A tool to simplify the management of homogeneous and heterogeneous grids

To simplify computer management, several system administrators are adopting advanced techniques to manage software configuration on grids, but the tight coupling between hardware and software makes every PC an individual managed entity, lowering the scalability and increasing the costs to manage hundreds or thousands of PCs. This paper discusses the feasibility of a distributed virtual machine environment, named Flexlab: a new approach for computer management that combines virtualization and distributed system architectures as the basis of a management system. Flexlab is able to extend the coverage of a computer management solution beyond client operating system limitations and also offers a convenient hardware abstraction, decoupling software and hardware, simplifying computer management. The results obtained in this work indicate that FlexLab is able to overcome the limitations imposed by the coupling between software and hardware, simplifying the management of homogeneous and heterogeneous grids. © 2009 IEEE.

Interface Gráfica para o planejamento da expansão da transmissão de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

FLEXLAB: Middleware de virtualização de hardware para gerenciamento centralizado de computadores em rede

Pós-graduação em Ciência da Computação - IBILCE

Tolerância a falha em um ambiente de computação em nuvem open source

Pós-graduação em Ciência da Computação - IBILCE

Abordagem icônica para modelagem e simulação de ambientes de computação em nuvem ?

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Esperimenti di Sistemi Distribuiti Virtuali riconfigurabili per il risparmio energetico

Esperimenti sulla virtualizzazione del laboratorio informatico della facoltà, che attraverso migrazioni di virtual machine, consentirebbe il risparmio energetico grazie allo spegnimento di alcune macchine fisiche.

Applying partial virtualization on ELF binaries through dynamic loaders

The technology of partial virtualization is a revolutionary approach to the world of virtualization. It lies directly in-between full system virtual machines (like QEMU or XEN) and application-related virtual machines (like the JVM or the CLR). The ViewOS project is the flagship of such technique, developed by the Virtual Square laboratory, created to provide an abstract view of the underlying system resources on a per-process basis and work against the principle of the Global View Assumption. Virtual Square provides several different methods to achieve partial virtualization within the ViewOS system, both at user and kernel levels. Each of these approaches have their own advantages and shortcomings. This paper provides an analysis of the different virtualization methods and problems related to both the generic and partial virtualization worlds. This paper is the result of an in-depth study and research for a new technology to be employed to provide partial virtualization based on ELF dynamic binaries. It starts with a mild analysis of currently available virtualization alternatives and then goes on describing the ViewOS system, highlighting its current shortcomings. The vloader project is then proposed as a possible solution to some of these inconveniences with a working proof of concept and examples to outline the potential of such new virtualization technique. By injecting specific code and libraries in the middle of the binary loading mechanism provided by the ELF standard, the vloader project can promote a streamlined and simplified approach to trace system calls. With the advantages outlined in the following paper, this method presents better performance and portability compared to the currently available ViewOS implementations. Furthermore, some of itsdisadvantages are also discussed, along with their possible solutions.

SDN e sperimentazioni di VM migration

Le nuove teorie di rete come Software Defined Networking Network Function Virtualization, insieme alle teorie Cognitive/Autonomics consentono di abilitare scenari futuri “disruptive” di rete. Lo scopo di questa tesi è quello di esplorare questi scenari futuri e di capire il ruolo della migrazione di funzioni di rete, sotto forma di Virtual Machine. Si vuole affrontare la migrazione di Virtual Machine dal punto di vista delle performance, ma anche come strumento di gestione delle risorse in uno scenario di rete d'accesso autonomica.

Gpu-based many-core architecture emulation: A double level approach

The efficient emulation of a many-core architecture is a challenging task, each core could be emulated through a dedicated thread and such threads would be interleaved on an either single-core or a multi-core processor. The high number of context switches will results in an unacceptable performance. To support this kind of application, the GPU computational power is exploited in order to schedule the emulation threads on the GPU cores. This presents a non trivial divergence issue, since GPU computational power is offered through SIMD processing elements, that are forced to synchronously execute the same instruction on different memory portions. Thus, a new emulation technique is introduced in order to overcome this limitation: instead of providing a routine for each ISA opcode, the emulator mimics the behavior of the Micro Architecture level, here instructions are date that a unique routine takes as input. Our new technique has been implemented and compared with the classic emulation approach, in order to investigate the chance of a hybrid solution.

Esperimenti di integrazione ViewOS-Rump: lo stack di rete NetBSD

In questo lavoro si indaga la possibilita' di includere lo stack TCP-IP NetBSD, estratto come libreria dinamica ed eseguito all'interno di un kernel rump, come sottomodulo di rete della System Call Virtual Machine UMView di Virtual Square. Il risultato ottenuto consiste in umnetbsd, il modulo che ne dimostra la fattibilita', e libvdeif, una libreria per connettere kernel rump a switch VDE.

Pinocchio: Bringing Reflection to Life with First-Class Interpreters

To support development tools like debuggers, runtime systems need to provide a meta-programming interface to alter their semantics and access internal data. Reflective capabilities are typically fixed by the Virtual Machine (VM). Unanticipated reflective features must either be simulated by complex program transformations, or they require the development of a specially tailored VM. We propose a novel approach to behavioral reflection that eliminates the barrier between applications and the VM by manipulating an explicit tower of first-class interpreters. Pinocchio is a proof-of-concept implementation of our approach which enables radical changes to the interpretation of programs by explicitly instantiating subclasses of the base interpreter. We illustrate the design of Pinocchio through non-trivial examples that extend runtime semantics to support debugging, parallel debugging, and back-in-time object-flow debugging. Although performance is not yet addressed, we also discuss numerous opportunities for optimization, which we believe will lead to a practical approach to behavioral reflection.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Practical Object-Oriented Back-in-Time Debugging

Back-in-time debuggers are extremely useful tools for identifying the causes of bugs, as they allow us to inspect the past states of objects no longer present in the current execution stack. Unfortunately the "omniscient" approaches that try to remember all previous states are impractical because they either consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach to back-in-time debugging that attempts to keep track of only the relevant past data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that past data that is not reachable from current application objects (and hence, no longer relevant) is automatically garbage collected. In this paper we describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore since our approach works at the virtual machine level, the performance penalty is significantly better than with other approaches.

PyGirl Generating Whole-System VMs from high-level models using PyPy

Virtual machines emulating hardware devices are generally implemented in low-level languages and using a low-level style for performance reasons. This trend results in largely difficult to understand, difficult to extend and unmaintainable systems. As new general techniques for virtual machines arise, it gets harder to incorporate or test these techniques because of early design and optimization decisions. In this paper we show how such decisions can be postponed to later phases by separating virtual machine implementation issues from the high-level machine-specific model. We construct compact models of whole-system VMs in a high-level language, which exclude all low-level implementation details. We use the pluggable translation toolchain PyPy to translate those models to executables. During the translation process, the toolchain reintroduces the VM implementation and optimization details for specific target platforms. As a case study we implement an executable model of a hardware gaming device. We show that our approach to VM building increases understandability, maintainability and extendability while preserving performance.

Flow-Centric, Back-In-Time Debugging

Conventional debugging tools present developers with means to explore the run-time context in which an error has occurred. In many cases this is enough to help the developer discover the faulty source code and correct it. However, rather often errors occur due to code that has executed in the past, leaving certain objects in an inconsistent state. The actual run-time error only occurs when these inconsistent objects are used later in the program. So-called back-in-time debuggers help developers step back through earlier states of the program and explore execution contexts not available to conventional debuggers. Nevertheless, even back-in-time debuggers do not help answer the question, ``Where did this object come from?'' The Object-Flow Virtual Machine, which we have proposed in previous work, tracks the flow of objects to answer precisely such questions, but this VM does not provide dedicated debugging support to explore faulty programs. In this paper we present a novel debugger, called Compass, to navigate between conventional run-time stack-oriented control flow views and object flows. Compass enables a developer to effectively navigate from an object contributing to an error back-in-time through all the code that has touched the object. We present the design and implementation of Compass, and we demonstrate how flow-centric, back-in-time debugging can be used to effectively locate the source of hard-to-find bugs.