Virtual Machines and Networks - Installation, Performance Study, Advantages and Virtualization Options

The interest in virtualization has been growing rapidly in the IT industry because of inherent benefits like better resource utilization and ease of system manageability. The experimentation and use of virtualization as well as the simultaneous deployment of virtual software are increasingly getting popular and in use by educational institutions for research and teaching. This paper stresses on the potential advantages associated with virtualization and the use of virtual machines for scenarios, which cannot be easily implemented and/or studied in a traditional academic network environment, but need to be explored and experimented by students to meet the raising needs and knowledge-base demanded by the IT industry. In this context, we discuss various aspects of virtualization - starting from the working principle of virtual machines, installation procedure for a virtual guest operating system on a physical host operating system, virtualization options and a performance study measuring the throughput obtained on a network of virtual machines and physical host machines. In addition, the paper extensively evaluates the use of virtual machines and virtual networks in an academic environment and also specifically discusses sample projects on network security, which may not be feasible enough to be conducted in a physical network of personal computers; but could be conducted only using virtual machines

Virtual numbers for virtual machines?

Knowing the number of virtual machines (VMs) that a cloud physical hardware can (further) support is critical as it has implications on provisioning and hardware procurement. However, current methods for estimating the maximum number of VMs possible on a given hardware is usually the ratio of the specifications of a VM to the underlying cloud hardware’s specifications. Such naive and linear estimation methods mostly yield impractical limits as to how many VMs the hardware can actually support. It was found that if we base on the naive division method, user experience on VMs at those limits would be severely degraded. In this paper, we demonstrate through experimental results, the significant gap between the limits derived using the estimation method mentioned above and the actual situation. We believe for a more practicable estimation of the limits of the underlying infrastructure

Server Placement with Shared Backups for Disaster-Resilient Clouds

A key strategy to build disaster-resilient clouds is to employ backups of virtual machines in a geo-distributed infrastructure. Today, the continuous and acknowledged replication of virtual machines in different servers is a service provided by different hypervisors. This strategy guarantees that the virtual machines will have no loss of disk and memory content if a disaster occurs, at a cost of strict bandwidth and latency requirements. Considering this kind of service, in this work, we propose an optimization problem to place servers in a wide area network. The goal is to guarantee that backup machines do not fail at the same time as their primary counterparts. In addition, by using virtualization, we also aim to reduce the amount of backup servers required. The optimal results, achieved in real topologies, reduce the number of backup servers by at least 40%. Moreover, this work highlights several characteristics of the backup service according to the employed network, such as the fulfillment of latency requirements.Comment: Computer Networks 201

Optimal Placement Algorithms for Virtual Machines

Cloud computing provides a computing platform for the users to meet their demands in an efficient, cost-effective way. Virtualization technologies are used in the clouds to aid the efficient usage of hardware. Virtual machines (VMs) are utilized to satisfy the user needs and are placed on physical machines (PMs) of the cloud for effective usage of hardware resources and electricity in the cloud. Optimizing the number of PMs used helps in cutting down the power consumption by a substantial amount. In this paper, we present an optimal technique to map virtual machines to physical machines (nodes) such that the number of required nodes is minimized. We provide two approaches based on linear programming and quadratic programming techniques that significantly improve over the existing theoretical bounds and efficiently solve the problem of virtual machine (VM) placement in data centers

Research and design of corporate networks infrastructure using SDN technologies with emphasis to virtual switch

Software Defined Networking has brought revolution to the world of Network technology which replaces most of the physical devices and control layer of the cloud computing reference model takes control of many Networking Devices. A Virtual Switch is a software by the virtue of which communication between several virtual machines take place. In contrast to physical switch is, it does not only forwards data packets but also checks the data for security before it is forwarded to other virtual machines. Interrelated components of software components work together to form a virtual network infrastructure. Out of the software components, the emphasis is targeted on Virtual switch functions and how it differs from the traditional switches

Virtual qubits, virtual temperatures, and the foundations of thermodynamics

We argue that thermal machines can be understood from the perspective of `virtual qubits' at `virtual temperatures': The relevant way to view the two heat baths which drive a thermal machine is as a composite system. Virtual qubits are two-level subsystems of this composite, and their virtual temperatures can take on any value, positive or negative. Thermal machines act upon an external system by placing it in thermal contact with a well-selected range of virtual qubits and temperatures. We demonstrate these claims by studying the smallest thermal machines. We show further that this perspective provides a powerful way to view thermodynamics, by analysing a number of phenomena. This includes approaching Carnot efficiency (where we find that all machines do so essentially by becoming equivalent to the smallest thermal machines), entropy production in irreversible machines, and a way to view work in terms of negative temperature and population inversion. Moreover we introduce the idea of "genuine" thermal machines and are led to considering the concept of "strength" of work.Comment: v2: Published version. 15 pages, 8 figure