Matthew Arrott

Rich Services: The Integration Piece of the SOA Puzzle

One of the key challenges to successful systems-of- systems integration using Web services technologies is how to address crosscutting architectural concerns such as policy management, governance, and authentication, while still maintaining the lightweight implementation and deployment flavor that distinguishes Web services from earlier attempts at providing interoperable enterprise systems. To address this challenge, this article introduces the notion of a Rich Service, an extension of the standard service notion, based on an architectural pattern that allows hierarchical decomposition of system architecture according to separate concerns. Rich Services enable the capture of different system aspects and their interactions. By leveraging emerging Enterprise Service Bus technologies, Rich Services also enable a direct transition from a logical to a deployed service-oriented architecture (SOA). This results in immediate benefits not only in SOA design, implementation, deployment, and quality assurance, but also in the traceability of architectural requirements to an SOA implementation.

Engineering Foreign Exchange Processes via Commitment Protocols

Foreign exchange (FX) markets see a transaction volume of over

Cyberinfrastructure for the US Ocean Observatories Initiative: Enabling interactive observation in the ocean

2 trillion per day. A number of standard ways of conducting business have been developed in the FX industry. However, current FX specifications are informal and their business semantics unclear. The resulting implementations tend to be complex and compliance with the standards unverifiable. This results in potential loss of value due to incompatible business processes and possible trades not consummated. This paper validates a formal, protocol-based approach by specifying foreign exchange processes as standardized by the TWIST consortium. The proposed approach formalizes a small, core set of foreign exchange interaction protocols on which the desired processes can be based. The core protocols can be composed to yield a large variety of possible processes. Each protocol is rigorously defined in terms of the commitments undertaken and manipulated by the parties involved. By contrast, traditional approaches as used in the current TWIST specification lead to redundancy in specification and difficulty in understanding the import of the interactions involved. In addition, our approach discovered interesting business scenarios that traditional approaches would have missed.

Serving ocean model data on the cloud

The Ocean Observatories Initiative (OOI) is an environmental observatory covering a diversity of oceanic environments, ranging from the coastal to the deep ocean. Construction is planned to begin in mid-2010 with deployment phased over five years. The key integrating element of the OOI is a comprehensive cyberinfrastructure whose design is based on loosely coupled distributed services, and whose elements are expected to reside throughout the OOI observatories, from seafloor instruments to deep sea moorings to shore facilities to computing and archiving infrastructure. There are six main components to the design comprising the core capability container, consisting of four elements providing services for users and distributed resources and two infrastructural elements providing core services. The Sensing and Acquisition component provides capabilities to acquire data from and manage distributed seafloor instrument resources, including their interactions with the infrastructure power, communication and time distribution networks. The Data Management component provides capabilities to distribute and archive data, including cataloging, versioning, metadata management, and attribution and association services. The Analysis and Synthesis element provides a wide range of services to users, including control and archival of models, event detection, quality control services and collaboration capabilities to create virtual laboratories and classrooms. The Planning and Prosecution element gives the ability to plan, simulate and execute observation missions using taskable instruments, and turns the OOI into an interactive observatory. The remaining elements are the Common Operating Infrastructure that provides core services to manage distributed, shared resources in a policy-based framework. It includes capabilities for efficient and scalable communication, to manage identity and policy, manage the resource life cycle, and catalog/repository services for observatory resources. The Common Execution Infrastructure provides an elastic computing framework to initiate, manage and store processes that may range from initial operations on data at a shore station to the execution of a complex numerical model on the national computing infrastructure, and on compute clouds.

The Uses of Norms

The NOAA-led Integrated Ocean Observing System (IOOS) and the NSF-funded Ocean Observatories Initiative Cyberinfrastructure Project (OOI-CI) are collaborating on a prototype data delivery system for numerical model output and other gridded data using cloud computing. The strategy is to take an existing distributed system for delivering gridded data and redeploy on the cloud, making modifications to the system that allow it to harness the scalability of the cloud as well as adding functionality that the scalability affords.

Ocean Observatories and Information: Building a Global Ocean Observing Network

This chapter presents a variety of applications of norms. These applications include governance in sociotechnical systems, data licensing and data collection, understanding software development teams, requirements engineering, assurance, natural resource allocation, wireless grids, autonomous vehicles, serious games, and virtual worlds.

Cyberinfrastructure for the US Ocean Observatories Initiative

Ocean observatories are collections of networks of sensors that are deployed to sample the ocean physics, chemistry, and biology. The goal of these networks is to overcome chronic undersampling of the oceans by providing sustained measurements in space and time. The data collected by these networks are used to address a range of basic and applied research questions, hindered by a lack of data. The ocean observatories represent collections of platforms capable of collecting data over a range of scales. The platforms include ships, satellites, radars, and a range of Lagrangian systems. Data from the individual platforms are aggregated by sophisticated cyberinfrastructure software systems, which when combined with global communications allow for two-way communication between the shoreside personnel and the networks that can be deployed anywhere in the world. This two-way communication allows the networks to be adaptively configured to improve sampling of specific processes. The maturation of these systems comes at a fortuitous time as the oceans are increasingly showing evidence of changes in the physics, chemistry, and biology over the last few decades. Understanding those changes will require the data collected by the ocean observatories.

OCean Observatories Initiative Scientific Data Model

The US National Science Foundations Ocean Observatories Initiative (OOI) is an environmental observatory covering a diversity of oceanic environments, ranging from the coastal to the deep ocean. The key integrating element of the OOI is a comprehensive cyberinfrastructure (CI) that is a substantial departure from previous approaches that will have a significant impact on oceanography over the next twenty years. This paper provides a high-level overview of the CI architecture, as well as the integration and deployment strategies that will ensure its success.

Towards an Autonomous Space In-situ Marine Sensorweb

The Ocean Observatories Initiative (OOI) through its Cyberinfrastructure (CI) Implementing Organization is developing a next generation platform for ocean sciences that will integrate a wide variety of information resources at scales unattainable before in the earth and ocean sciences. We introduce a novel scientific data model that enables distributed, large-scale storage and query of science data. Our model is built on multiple levels of abstraction ranging from domain-specific at the top down to encodings for message-oriented transport and persistence at the base. The key is exposing the properties of scientific feature types separately from the underlying structure of the data, which in turn is separated from their representation. The data representation is further isolated from the serialization and encoding used for transport and persistence. Our model greatly simplifies expressions of provenance and versioning of various data entities. It is robust, scalable and reliable. We implemented it for the first release of the OOI Integrated Observatory Network (ION), with rollout to operations currently underway.

Building transparent data access for ocean observatories: Coordination of U.S. IOOS DMAC with NSF's OOI Cyberinfrastructure

We describe ongoing efforts to integrate and coordinate space and marine assets to enable autonomous response to dynamic ocean phenomena such as algal blooms, eddies, and currents. Thus far we have focused on the use of remote sensing assets (e.g. satellites) but future plans include expansions to use a range of in-situ sensors such as gliders, autonomous underwater vehicles, and buoys/moorings.