192 research outputs found

    High availability using virtualization

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    High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows to share the running virtual machines over the servers up and running, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The system (3RC) is based on a finite state machine with hysteresis, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system. As extension of the 3RC architecture, several storage solutions have been tested to store and centralize all the virtual disks, from NAS to SAN, to grant data safety and access from everywhere. Exploiting virtualization and ability to automatically reinstall a host, we provide a sort of host on-demand, where the action on a virtual machine is performed only when a disaster occurs.Comment: PhD Thesis in Information Technology Engineering: Electronics, Computer Science, Telecommunications, pp. 94, University of Pisa [Italy

    Intel TDX Demystified: A Top-Down Approach

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    Intel Trust Domain Extensions (TDX) is a new architectural extension in the 4th Generation Intel Xeon Scalable Processor that supports confidential computing. TDX allows the deployment of virtual machines in the Secure-Arbitration Mode (SEAM) with encrypted CPU state and memory, integrity protection, and remote attestation. TDX aims to enforce hardware-assisted isolation for virtual machines and minimize the attack surface exposed to host platforms, which are considered to be untrustworthy or adversarial in the confidential computing's new threat model. TDX can be leveraged by regulated industries or sensitive data holders to outsource their computations and data with end-to-end protection in public cloud infrastructure. This paper aims to provide a comprehensive understanding of TDX to potential adopters, domain experts, and security researchers looking to leverage the technology for their own purposes. We adopt a top-down approach, starting with high-level security principles and moving to low-level technical details of TDX. Our analysis is based on publicly available documentation and source code, offering insights from security researchers outside of Intel

    DEPENDABILITY BENCHMARKING OF NETWORK FUNCTION VIRTUALIZATION

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    Network Function Virtualization (NFV) is an emerging networking paradigm that aims to reduce costs and time-to-market, improve manageability, and foster competition and innovative services. NFV exploits virtualization and cloud computing technologies to turn physical network functions into Virtualized Network Functions (VNFs), which will be implemented in software, and will run as Virtual Machines (VMs) on commodity hardware located in high-performance data centers, namely Network Function Virtualization Infrastructures (NFVIs). The NFV paradigm relies on cloud computing and virtualization technologies to provide carrier-grade services, i.e., the ability of a service to be highly reliable and available, within fast and automatic failure recovery mechanisms. The availability of many virtualization solutions for NFV poses the question on which virtualization technology should be adopted for NFV, in order to fulfill the requirements described above. Currently, there are limited solutions for analyzing, in quantitative terms, the performance and reliability trade-offs, which are important concerns for the adoption of NFV. This thesis deals with assessment of the reliability and of the performance of NFV systems. It proposes a methodology, which includes context, measures, and faultloads, to conduct dependability benchmarks in NFV, according to the general principles of dependability benchmarking. To this aim, a fault injection framework for the virtualization technologies has been designed and implemented for the virtualized technologies being used as case studies in this thesis. This framework is successfully used to conduct an extensive experimental campaign, where we compare two candidate virtualization technologies for NFV adoption: the commercial, hypervisor-based virtualization platform VMware vSphere, and the open-source, container-based virtualization platform Docker. These technologies are assessed in the context of a high-availability, NFV-oriented IP Multimedia Subsystem (IMS). The analysis of experimental results reveal that i) fault management mechanisms are crucial in NFV, in order to provide accurate failure detection and start the subsequent failover actions, and ii) fault injection proves to be valuable way to introduce uncommon scenarios in the NFVI, which can be fundamental to provide a high reliable service in production

    A Survey of Techniques for Improving Security of GPUs

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    Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest `link' in the security `chain'. In this paper, we present a survey of techniques for analyzing and improving GPU security. We classify the works on key attributes to highlight their similarities and differences. More than informing users and researchers about GPU security techniques, this survey aims to increase their awareness about GPU security vulnerabilities and potential countermeasures

    Emerging Security Threats in Modern Digital Computing Systems: A Power Management Perspective

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    Design of computing systems — from pocket-sized smart phones to massive cloud based data-centers — have one common daunting challenge : minimizing the power consumption. In this effort, power management sector is undergoing a rapid and profound transformation to promote clean and energy proportional computing. At the hardware end of system design, there is proliferation of specialized, feature rich and complex power management hardware components. Similarly, in the software design layer complex power management suites are growing rapidly. Concurrent to this development, there has been an upsurge in the integration of third-party components to counter the pressures of shorter time-to-market. These trends collectively raise serious concerns about trust and security of power management solutions. In recent times, problems such as overheating, performance degradation and poor battery life, have dogged the mobile devices market, including the infamous recall of Samsung Note 7. Power outage in the data-center of a major airline left innumerable passengers stranded, with thousands of canceled flights costing over 100 million dollars. This research examines whether such events of unintentional reliability failure, can be replicated using targeted attacks by exploiting the security loopholes in the complex power management infrastructure of a computing system. At its core, this research answers an imminent research question: How can system designers ensure secure and reliable operation of third-party power management units? Specifically, this work investigates possible attack vectors, and novel non-invasive detection and defense mechanisms to safeguard system against malicious power attacks. By a joint exploration of the threat model and techniques to seamlessly detect and protect against power attacks, this project can have a lasting impact, by enabling the design of secure and cost-effective next generation hardware platforms

    Intelligent Management of Virtualised Computer Based Workloads and Systems

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    Managing the complexity within virtualised IT infrastructure platforms is a common problem for many organisations today. Computer systems are often highly consolidated into a relatively small physical footprint compared with previous decades prior to late 2000s, so much thought, planning and control is necessary to effectively operate such systems within the enterprise computing space. With the development of private, hybrid and public cloud utility computing this has become even more relevant; this work examines how such cloud systems are using virtualisation technology and embedded software to leverage advantages, and it uses a fresh approach of developing and creating an Intelligent decision engine (expert system). Its aim is to help reduce the complexity of managing virtualised computer-based platforms, through tight integration, high-levels of automation to minimise human inputs, errors, and enforce standards and consistency, in order to achieve better management and control. The thesis investigates whether an expert system known as the Intelligent Decision Engine (IDE) could aid the management of virtualised computer-based platforms. Through conducting a series of mixed quantitative and qualitative experiments in the areas of research, the initial findings and evaluation are presented in detail, using repeatable and observable processes and provide detailed analysis on the recorded outputs. The results of the investigation establish the advantages of using the IDE (expert system) to achieve the goal of reducing the complexity of managing virtualised computer-based platforms. In each detailed area examined, it is demonstrated how using a global management approach in combination with VM provisioning, migration, failover, and system resource controls can create a powerful autonomous system

    Optimizing live virtual machine migrations using content-based page hashes

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 55).Virtualization systems such as VMware ESX Server use content-based page hashing to help identify duplicate memory pages within virtual machines. Such duplicate pages, once identified, can then be mapped copy-on-write to a single page in physical RAM, thus saving memory in a manner that is transparent to the virtual machine. The page hashes that are collected in this process can be further utilized. This thesis demonstrates how these page hashes can be used to reduce the time required to migrate running virtual machines from one physical machine to another. Normally, this is done by sending the virtual machine state and all memory contents from the source to destination machine. However, since some memory pages may already be present on the destination, it is possible to reduce the number of pages sent (and therefore total migration time and bandwidth used), by sending only a compact hash instead of the full contents for each page likely to be present on the destination machine. This thesis accomplishes this by creating a database of canonical or "standard" pages to determine which pages can be safely sent as only a hash. Tests of the system demonstrate up to 70% reduction in migration time in idealized workloads, 40% reduction in some realistic workloads, and minimal slowdown in some pathological cases.by Jacob A. Stultz.M.Eng

    Cloud Computing cost and energy optimization through Federated Cloud SoS

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    2017 Fall.Includes bibliographical references.The two most significant differentiators amongst contemporary Cloud Computing service providers have increased green energy use and datacenter resource utilization. This work addresses these two issues from a system's architectural optimization viewpoint. The proposed approach herein, allows multiple cloud providers to utilize their individual computing resources in three ways by: (1) cutting the number of datacenters needed, (2) scheduling available datacenter grid energy via aggregators to reduce costs and power outages, and lastly by (3) utilizing, where appropriate, more renewable and carbon-free energy sources. Altogether our proposed approach creates an alternative paradigm for a Federated Cloud SoS approach. The proposed paradigm employs a novel control methodology that is tuned to obtain both financial and environmental advantages. It also supports dynamic expansion and contraction of computing capabilities for handling sudden variations in service demand as well as for maximizing usage of time varying green energy supplies. Herein we analyze the core SoS requirements, concept synthesis, and functional architecture with an eye on avoiding inadvertent cascading conditions. We suggest a physical architecture that diminishes unwanted outcomes while encouraging desirable results. Finally, in our approach, the constituent cloud services retain their independent ownership, objectives, funding, and sustainability means. This work analyzes the core SoS requirements, concept synthesis, and functional architecture. It suggests a physical structure that simulates the primary SoS emergent behavior to diminish unwanted outcomes while encouraging desirable results. The report will analyze optimal computing generation methods, optimal energy utilization for computing generation as well as a procedure for building optimal datacenters using a unique hardware computing system design based on the openCompute community as an illustrative collaboration platform. Finally, the research concludes with security features cloud federation requires to support to protect its constituents, its constituents tenants and itself from security risks
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