Locking Timestamps Versus Locking Objects

We present multiversion timestamp locking (MVTL), a new genre of multiversion concurrency control algorithms for serializable transactions. The key idea behind MVTL is simple and novel: lock individual time points instead of locking objects or versions. After showing what a generic MVTL algorithm looks like, we demonstrate MVTL’s expressiveness: we present several simple MVTL algorithms that address limitations of current multiversion schemes, by committing trans- actions that previous schemes would abort, by avoiding the problem of serial aborts and ghost aborts, and by offering a way to prioritize transactions that should not be aborted

Universally Scalable Concurrent Data Structures

The increase in the number of cores in processors has been an important trend over the past decade. In order to be able to efficiently use such architectures, modern software must be scalable: performance should increase proportionally to the number of allotted cores. While some software is inherently parallel, with threads seldom having to coordinate, a large fraction of software systems are based on shared state, to which access must be coordinated. This shared state generally comes in the form of a concurrent data structure. It is thus essential for these concurrent data structures to be correct, fast and scalable, regardless of the scenario (i.e.,different workloads, processors, memory units, programming abstractions). Nevertheless, few or no generic approaches exist that result in concurrent data structures which scale in a large spectrum of environments. This dissertation introduces a set of generic methods that allows to build - irrespective of the deployment environment - fast and scalable concurrent data structures. We start by identifying a set of sufficient conditions for concurrent search data structures to scale and perform well regardless of the workloads and processors they are running on.We introduce âasynchronized concurrencyâ, a paradigm consisting of four complementary programming patterns, which calls for the design of concurrent search data structures to resemble that of their sequential counterparts. Next, we show that there is virtually no practical situation in which one should seek a âtheoretically wait-freeâ algorithm at the expense of a state-of-the-art blocking algorithm in the case of search data structures: blocking algorithms are simple, fast, and can be made "practically wait-free". We then focus on the memory unit, and provide a method yielding fast concurrent data structures even when the memory is non-volatile, and structures must be recoverable in case of a transient failure. We start by introducing a generic technique that allows us to avoid doing expensive writes to non-volatile memory by using a fast software cache. We also study memory management, and propose a solution tailored to concurrent data structures that uses coarse-grained memory management in order to avoid logging. Moreover, we argue for the use of lock-free algorithms in this non-volatile context, and show how by optimizing them we can avoid expensive logging operations. Together, the techniques we propose enable us to avoid any form of logging in the common case, thus significantly improving concurrent data structure performance when using non-volatile RAM. Finally, we go beyond basic interfaces, and look at scalable partitioned data structures implemented through a transactional interface. We present multiversion timestamp locking (MVTL),a new genre of multiversion concurrency control algorithms for serializable transactions. The key idea behind MVTL is simple and novel: lock individual time points instead of locking objects or versions. We provide several MVTL-based algorithms, that address limitations of current concurrency-control schemes. In short, by spanning workloads, processors, storage abstractions, and system sizes, this dissertation takes a step towards concurrent data structures that are universally scalable

Decentralized information flow control for databases

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 177-194).Privacy and integrity concerns have been mounting in recent years as sensitive data such as medical records, social network records, and corporate and government secrets are increasingly being stored in online systems. The rate of high-profile breaches has illustrated that current techniques are inadequate for protecting sensitive information. Many of these breaches involve databases that handle information for a multitude of individuals, but databases don't provide practical tools to protect those individuals from each other, so that task is relegated to the application. This dissertation describes a system that improves security in a principled way by extending the database system and the application platform to support information flow control. Information flow control has been gaining traction as a practical way to protect information in the contexts of programming languages and operating systems. Recent research advocates the decentralized model for information flow control (DIFC), since it provides the necessary expressiveness to protect data for many individuals with varied security concerns.However, despite the fact that most applications implicated in breaches rely on relational databases, there have been no prior comprehensive attempts to extend DIFC to a database system. This dissertation introduces IFDB, which is a database management system that supports DIFC with minimal overhead. IFDB pioneers the Query by Label model, which provides applications with a simple way to delineate constraints on the confidentiality and integrity of the data they obtain from the database. This dissertation also defines new abstractions for managing information flows in a database and proposes new ways to address covert channels. Finally, the IFDB implementation and case studies with real applications demonstrate that database support for DIFC improves security, is easy for developers to use, and has good performance.by David Andrew Schultz.Ph.D

New Concepts for Virtual Testbeds : Data Mining Algorithms for Blackbox Optimization based on Wait-Free Concurrency and Generative Simulation

Virtual testbeds have emerged as a key technology for improving and streamlining complex engineering processes by delivering long-term simulation and assessment of complex designs in virtual environments. In contrast to existing simulation technology, virtual testbeds focus on long-term physically-based simulation of the overall design in its (virtual) environment instead of only focussing on isolated, specific parts for short periods of time. This technology has the major advantage that costly testing, prototyping, and assessment in real-life environments are replaced by a cost-efficient simulation in virtual worlds for comprehensive and long-term analysis of designs. For this purpose, engineering models and their requirements are abstracted into software simulation models and objectives which are executed in virtual assessments. Simulation models are used to predict complex, real systems which can be further a subject to random influences. These predictions are used to examine the effects of individual configuration alternatives without actually realizing them and causing possible negative effects on the real system. Virtual testbeds further offer engineers the opportunity to immersively and naturally interact with their simulation model in these virtual assessments. This enables a greater and comprehensive understanding of possible design flaws early-on in the design process for engineers because they can directly assess their design in the virtual environment, based on the simulation objectives. The fact that virtual testbeds enable these realtime interactive virtual assessments, makes their underlying software infrastructure very complex. One major challenge is to minimize the development time of virtual testbeds in order to efficiently integrate them into the overall engineering process. Usually, this can be achieved by minimizing the underlying concurrency of the testbed and by simplifying its software architecture. However, this may result in a degradation of their very concurrent and asynchronous behavior, which is usually required for immersive and natural virtual interaction. A major goal of virtual testbeds in the engineering process is to find a set of optimal configurations of the simulation model which maximizes all simulation objectives for the specified virtual assessments. Once such a set has been computed, engineers can interactively explore it in the virtual environment. The main challenge is that sophisticated simulation models and their configuration are subject to a multiobjective optimization problem, which usually can not be solved manually by engineers or simulation analysts in feasible time. This is further aggravated because the relationships between simulation model configurations and simulation objectives are mostly unknown, leading to what is known as blackbox simulations. In this thesis, I propose novel data mining algorithms for computing Pareto optimal simulation model configurations, based on an approximation of the feasible design space, for deterministic and stochastic blackbox simulations in virtual testbeds for achieving above stated goal. These novel data mining algorithms lead to an automatic knowledge discovery process that does not need any supervision for its data analysis and assessment for multiobjective optimization problems of simulation model configurations. This achieves the previously stated goal of computing optimal configurations of simulation models for long-term simulations and assessments. Furthermore, I propose two complementary solutions for efficiently integrating massively-parallel virtual testbeds into engineering processes. First, I propose a novel multiversion wait-free data and concurrency management based on hash maps. These wait-free hash maps do not require any standard locking mechanisms and enable low-latency data generation, management and distribution for massively-parallel applications. Second, I propose novel concepts for efficiently code generating above wait-free data and concurrency management for arbitrary massively-parallel simulation applications of virtual testbeds. My generative simulation concept combines a state-of-the-art realtime interactive system design pattern for high maintainability with template code generation based on domain specific modelling. This concept is able to generate massively-parallel simulations and, at the same time, model checks its internal dataflow for possible interface errors. These generative concept overcomes the challenge of efficiently integrating virtual testbeds into engineering processes. These contributions enable for the first time a powerful collaboration between simulation, optimization, visualization and data analysis for novel virtual testbed applications but also overcome and achieve the presented challenges and goals

Proceedings Work-In-Progress Session of the 13th Real-Time and Embedded Technology and Applications Symposium

The Work-In-Progress session of the 13th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS\u2707) presents papers describing contributions both to state of the art and state of the practice in the broad field of real-time and embedded systems. The 17 accepted papers were selected from 19 submissions. This proceedings is also available as Washington University in St. Louis Technical Report WUCSE-2007-17, at http://www.cse.seas.wustl.edu/Research/FileDownload.asp?733. Special thanks go to the General Chairs – Steve Goddard and Steve Liu and Program Chairs - Scott Brandt and Frank Mueller for their support and guidance