The Brokering Approach STEFANO NATIVI (CNR-IIA), MAX CRAGLIA - - PowerPoint PPT Presentation

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The Brokering Approach STEFANO NATIVI (CNR-IIA), MAX CRAGLIA - - PowerPoint PPT Presentation

Nov 05, 2023 277 likes •556 views

Citizens Science and Smart Cities JRC Ispra 5-7 February 2014 The Brokering Approach STEFANO NATIVI (CNR-IIA), MAX CRAGLIA (EC-JRC) AND MATTIA SANTORO (CNR-IIA) Rationale Build Network of Networks Large or complex networks

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The Brokering Approach

STEFANO NATIVI (CNR-IIA), MAX CRAGLIA (EC-JRC) AND MATTIA SANTORO (CNR-IIA)

Citizens’ Science and Smart Cities JRC –Ispra 5-7 February 2014

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nativi@iia.cnr.it nativi@iia.cnr.it

Rationale

  • Build «Network of Networks»
  • Large or complex networks
  • Heterogeneous networks
  • Independent networks
  • Evolving networks
  • Reuse/share of (open) data
  • Heterogeneity
  • Technology
  • Domain/Goal
  • Organization
  • Maturity level
  • Policy
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Network of Networks Principles

Build on existing (Community) network/system/ infrastructures Supplement but not supplant network/system (i.e. Community) mandates and governance arrangements Address heterogeneity to lower barriers avoiding to impose any common (federal) technology Be flexible and extensible to

  • Interconnect new network/system (Community)
  • Sustain and advance the achieved interoperability
  • Allow each network/system (i.e. Community) to evolve
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THE EUROGEOSS LEGACY

Network of Networks Interoperability

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Two main (complementary) approaches

  • Standardization

Controlled and mature environments

  • Intermediation (i.e. System Brokering)
  • Heterogeneous and

rapidly-evolving environments

Interoperability Approaches

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The Brokerage Approach

INTERMEDIATION OF EXISTING NETWORKS AND COMMUNITIES

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Network interoperability

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Network service bus Network service bus Network service bus Network service bus

.. .

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Interoperability with «Authoritative Systems»

.. .

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Network service bus Network service bus Network service bus Network service bus

.. .

Brokering Infrastructure

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empowered by

Brokering Framework

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Brokering Benefits

Lowers barriers to participation in distributed systems for both users and resource providers

  • minimal burden or cost impact on existing systems;

Accelerates interconnection of disparate systems; Facilitates sustainability, reusability, extensibility, and flexibility of the infrastructure Enhances cross-domain interoperability via introduction of new capabilities across multiple domains; Removes need to impose common (e.g. federal, “top-down”) specifications and software components enabling a more adaptive “bottom-up” evolution of the infrastructure

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Brokering Challenges

Scalability

  • Intermediation services introduce a overhead

Governance

  • A new service layer is introduced: it must be a third party

infrastructure

  • Brokering agreements
  • Trustiness

Sustainability

  • A Bokering layer is a complex piece of technology
  • Evolve along with Community standards and Best Practices
  • Business model
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Projects dealing with Brokering technology

APPLYING, ADVANCING AND BUILDING ON A BROKERING FRAMEWORK

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Facin ing Scala labilit bility

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Current Assets

GEO Home Page GEOSS Portal

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Current Assets

About 20 brokered data providers – capacities, systems, Communities .. . More than 7 Million (1.2 Million GEOSS Data Core) Discoverable and potentially Accessible aggregated resources (mix of data collections, datasets and individual images) .. .

Publish Contain [source: data providers]

More than 65 Million (50 Million GEOSS Data Core) Discoverable and potentially Accessible individual resources (e.g. satellite scenes, rain gauge records)

.. .

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GEO DAB in the Cloud …

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GEO DAB Cloud capabilities

Load Balancing

  • Each DAB component is replicated on multiple machines
  • Amazon Load Balancers take care of routing requests to machines with lighter loads
  • New machine can be added on-the-fly as needed

Tiles and Data Caches

  • DAB makes use of Hadoop-based solutions for storing and retrieving maps and

data.

Monitoring system usage and resource consuming (number of queries, use of CPU, memory, etc.) Store user’s queries and selections to improve ranking of results (under development)

Elastic Load Balancing Instance with CloudWatch

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Typical Configuration

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Ranking Metrics applied by DAB

  • A weight-based algorithm rewarding a set of criteria

belonging to four high-level principles

  • Data accessibility & quality of service
  • GEOSS SBA Essential Variables
  • GEOSS Data Core
  • Metadata Completeness
  • The solution applied by DAB

is configurable and flexible

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Study dyin ing g G Governance ance & & Sustain inabili ability ty

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BC BCUBE

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