Abstract. Middleware has emerged as an important architectural component in modern distributed systems. Most recently, industry has witnessed the emergence of component-based middleware platforms, such as Enterprise JavaBeans and the CORBA Component Model, aimed at supporting third party development, configuration and subsequent deployment of software. The goal of our research is to extend this work in order to exploit the benefits of componentbased approaches within the middleware platform as well as on top of the platform, the result being more configurable and reconfigurable middleware technologies. This is achieved through a marriage of components with reflection, the latter providing the necessary levels of openness to access the underlying component infrastructure. More specifically, the paper describes in detail the OpenCOM component model, a lightweight and efficient component model based on COM. The paper also describes how OpenCOM can be used to construct a full middleware platform, and also investigates the performance of both OpenCOM and this resultant platform. The main overall contribution of the paper is to demonstrate that flexible middleware technologies can be developed without an adverse effect on the performance of resultant systems.

It is now well established that middleware platforms must accommodate an increasingly diverse range of requirements arising from the needs of both applications and underlying systems. Moreover, it is clear that to achieve this accommodation, platforms must be capable of both deploymenttime configurability and run-time reconfigurability. This paper describes a middleware platform that addresses these requirements. The platform is built using a well-founded lightweight component model, uses reflective techniques to facilitate (re)configuration, and employs the notion of component frameworks to manage and constrain the scope of reconfiguration operations. Importantly, the platform also aims to achieve high performance and a level of standards conformance (e.g., with CORBA and COM). We demonstrate that, despite its high degree of configurability, the platform performs on a par with standard commercial CORBA ORBs.

Abstract:The MapReduce programming model, introduced by Google, offers a simple and efficient way of performing distributed computation over large data sets. Although Google's implementation is proprietary, MapReduce can be leveraged by anyone using the free and open-source Apache Hadoop framework. To simplify the usage of Hadoop in the cloud, Amazon Web Services offers Elastic MapReduce, a web service enabling users to run MapReduce jobs. Elastic MapReduce takes care of resource provisioning, Hadoop configuration and performance tuning, data staging, fault tolerance, etc. This service drastically reduces the entry barrier to perform MapReduce computations in the cloud, allowing users to concentrate on the problem to solve. However, Elastic MapReduce is restricted to Amazon EC2 resources, and is provided at an additional cost. In this paper, we present Resilin, a system implementing the Elastic MapReduce API with resources from clouds other than Amazon EC2, such as private and scientific clouds. Furthermore, we explore a feature going beyond the current Amazon Elastic MapReduce offering: performing MapReduce computations over multiple distributed clouds. The evaluation of Resilin shows the benefits of running computations on more than one cloud. While not being the most efficient way to perform Hadoop computations, it solves the problem of resource availability and adds more flexibility regarding the type/price of resource.

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Abstract. Middleware has emerged as an important architectural component in supporting distributed applications. With the expanding role of middleware, however, a number of problems are emerging. Most significantly, it is becoming difficult for a single solution to meet the requirements of a range of application domains. Hence, the paper argues that the next generation of middleware platforms should be both configurable and re-configurable. Furthermore, it is claimed that reflection offers a principled means of achieving these goals. The paper then presents an architecture for reflective middleware based on a multi-model approach. The main emphasis of the paper is on resource management within this architecture (accessible through one of the meta-models). Through a number of worked examples, we demonstrate that the approach can support introspection, and fine-and coarse-grained adaptation of the resource management framework. We also illustrate how we can achieve multi-faceted adaptation, spanning multiple meta-models.

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