from page-level content redundancy problem, where complete VM memory page is transferred instead of modified contents of the page. Therefore, a technique is proposed which transfers only modified contents of VM memory page. The performance of proposed technique is evaluated with VMs running read-and write-intensive workloads configured on QEMU-KVM virtualized environment. The results obtained demonstrate that for read-intensive workload, compared to existing pre-copy VM migration scheme, our proposed technique minimize downtime by 69.4%, migration time by 73.5%, and reduces network traffic generated by 74.21%. Similarly, for write-intensive workload, downtime, migration time, and network traffic generated are reduced by 47.23, 49.16, and 51.37%. Thus, the proposed technique effectively improves the performance of VM migration scheme.