Storage Deduplication and Management for Application Testing over a Virtual Network Testbed

The virtual machine technology as new teaching aids in the teaching of computer network security has very good application prospect. At the same time, the virtual machine technology is adopted to simulate the real network teaching environment and improve teachers' teaching effect and has become a kind of effective means to ensure the quality of teaching. The virtual machine technology is adopted to enhance the teaching effect of Network Security. The installation and use of the virtual machine software VMware,setting a virtual network environment on single computer, and simulating attacks and defense on network safety, the teaching effect in both theory and practice teaching is promoted.The virtual machine technology application in computer network has very broad prospects.

Virtual machine (VM) technologies offer lots of benefits such as users' isolation, server consolidation and live migration. However, owing to the overhead incurred by indirect access to physical resources such as GPU, IO devices and VM technologies have not been widely used in high performance computing area. General purpose graphics processing unit (GPGPU) computing solution for virtual machines makes it possible that high performance computing (HPC) applications running on GPU can be ported to virtual machines (VMs) environment. A novel GPU resources management system built on VMs called VMGPURMS and a novel GPU cluster schedule policy are presented to use VM as computing node, and enable users to run jobs in the whole virtual machine environment transparently. Evaluation demonstrates that the efficiency of GPUs with the GPU cluster schedule policy could be improved by 17% over the traditional cluster schedule policy without taking GPU into consideration.

This study aims to explore the application of Virtual Reality (VR) and virtual machine technology in the restoration of ancient books, and to compare these methods with traditional restoration techniques. By elucidating the current status of ancient book restoration and the evolution of relevant technologies, the study identifies both the challenges and opportunities for cultural heritage preservation in the digital age. Additionally, the study introduces examples of virtual machine technology applications in data backup, restoration environment simulation, and cross-platform compatibility. Through case comparison analysis, the study comprehensively evaluates traditional and new technologies in terms of restoration quality, speed, and reliability. Furthermore, a cost-benefit analysis was conducted, considering labor, materials, and technology costs. The research results indicate that VR and virtual machine technology have significant advantages in enhancing restoration efficiency, reducing risks, and improving restoration accuracy. Lastly, the study anticipates future trends in restoration technology development and the potential for multi-technology integration, suggesting that intelligent and standardized approaches are crucial directions for future cultural heritage preservation.

Simulation is a common approach for assisting system design and optimization. For system-wide optimization, energy and computational resources are often the two most critical limitations. Modeling energy-states of each hardware component and time spent in each state is needed for accurate energy and performance prediction. Tracking software execution in a realistic operating environment with properly modeled input/output is key to accurate prediction. However, the conventional approaches can have difficulties in practice. First, for a complex system such as an Android smartphone, building a cycle-accurate simulation environment is no easy task. Secondly, for I/O-intensive applications, a slow simulation would significantly alter the application behavior and change its performance profile. Thirdly, conventional software profiling tools generally do not work on simulators, which makes it difficult for performance analysis of complicated software, e.g., Java applications executed by the Dalvik virtual machine. Recently, virtual machine technologies are widely used to emulate a variety of computer systems. While virtual machines do not model the hardware components in the emulated system, we can ease the effort of building a simulation environment by leveraging the infrastructure of virtual machines and adding performance and power models. Moreover, multiple sets of the performance and energy models can be selectively used to verify if the speed of the simulated system impacts the software behavior. Finally, performance monitoring facilities can be integrated to work with profiling tools. We believe this approach should help overcome the aforementioned difficulties. We have prototyped a framework and our case studies showed that the information provided by our tools are useful for software optimization and system design for Android smartphones.

In this paper, we investigate the benefits that organisations can reap by using "Cloud Computing" providers to augment the computing capacity of their local infrastructure. We evaluate the cost of seven scheduling strategies used by an organisation that operates a cluster managed by virtual machine technology and seeks to utilise resources from a remote Infrastructure as a Service (IaaS) provider to reduce the response time of its user requests. Requests for virtual machines are submitted to the organisation's cluster, but additional virtual machines are instantiated in the remote provider and added to the local cluster when there are insufficient resources to serve the users' requests. Naive scheduling strategies can have a great impact on the amount paid by the organisation for using the remote resources, potentially increasing the overall cost with the use of IaaS. Therefore, in this work we investigate seven scheduling strategies that consider the use of resources from the "Cloud", to understand how these strategies achieve a balance between performance and usage cost, and how much they improve the requests' response times.

Virtual machine technology and the ease with which VMs can be migrated within the LAN, has changed the scope of resource management from allocating resources on a single server to manipulating pools of resources within a data center. We expect WAN migration of virtual machines to likewise transform the scope of provisioning compute resources from a single data center to multiple data centers spread across the country or around the world. In this paper we present the CloudNet architecure as a cloud framework consisting of cloud computing platforms linked with a VPN based network infrastructure to provide seamless and secure connectivity between enterprise and cloud data center sites. To realize our vision of efficiently pooling geographically distributed data center resources, CloudNet provides optimized support for live WAN migration of virtual machines. Specifically, we present a set of optimizations that minimize the cost of transferring storage and virtual machine memory during migrations over low bandwidth and high latency Internet links. We evaluate our system on an operational cloud platform distributed across the continental US. During simultaneous migrations of four VMs between data centers in Texas and Illinois, CloudNet's optimizations reduce memory migration time by 65% and lower bandwidth consumption for the storage and memory transfer by 19GB, a 50% reduction.

Increasing the accuracy of the portrayal of all of the elements of a simulation environment has long been a prime goal of the modeling and simulation community; a goal that has remained far out of reach for many reasons. One of the greatest hurdles facing simulation developers in the effort to increase simulation accuracy is the need to segregate information across the entire simulation environment according to access restrictions in order to insure the integrity, security, and reliability requirements imposed on the data. However, this need for segregation does not mean that those with the highest access permissions should be forced to use multiple computers and displays to integrate the information that they need or that intelligent agents should be restricted in their access to the information that they need in order to adequately assist their human operators. In this paper, we present a potential solution to the problem of integrating and segregating data, which is the use of virtual machine and virtual private network technology in order to maintain segregation of data, control access, and control intercommunication.

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

In mobile ad hoc networks (MANETs), authentication is a critical issue. It is a tough task to provide security and authentication in MANETs due to the absence of any centralized administration and dynamic topology of the network. This paper presents a robust and secure mechanism for authentication of nodes in the MANET. The proposed authentication protocol is based on certificate exchange between the nodes. This protocol also uses digital signature with a hash function to maintain the authenticity of certificates. Simulation shows that this protocol shows better performance in terms of throughput, end-to-end delay and packet dropping in presence of malicious nodes in the MANET. In addition, it also has less computation and communication overhead, which makes it suitable for MANETs.

Scalable, highly reliable distributed systems supporting data deduplication have recently become popular for storing backup and archival data. One of the important requirements for backup storage is the ability to delete data selectively. Unlike in traditional storage systems, data deletion in distributed systems with deduplication is a major challenge because deduplication leads to multiple owners of data chunks. Moreover, system configuration changes often due to node additions, deletions and failures. Expected high performance, high availability and low impact of deletion on regular user operations additionally complicate identification and reclamation of unnecessary blocks.This paper describes a deletion algorithm for a scalable, content-addressable storage with global deduplication. The deletion is concurrent: user reads and writes can proceed in parallel with deletion with only minor restrictions established to make reclamation feasible. Moreover, our approach allows for deduplication of user writes during deletion. We extend traditional distributed reference counting to deliver a failure-tolerant deletion that accommodates not only deduplication, but also the dynamic nature of a scalable system and its physical resource constraints. The proposed algorithm has been verified with an implementation in a commercial deduplicating storage system. The impact of deletion on user operations is configurable. Using a default setting that grants deletion maximum 30% of system resources running the deletion reduces end performance by not more that 30%. This impact can be reduced to less than 5% when deletion is given only minimal resources.

Network intrusions become a signification threat to network servers and its availability. A simple intrusion can suspend the organization's network services and can lead to a financial disaster. In this paper, we propose a framework called TimeVM to mitigate, or even eliminate, the infection of a network intrusion on-line as fast as possible. The framework is based on the virtual machine technology and traffic-replay-based recovery. TimeVM gives the illusion of machine. TimeVM logs only the network traffic to a server and replays the logged traffic to multiple shadow virtual machines (Shadow VM) after different time delays (time lags). Consequently, each Shadow VM will represent the server at different time in history. When attack/infection is detected, TimeVM enables navigating through the traffic history (logs), picking uninfected Shadow VM, removing the attack traffic, and then fast-replaying the entire traffic history to this Shadow VM. As a result, a typical up-to-date uninfected version of the original system can be constructed.The paper shows the implementation details for TimeVM. It also addresses many practical challenges related to how to configure and deploy TimeVM in a system in order to minimize the recovery time. We present analytical framework and extensive evaluation to validate our approach in different environments.

Honeynet is a framework containing more than one honeypot to provide data control, data capture, and data analysis. This framework aims to simulate a highly controllable attack or decoy for the security analysis of a network. In this paper, the Xen-based virtual machine solution is proposed to build the virtual honeynet. A virtual honeynet deploys a honeynet on a physical machine based on virtual machine technology with the advantages of low cost as well as convenient management, and maintenance features. The virtual honeynet system includes dynamic resource allocation, data control, data capture, data presentation, and analysis. It is lightweight but has high performance, which is verified with extensive experiments.

As 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.

Virtual machine technology is rapidly gaining acceptance as a fundamental building block in enterprise data centers. It is most known for improving efficiency and ease of management. However, it also provides a compelling approach to enhancing system security, offering new ways to rearchitect todays systems and opening the door for a wide range of future security technologies. While this technology is meant to enhance the security of computer systems, some recent attacks show that virtual machine technology has many weaknesses and becomes exposed to many security threats. In this paper we present some of these threats and show how we protect these systems through intrusion detection and security policies mechanisms.

The programming foundation course which based on Python has become an important basic course for different disciplines in universities. In experimental teaching, the main difficulty is the environment configuration and rapid deployment of Python. Virtualization technology is a common method to solve this problem. However, there are some problems, such as low resource utilization, insufficient support for concurrent, slow start, and so on. So, a new method for constructing the teaching experiment platform of the course using Docker container technology is proposed. This method can quickly realize the dynamic allocation, deployment and management of the running environment image according to the needs of students. Experimental results show that this method has obvious advantages in terms of resource utilization, concurrent users, response time, construction cost and so on, compared with virtual machine technology