Unification of Transactions and Replication in Three-Tier Architectures Based on CORBA

In this paper, we describe a software infrastructure that unifies transactions and replication in three-tier architectures and provides data consistency and high availability for enterprise applications. The infrastructure uses transactions based on the CORBA object transaction service to protect the application data in databases on stable storage, using a roll-backward recovery strategy, and replication based on the fault tolerant CORBA standard to protect the middle-tier servers, using a roll-forward recovery strategy. The infrastructure replicates the middle-tier servers to protect the application business logic processing. In addition, it replicates the transaction coordinator, which renders the two-phase commit protocol nonblocking and, thus, avoids potentially long service disruptions caused by failure of the coordinator. The infrastructure handles the interactions between the replicated middle-tier servers and the database servers through replicated gateways that prevent duplicate requests from reaching the database servers. It implements automatic client-side failover mechanisms, which guarantee that clients know the outcome of the requests that they have made, and retries aborted transactions automatically on behalf of the clients

Parallelizing RRT on large-scale distributed-memory architectures

This paper addresses the problem of parallelizing the Rapidly-exploring Random Tree (RRT) algorithm on large-scale distributed-memory architectures, using the Message Passing Interface. We compare three parallel versions of RRT based on classical parallelization schemes. We evaluate them on different motion planning problems and analyze the various factors influencing their performance

The parallel event loop model and runtime: a parallel programming model and runtime system for safe event-based parallel programming

Recent trends in programming models for server-side development have shown an increasing popularity of event-based single- threaded programming models based on the combination of dynamic languages such as JavaScript and event-based runtime systems for asynchronous I/O management such as Node.JS. Reasons for the success of such models are the simplicity of the single-threaded event-based programming model as well as the growing popularity of the Cloud as a deployment platform for Web applications. Unfortunately, the popularity of single-threaded models comes at the price of performance and scalability, as single-threaded event-based models present limitations when parallel processing is needed, and traditional approaches to concurrency such as threads and locks don't play well with event-based systems. This dissertation proposes a programming model and a runtime system to overcome such limitations by enabling single-threaded event-based applications with support for speculative parallel execution. The model, called Parallel Event Loop, has the goal of bringing parallel execution to the domain of single-threaded event-based programming without relaxing the main characteristics of the single-threaded model, and therefore providing developers with the impression of a safe, single-threaded, runtime. Rather than supporting only pure single-threaded programming, however, the parallel event loop can also be used to derive safe, high-level, parallel programming models characterized by a strong compatibility with single-threaded runtimes. We describe three distinct implementations of speculative runtimes enabling the parallel execution of event-based applications. The first implementation we describe is a pessimistic runtime system based on locks to implement speculative parallelization. The second and the third implementations are based on two distinct optimistic runtimes using software transactional memory. Each of the implementations supports the parallelization of applications written using an asynchronous single-threaded programming style, and each of them enables applications to benefit from parallel execution

Self-Similarity in a multi-stage queueing ATM switch fabric

Recent studies of digital network traffic have shown that arrival processes in such an environment are more accurately modeled as a statistically self-similar process, rather than as a Poisson-based one. We present a simulation of a combination sharedoutput queueing ATM switch fabric, sourced by two models of self-similar input. The effect of self-similarity on the average queue length and cell loss probability for this multi-stage queue is examined for varying load, buffer size, and internal speedup. The results using two self-similar input models, Pareto-distributed interarrival times and a Poisson-Zeta ON-OFF model, are compared with each other and with results using Poisson interarrival times and an ON-OFF bursty traffic source with Ge ometrically distributed burst lengths. The results show that at a high utilization and at a high degree of self-similarity, switch performance improves slowly with increasing buffer size and speedup, as compared to the improvement using Poisson-based traffic

The parallel event loop model and runtime: a parallel programming model and runtime system for safe event-based parallel programming

Recent trends in programming models for server-side development have shown an increasing popularity of event-based single- threaded programming models based on the combination of dynamic languages such as JavaScript and event-based runtime systems for asynchronous I/O management such as Node.JS. Reasons for the success of such models are the simplicity of the single-threaded event-based programming model as well as the growing popularity of the Cloud as a deployment platform for Web applications. Unfortunately, the popularity of single-threaded models comes at the price of performance and scalability, as single-threaded event-based models present limitations when parallel processing is needed, and traditional approaches to concurrency such as threads and locks don't play well with event-based systems. This dissertation proposes a programming model and a runtime system to overcome such limitations by enabling single-threaded event-based applications with support for speculative parallel execution. The model, called Parallel Event Loop, has the goal of bringing parallel execution to the domain of single-threaded event-based programming without relaxing the main characteristics of the single-threaded model, and therefore providing developers with the impression of a safe, single-threaded, runtime. Rather than supporting only pure single-threaded programming, however, the parallel event loop can also be used to derive safe, high-level, parallel programming models characterized by a strong compatibility with single-threaded runtimes. We describe three distinct implementations of speculative runtimes enabling the parallel execution of event-based applications. The first implementation we describe is a pessimistic runtime system based on locks to implement speculative parallelization. The second and the third implementations are based on two distinct optimistic runtimes using software transactional memory. Each of the implementations supports the parallelization of applications written using an asynchronous single-threaded programming style, and each of them enables applications to benefit from parallel execution

Service selection and transactional management for web service composition

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