The two-decade long history of events relating object-oriented programming, the development of persistence and transactional support, and the aggregation of multiple nodes in a single-system image cluster, appears to convey the following conclusion: programmers ideally would develop and deploy applications against a single shared global memory space (heap of objects) of mostly unbounded capacity, with implicit support for persistence and concurrency, transparently backed by a possibly large number of clustered physical machines.

In this paper, we propose a new approach to the design of OODB systems for Java applications: (O3)2 (pronounced ozone squared). It aims at providing to developers a single-system image of virtually unbounded object space/heap with support for object persistence, object querying, transactions and concurrency enforcement, backed by a cluster of multi-core machines with Java VMs that is kept transparent to the user/developer. It is based on an existing persistence framework (ozone-db) and the feasibility and performance of our approach has been validated resorting to the OO7 benchmark.

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In this work, we propose RATS, a middleware to enhance and extend the Terracotta framework for Java with the ability to transparently execute multi-threaded Java applications to provide a single-system image. It supports efficient scheduling of threads, according to available resources, across several nodes in a Terracotta cluster, taking advantage of the extra computational and memory resources available. It also supports profiling to gather application characteristics such as dispersion of thread workload, thread inter-arrival time and resource usage of the application. Profiling and clustering capabilities are inserted with the help of byte code instrumentations. We developed a range of alternative scheduling heuristics and classify them based on the application and cluster behavior. The middleware is tested with different applications with varying thread characteristics to assess and classify the scheduling heuristics with respect to application speed-ups. Results indicate that, for a CPU intensive application, it is possible to classify the scheduling heuristic based on application and cluster properties and also achieve linear speed ups. Furthermore, we show that a memory intensive application is able to scale its memory usage considerably when compared to running the application on a single JVM.

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Object-oriented programming languages presently are the dominant paradigm of application development (e.g., Java, .NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e-Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio-informatics, with many available Java-based APIs (e.g., Neobio).Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re-initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees.Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright © 2011 John Wiley & Sons, Ltd.

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Cloud computing has been dominated by system-level virtual machines to enable the management of resources using a coarse grained approach, largely in a manner independent from the applications running on these infrastructures. However, in such environments, although different types of applications can be running, the resources are often delivered in a equal manner to each one, missing the opportunity to manage the available resources in a more efficient and application aware or driven way. Our proposal is QoE-JVM supporting Java applications with a global and elastic distributed image of a high-level virtual machine (HLLVM), where total resource consumption and allocation (within and across applications in the infrastructure) are driven by incremental gains in quality-of-execution (QoE), which relates the resources allocated to an application and the performance the application can extract from having those resources. In this paper, we discuss how critical resources (memory and CPU) can be allocated among HLL-VMs, so that Cloud providers can exchange resource slices among virtual machines, continually adaptdressing where those resources are required, while being able to determine where the reduction will be more economically effective, i.e., will contribute in lesser extent to performance degradation.

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The traditional lock-based concurrency control is complex and error-prone due to its low-level nature and composability challenges. Software transactional memory (STM), inherited from the database world, has risen as an exciting alternative, sparing the programmer from dealing explicitly with such low-level mechanisms. In real world scenarios, software is often faced with requirements such as high availability and scalability, and the solution usually consists on building a distributed system. Given the benefits of STM over traditional concurrency controls, Distributed Software Transactional Memory (DSTM) is now being investigated as an attractive alternative for distributed concurrency control. Our long-term objective is to transparently enable multithreaded applications to execute over a DSTM setting. In this work we intend to pave the way by defining a modular DSTM framework for the Java programming language. We extend an existing, efficient, STM framework with a new software layer to create a DSTM framework. This new layer interacts with the local STM using well-defined interfaces, and allows the implementation of different distributed memory models while providing a non-intrusive, familiar, programming model to applications, unlike any other DSTM framework. Using the proposed DSTM framework we have successfully, and easily, implemented a replicated STM which uses a Certification protocol to commit transactions. An evaluation using common STM benchmarks showcases the efficiency of the replicated STM, and its modularity enables us to provide insight on the relevance of different implementations of the Group Communication System required by the Certification scheme, with respect to performance under different workloads.