Vincent Matossian

AutoMate: enabling autonomic applications on the grid

The increasing complexity, heterogeneity and dynamism of networks, systems, services applications have made our computational/information infrastructure brittle, unmanageable and insecure. This has necessitated the investigation of a new paradigm for design, development and deployment based on strategies used by biological systems to deal with complexity, heterogeneity, and uncertainty, i.e. autonomic computing. This paper introduces the AutoMate project and describes its key components. The overall objective of AutoMate is to investigate key technologies to enable the development of autonomic grid applications that are context aware and are capable of self-configuring, self-composing, self-optimizing and self-adapting. Specifically, it will investigate the definition of autonomic components, the development of autonomic applications as dynamic composition of autonomic components, and the design of key enhancements to existing grid middleware and runtime services to support these applications.

AutoMate: Enabling Autonomic Applications on the Grid

The increasing complexity, heterogeneity, and dynamism of emerging pervasive Grid environments and applications has necessitated the development of autonomic self-managing solutions, that are inspired by biological systems and deal with similar challenges of complexity, heterogeneity, and uncertainty. This paper introduces Project AutoMate and describes its key components. The overall goal of Project Automate is to investigate conceptual models and implementation architectures that can enable the development and execution of such self-managing Grid applications. Illustrative autonomic scientific and engineering Grid applications enabled by AutoMate are presented.

An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement

The adequate location of wells in oil and environmental applications has a significant economic impact on reservoir management. However, the determination of optimal well locations is both challenging and computationally expensive. The overall goal of this research is to use the emerging Grid infrastructure to realize an autonomic self-optimizing reservoir framework. In this paper, we present a policy-driven peer-to-peer Grid middleware substrate to enable the use of the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm, coupled with the Integrated Parallel Accurate Reservoir Simulator (IPARS) and an economic model to find the optimal solution for the well placement problem.

A Study of Discovery Mechanisms for Peer-to-Peer Applications

Peer-to-peer applications allow peers to connect or disconnect from a network at any time and are based on a loosely coupled resource distribution model. As a result, robust and efficient discovery mechanisms are central to the efficient functioning of such applications. In this paper we evaluate four discovery mechanisms (flooding and the forward routing algorithms CHORD, Pastry and CAN) against the requirements of three prevalent classes of peer-to-peer applications, and investigate the suitability of these mechanisms for the applications.

Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies

This paper presents the use of numerical simulations coupled with optimization techniques in oil reservoir modeling and production optimization. We describe three main components of an autonomic oil production management framework. The framework implements a dynamic, data-driven approach and enables Grid-based large scale optimization formulations in reservoir modeling.

Autonomic oil reservoir optimization on the Grid

The emerging Grid infrastructure and its support for seamless and secure interactions is enabling a new generation of autonomic applications where the application components, Grid services, resources, and data interact as peers to manage, adapt and optimize themselves and the overall application. In this paper we describe the design, development and operation of a prototype of such an application that uses peer‐to‐peer interactions between distributed services and data on the Grid to enable the autonomic optimization of an oil reservoir. Copyright

Enabling autonomic grid applications: requirements, models and infrastructure

The increasing complexity, heterogeneity and dynamism of emerging pervasive Grid environments and applications has necessitated the development of autonomic self-managing solutions, which are based on strategies used by biological systems to deal with similar challenges of complexity, heterogeneity, and uncertainty. This paper introduces Project AutoMate and describes its key components. The overall goal of Project Automate is to investigate conceptual models and implementation architectures that can enable the development and execution of such self-managing Grid applications. Two applications enabled by AutoMate are also described.

Towards dynamic data-driven management of the ruby gulch waste repository

Previous work in the Instrumented Oil-Field DDDAS project has enabled a new generation of data-driven, interactive and dynamically adaptive strategies for subsurface characterization and oil reservoir management. This work has led to the implementation of advanced multi-physics, multi-scale, and multi-block numerical models and an autonomic software stack for DDDAS applications. The stack implements a Grid-based adaptive execution engine, distributed data management services for real-time data access, exploration, and coupling, and self-managing middleware services for seamless discovery and composition of components, services, and data on the Grid. This paper investigates how these solutions can be leveraged and applied to address another DDDAS application of strategic importance – the data-driven management of Ruby Gulch Waste Repository.

Autonomic optimization of an oil reservoir using decentralized services

The Grid community is actively working on defining,deploying and standardizing protocols, mechanisms,and infrastructure to support decentralized, seamless,and secure interactions across distributed resources.Such an infrastructure will enable a new generationof autonomic applications where the application components,Grid services, resources and data interact aspeers. In this paper we describe the development andoperation of a prototype application that uses such peer-to-peer interactions between services on the Grid to enablethe autonomic optimization of an oil reservoir.

Enabling Peer-to-Peer Interactions for Scientific Applications on the Grid

P2P and Grid communities are actively working on deploying and standardizing infrastructure, protocols, and mechanisms, to support decentralized interactions across distributed resources. Such an infrastructure will enable new classes of applications based on continuous, seamless and secure interactions, where the application components, Grid services, resources and data interact as peers. This paper presents the design, implementation and evaluation of a peer-to-peer messaging framework that builds on the JXTA protocols to support the interaction and associated messaging semantics required by these applications.