Design and Implementation of the LogicBlox System

Collaborative virtual environment for product design occurs between people and often involves 3D objects. Fruitful cooperation is helped by natural and intuitive way of communication and interaction, for which responsiveness and consistency are leading factors. In order to guarantee consistency and improve responsiveness, a novel concurrency control scheme is first proposed. In our scheme, non-exclusive concurrent manipulations are merged so as to undo a small quantity of manipulations rather than all the operations triggered by users who are not granted, therefore, a majority of concurrent operations are collision-free and executed immediately to maximize responsiveness. Moreover, notification and visual indicator mechanism are used to avoid unnecessary concurrency collision. The implementation of collaborative virtual environment named VRCAD is then introduced in detail, including system architecture, concurrency control strategy and communication facilities. Experiment and practice show that our concurrency control scheme is effective and efficient for collaborative virtual environment involving 3D objects.

Proposes a hybrid concurrency control scheme which can alleviate the effects of frequent disconnections and bandwidth limitations in mobile computing environments. If a transaction in a mobile host executes only read operations, our concurrency control scheme is the same as the optimistic concurrency control scheme based on the timestamp history. Otherwise, if it executes write operations, the write set has to be sent to a fixed host during the execution phase. If a disconnection from the mobile host occurs, the fixed host performs a pre-validation of the write set. As a result of this pre-validation, if conflicts are detected, the transaction is aborted. Otherwise, we use the locking method called weak lock. Our scheme reduces the number of aborts and the validation time without message overheads.

Concurrency control schemes for OODBMSs used in the area of performance-critical applications should increase the degree of concurrency and decrease locking overhead in order to offer maximum throughput and minimum response time. However, most commercially available OODBMSs use conventional concurrency control schemes which never exploit the rich semantics of object-oriented data model, so that they fail to offer better performance. In this paper, we propose a concurrency control scheme for OODBMSs, called ISMGL, that not only exploits semantics regarding methods to enhance the concurrency degree, but also utilizes multigranularity locking rules to decrease locking overhead. The novel aspect of ISMGL is that it combines conventional multigranularity locking and nested transaction model with utilizing commutativity of methods. Our concurrency control scheme is applicable for realistic OODBMSs in the presence of complex objects with shared subobjects.

This research focuses on analyzing and improving maintenance process by exploring novel applications of process mining and predictive analytics. We analyze the software maintenance process by applying process mining on software repositories, and address the identified inefficiencies using predictive analytics. To drive our research, we engage with practitioners from large, global IT companies and emphasize on the practical usability of the proposed solution approaches, which are evaluated by conducting a series of case studies on open source and commercial projects.

For next generation information systems, concurrency control mechanisms are required to handle high level abstract operations and to meet high throughput demands. The currently available single level concurrency control mechanisms for reads and writes are inadequate for future complex information systems. In this paper, we will present a new multilevel concurrency protocol that uses a semantics-based notion of conflict, which is weaker than commutativity, called recoverability . Further, operations are scheduled according to relative conflict , a conflict notion based on the structure of operations. Performance evaluation via extensive simulation studies show that with our multilevel concurrency control protocol, the performance improvement is significant when compared to that of a single level two-phase locking based concurrency control scheme or to that of a multilevel concurrency control scheme based on commutativity alone. Further, simulation studies show that our new multilevel concurrency control protocol performs better even with resource contention.

Multicore in-memory databases often rely on traditional con- currency control schemes such as two-phase-locking (2PL) or optimistic concurrency control (OCC). Unfortunately, when the workload exhibits a non-trivial amount of contention, both 2PL and OCC sacrifice much parallel execution op- portunity. In this paper, we describe a new concurrency control scheme, interleaving constrained concurrency con- trol (IC3), which provides serializability while allowing for parallel execution of certain conflicting transactions. IC3 combines the static analysis of the transaction workload with runtime techniques that track and enforce dependencies among concurrent transactions. The use of static analysis simplifies IC3's runtime design, allowing it to scale to many cores. Evaluations on a 64-core machine using the TPC- C benchmark show that IC3 outperforms traditional con- currency control schemes under contention. It achieves the throughput of 434K transactions/sec on the TPC-C bench- mark configured with only one warehouse. It also scales better than several recent concurrent control schemes that also target contended workloads.

A transaction model for multidatabase system (MDBS) applications in which global subtransactions may be either compensatable or retriable is presented. In this model compensation and retrying are used for recovery purposes. However, since such executions may no longer consist of atomic transactions, a correctness criterion that ensures that transactions see consistent database states is necessary. A commit protocol and a concurrency control scheme that ensures that all generated schedules are correct are also presented. The commit protocol eliminates the problem of blocking, which is characteristics of the standard 2PC protocol. The concurrency control protocol can be used in any MDBS environment irrespective of the concurrency control protocol followed by the local DBMSs in order to ensure serializability. >

OODBMS is widely favored for mapping domains like CAD, with complex representation requirements. The transactions accessing OODBMS can be categorized into runtime transactions and design time transactions. Runtime transactions are meant for accessing data and design time transactions are meant for accessing schema. Parallel execution of transactions is supported to promote concurrency and throughput. In continuously evolving business domains, frequent schema changes are done to reflect the changes of business domain. Then it implies that more number of design time transactions arrive parallely with runtime transactions. Concurrency control schemes are employed to maintain the consistency of the database. Several semantic multi-granular lock based concurrency control schemes have been proposed in the literature. They have the drawback of either poor performance or high maintenance overhead when applied to continuously evolving domains. This paper proposes semantic lock-based concurrency control mechanism with better performance and nil maintenance overhead for continuously evolving OODBMS. It uses lock rippling to improve the performance.KeywordsDistributed object oriented databasescontinuously evolving domainsconcurrency controlmulti granular lock model

With ever-increasing volume and heterogeneity of data, advent of new specialized compute engines, and demand for complex use cases, large-scale data systems require a performant catalog system that can satisfy diverse needs. We argue that existing solutions, including recent lakehouse storage formats, have fundamental limitations and that there is a strong motivation for a specialized database engine, dedicated to serve as the catalog. We present the design and implementation of TreeCat , a database engine that features a hierarchical data model with a path-based query language, a storage format optimized for efficient range queries and versioning, and a correlated scan operation that enables fast query execution. A key performance challenge is supporting concurrent read and write operations from many different clients while providing strict consistency guarantees. To this end, we present a novel MVOCC (multi-versioned optimistic concurrency control) protocol that guarantees serializable isolation. We conduct a comprehensive experimental evaluation comparing our concurrency control scheme with prior techniques, and evaluating our overall system against Hive Metastore, Delta Lake, and Iceberg.

Early simulation is a very important tool in the development any large scale system. Accuracy and flexibility are critical characteristics which allow the architect to explore the design tradeoff space. Moreover, in many systems, especially those for reconfigurable computing, a good simulation environment will continue to be used long after the architecture solidifies, serving a variety of roles including as a platform for the development of run time systems, programming tools, benchmarks, and even end applications. Therefore, visibility, controllability and user interface are also important design considerations. National Semiconductor's Adaptive Processing Architecture (NAPA) integrates a Fixed Instruction set Processor (FIP), an Adaptive Logic Processor (ALP), memory and other support circuitry into a single reconfigurable computing device. The NAPA architecture simulator, NAPAsim, consists of a C language, cycle accurate model of the RISC core, peripherals and memories, coupled with an event driven logic simulator for modelling the user-defined contents of the reconfigurable logic and a Tcl/Tk based GUI to provide source level symbolic debugging capabilities. NAPAsim was developed to serve as both a tool for architectural exploration and as a platform for system and application software development.

The proliferation of financial data and the increasing complexity of global markets have necessitated the development of advanced predictive frameworks for informed investment decision-making. Traditional forecasting approaches, including fundamental and technical analysis, often fail to capture the nonlinear, high-dimensional, and dynamic nature of stock markets, limiting their effectiveness in volatile environments. This chapter presents a comprehensive exploration of machine learning (ML) techniques and predictive analytics methodologies for stock market trend forecasting and adaptive investment management. By integrating structured financial data with unstructured sources such as news sentiment, social media indicators, and alternative datasets, predictive models can capture both quantitative and qualitative market signals, enhancing the accuracy and robustness of forecasts. The application of supervised, unsupervised, and reinforcement learning algorithms enables the development of adaptive investment strategies that respond dynamically to evolving market conditions. Reinforcement learning frameworks, in particular, facilitate sequential decision-making, optimizing portfolio allocations and trading policies through continuous interaction with market environments. The incorporation of real-time analytics and scenario-based stress testing allows institutions to proactively manage risk, identify anomalous patterns, and adjust strategies to mitigate potential losses. Challenges associated with data heterogeneity, noise, model interpretability, and regulatory compliance are addressed through feature engineering, explainable AI techniques, and ethical design considerations, ensuring both reliability and transparency of predictive outputs. This chapter underscores the transformative potential of integrating machine learning-driven predictive insights into real-time financial decision-making. By combining advanced algorithms, heterogeneous data sources, and adaptive learning strategies, financial institutions can achieve superior forecasting accuracy, enhanced portfolio performance, and effective risk mitigation. The findings highlight the critical role of explainable, ethically-informed predictive analytics in modern investment management, offering a framework for both academic research and practical application in dynamic market environments.

Multi-version concurrency control scheme for a database system

An adaptable constrained locking protocol for high data contention environments: correctness and performance

A composite service consists of many Web Services. The execution of a composite service is conducted by an execution engine according to the workflow specification. Since different composite services might share and access some of the Web Services concurrently, ensuring the correctness of the concurrent execution of the composite services becomes an important issue. This paper proposes a concurrency control scheme for executing transactional composite services. The scheme is implemented as a middleware. It uses the information gathered from the workflow specifications of the composite services to guarantee the correctness of the execution of the composite services. The proposed scheme avoids the repeated rollback problem facing most existing concurrency control schemes, and, it is more suitable for the clients who use handheld devices to access the web services.

To speed up online analytical processing, data warehousing systems materialize views derived from several operational databases. When the operational databases happen to change, the materialized views get stale. To enhance the freshness of the materialized views, this article proposes a new concurrency control scheme that makes use of selective versioning to aid analytical transactions in continuously accessing fresh data.