Cees de Laat

Addressing big data issues in Scientific Data Infrastructure

Big Data are becoming a new technology focus both in science and in industry. This paper discusses the challenges that are imposed by Big Data on the modern and future Scientific Data Infrastructure (SDI). The paper discusses a nature and definition of Big Data that include such features as Volume, Velocity, Variety, Value and Veracity. The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science. The paper proposes the SDI generic architecture model that provides a basis for building interoperable data or project centric SDI using modern technologies and best practices. The paper explains how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services provisioning model and suggests the major infrastructure components for Big Data.

TransLight: a global-scale LambdaGrid for e-science

This global experiment wants to see if high-end applications needing transport capacities of multiple Gbps for up to hours at a time can be handled through an optical bypass network.

Defining architecture components of the Big Data Ecosystem

Big Data are becoming a new technology focus both in science and in industry and motivate technology shift to data centric architecture and operational models. There is a vital need to define the basic information/semantic models, architecture components and operational models that together comprise a so-called Big Data Ecosystem. This paper discusses a nature of Big Data that may originate from different scientific, industry and social activity domains and proposes improved Big Data definition that includes the following parts: Big Data properties (also called Big Data 5V: Volume, Velocity, Variety, Value and Veracity), data models and structures, data analytics, infrastructure and security. The paper discusses paradigm change from traditional host or service based to data centric architecture and operational models in Big Data. The Big Data Architecture Framework (BDAF) is proposed to address all aspects of the Big Data Ecosystem and includes the following components: Big Data Infrastructure, Big Data Analytics, Data structures and models, Big Data Lifecycle Management, Big Data Security. The paper analyses requirements to and provides suggestions how the mentioned above components can address the main Big Data challenges. The presented work intends to provide a consolidated view of the Big Data phenomena and related challenges to modern technologies, and initiate wide discussion.

Addressing Big Data challenges for Scientific Data Infrastructure

This paper discusses the challenges that are imposed by Big Data Science on the modern and future Scientific Data Infrastructure (SDI). The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics in data management in modern e-Science. The paper proposes the SDI generic architecture model that provides a basis for building interoperable data or project centric SDI using modern technologies and best practices. The paper explains how the proposed models SDLM and SDI can be naturally implemented using modern cloud based infrastructure services provisioning model.

Using RDF to describe networks

Conventions such as iGrid 2005 and SuperComputing show that there is increasing demand for more service options on networks. For such networks, large teams of experts are needed to configure and manage them. In order to make the full potential of hybrid networks available to the ordinary user, the complexity must be reduced.This paper presents the idea of the Network Description Language (NDL), which builds on Semantic Web techniques to create a distributed Topology Knowledge Base (TKB). The TKB can provide a collection of reachability graphs, showing connectivity rules among physical and/or virtual entities.Latching onto the Semantic Web provides network management with a new breed of tools--bots, compilers, browsers, both commercial off-the-shelf (COTS) and open source. The approach appears to be applicable to the Global Lambda Integrated Facility (GLIF) as well as other experimental communities.

A distributed topology information system for optical networks based on the semantic web

The research networking community has embraced novel network architectures to provide e-Science applications with dedicated connections instead of shared links. IP and optical services converge in these new infrastructures to form hybrid networks. Lightpaths are the services offered to clients in the optical portion of the network. They are chosen because they guarantee the appropriate QoS in terms of bandwidth and latency. NDL-the Network Description Language-is a data model offering users and providers of lightpaths with a common ontology to describe topology information of hybrid optical networks. The strength of NDL is that it supports a wide range of applications, including pathfinding, visualisation and asset management, via the definition of a common data model to exchange network descriptions. Since NDL is based on the Semantic Web techniques, it is straightforward to relate NDL with application-specific ontologies. In this paper we present the current status of the NDL schemas and its use in several applications.

The rationale of the current optical networking initiatives

The future of networking is to move to an entirely optical infrastructure. Several leading National Research Networking organizations are creating test-beds to pilot the new paradigm. This paper explores some thoughts about the different usage models of optical networks. Different classes of users are identified. The services, required by the Internet traffic from those different classes of users, are analysed and a differentiated Internet architecture is proposed to minimize the cost per transported packet for the whole architecture.

Towards an Infrastructure Description Language for Modeling Computing Infrastructures

This paper describes the Infrastructure and Network Description Language (INDL). The aim of INDL is to provide technology independent descriptions of computing infrastructures. These descriptions include the physical resources and the network infrastructure that connects these resources. The description language also provides the necessary vocabulary to describe virtualization of resources and the services offered by these resources. Furthermore, the language can be easily extended to describe federation of different existing computing infrastructures, specific types of (optical) equipment and also behavioral aspects of resources, for example, their energy consumption. Before we introduce INDL we first discuss a number of modeling efforts that have lead to the development of INDL, namely the Network Description Language, the Network Markup Language and the CineGrid Description Language. We also show current applications of INDL in two EU-FP7 projects: NOVI and GEYSERS. We demonstrate the flexibility and extensibility of INDL to cater the specific needs of these two projects.

Intercloud Architecture for interoperability and integration

This paper presents on-going research to develop the Intercloud Architecture Framework (ICAF) that addresses problems in multi-provider multi-domain heterogeneous cloud based infrastructure services and applications integration and interoperability. The paper refers to existing standards in Cloud Computing, in particular, recently published NIST Cloud Computing Reference Architecture (CCRA). The proposed ICAF defines four complementary components addressing Intercloud integration and interoperability: multilayer Cloud Services Model that combines commonly adopted cloud service models, such as IaaS, PaaS, SaaS, in one multilayer model with corresponding inter-layer interfaces; Intercloud Control and Management Plane that supports cloud based applications interaction; Intercloud Federation Framework, and Intercloud Operation Framework. The paper briefly describes the architectural framework for cloud based infrastructure services provisioned on-demand being developed in the framework of the GEYSERS project that is used as a basis for building multilayer cloud services integration framework that allows optimized provisioning of both computing, storage and networking resources. The proposed architecture is intended to provide an architectural model for developing Intercloud middleware and in this way will facilitate clouds interoperability and integration.

Editorial: Special section: OptIPlanet - The OptIPuter global collaboratory

The technological developments made by OptIPuter research project as an OptIPlanet Collaboratory of virtual organizations, in various scientific and technology domains, enhancing and contributing to this evolving cyberinfrastructure to solve complex global problems, are summarized. OptIPuter project has developed an optical control plane, an infrastructure and distributed intelligence, to control the establishment and maintenance of connections in a network and algorithms for engineering an optimal path among endpoints. The Scalable Adaptive Graphics Environment (SAGE) visualization middleware developed by OptIPuter partner Electronic Visualization Laboratory, is an operating system for tiled-display environments, which allows users to launch distributed visualization applications on remote computer clusters.