Explore the vast range of titles available.

Learn virtualization skills by building your own virtual machine Virtualization Essentials, Second Edition provides new and aspiring IT professionals with immersive training in working with virtualization environments. Clear, straightforward discussion simplifies complex concepts, and the hands-on tutorial approach helps you quickly get up to speed on the fundamentals. You'll begin by learning what virtualization is and how it works within the computing environment, then you'll dive right into building your own virtual machine. You'll learn how to set up the CPU, memory, storage, networking, and more as you master the skills that put you in-demand on the job market. Each chapter focuses on a specific goal, and concludes with review questions that test your understanding as well as suggested exercises that help you reinforce what you've learned. As more and more companies are leveraging virtualization, it's imperative that IT professionals have the skills and knowledge to interface with virtualization-centric infrastructures. This book takes a learning-by-doing approach to give you hands-on training and a core understanding of virtualization. Understand how virtualization works Create a virtual machine by scratch and migration Configure and manage basic components and supporting devices Develop the necessary skill set to work in today's virtual world Virtualization was initially used to build test labs, but its use has expanded to become best practice for a tremendous variety of IT solutions including high availability, business continuity, dynamic IT, and more. Cloud computing and DevOps rely on virtualization technologies, and the exponential spread of these and similar applications make virtualization proficiency a major value-add for any IT professional. Virtualization Essentials, Second Edition provides accessible, user-friendly, informative virtualization training for the forward-looking pro.

Xen, the open source virtualization tool, is a system administrator's dream. Xen is a free, high-performance virtual machine monitor that lets you consolidate your hardware and finally put those unused cycles to use—without sacrificing reliability, performance, or scalability. The Book of Xen explains everything you need to know in order to use Xen effectively, including installation, networking, memory management, and virtualized storage. You'll also learn how to use Xen and standard Linux tools to take snapshot backups, perform QoS operations on network traffic, and limit over-aggressive disk users. Authors Chris Takemura and Luke S. Crawford show you how to: Provide virtual hosting for dozens of users, each with their own individual needs Install and manage multiple guests, including various flavors of Linux, NetBSD, Solaris, and Windows Choose the right virtual storage options for your needs Migrate your systems seamlessly and create new images Tune and benchmark your systems to make them as fast as possible Troubleshoot Xen's most common problems like network and memory management Expert advice is priceless when it comes to running a complicated open source virtualization technology like Xen. You'll get the advice you need in The Book of Xen .

In audio transduction applications, virtualization can be defined as the task of digitally altering the acoustic behavior of an audio sensor or actuator with the aim of mimicking that of a target transducer. Recently, a digital signal preprocessing method for the virtualization of loudspeakers based on inverse equivalent circuit modeling has been proposed. The method applies Leuciuc’s inversion theorem to obtain the inverse circuital model of the physical actuator, which is then exploited to impose a target behavior through the so called Direct–Inverse–Direct Chain. The inverse model is designed by properly augmenting the direct model with a theoretical two-port circuit element called nullor. Drawing on this promising results, in this manuscript, we aim at describing the virtualization task in a broader sense, including both actuator and sensor virtualizations. We provide ready-to-use schemes and block diagrams which apply to all the possible combinations of input and output variables. We then analyze and formalize different versions of the Direct–Inverse–Direct Chain describing how the method changes when applied to sensors and actuators. Finally, we provide examples of applications considering the virtualization of a capacitive microphone and a nonlinear compression driver.

With the proliferation of mobile demands and increasingly multifarious services and applications, mobile Internet has been an irreversible trend. Unfortunately, the current mobile and wireless network (MWN) faces a series of pressing challenges caused by the inherent design. In this paper, we extend two latest and promising innovations of Internet, software-defined networking and network virtualization, to mobile and wireless scenarios. We first describe the challenges and expectations of MWN, and analyze the opportunities provided by the software-defined wireless network (SDWN) and wireless network virtualization (WNV). Then, this paper focuses on SDWN and WNV by presenting the main ideas, advantages, ongoing researches and key technologies, and open issues respectively. Moreover, we interpret that these two technologies highly complement each other, and further investigate efficient joint design between them. This paper confirms that SDWN and WNV may efficiently address the crucial challenges of MWN and significantly benefit the future mobile and wireless network.

Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Moreover, NFV plays a crucial role in sensor and IoT networks by ensuring optimal resource usage and effective network management. However, adopting NFV in these networks also brings security challenges that must promptly and effectively address. This survey paper focuses on exploring the security challenges associated with NFV. It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. The research evaluates the strengths and weaknesses of various machine learning-based algorithms for detecting network-based anomalies in NFV networks. By providing insights into the most efficient algorithm for timely and effective anomaly detection in NFV networks, this study aims to assist network administrators and security professionals in enhancing the security of NFV deployments, thus safeguarding the integrity and performance of sensors and IoT systems.

Within the dynamic landscape of fifth-generation (5G) and emerging sixth-generation (6G) wireless networks, the adoption of network slicing has revolutionized telecommunications by enabling flexible and efficient resource allocation. However, this advancement introduces new security challenges, as traditional protection mechanisms struggle to address the dynamic and complex nature of sliced network environments. This study proposes a Hybrid Security Framework Using Cross-Layer Integration, combining Software-Defined Networking (SDN), Network Function Virtualization (NFV), and AI-driven anomaly detection to strengthen network defenses. By integrating security mechanisms across multiple layers, the framework effectively mitigates threats, ensuring the integrity and confidentiality of network slices. An implementation was developed, focusing on the AI-based detection process using a representative 5G security dataset. The results demonstrate promising detection accuracy and real-time response capabilities. While full SDN/NFV integration remains under development, these findings lay the groundwork for scalable, intelligent security architectures tailored to the evolving needs of next-generation networks.

Originality value: The following groups should be interested in the research results: 1) musical arts creators to develop or structure their perception of the creative process; 2) musical art managers to develop or structure their perception of the complex nature of the creative process of musical art groups they manage; 3) musical art institutions' managers to develop or structure their perception of the complex nature of the creative process of musical artists involved in the institutions they manage.