Ralph Koning

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The recent emergence of advanced network infrastructures for e-Science enables tuning of network performance at the application level. The Network Service Interface (NSI) has been created as a result of collaborative development of network and application engineers primarily associated with the Research and Education (R&E) community. The NSI allows(More)
The ever increasing demands of data intensive eScience applications have pushed the limits of computer networks. With the launch of the new 40 Gigabit Ether-net(40GE) standard, 802.3ba, applications can go beyond the common 10 Gigabit/s per data stream barrier for both local area, and as demonstrated in the GLIF 2010 and Supercomputing 2010 demos[3], wide(More)
Linux container virtualisation is gaining momentum as lightweight technology to support cloud and distributed computing. Applications relying on container architectures might at times rely on inter-container communication, and container networking solutions are emerging to address this need. Containers can be networked together as part of an overlay(More)
This paper presents results of the ongoing development of the Open Cloud eXchange (OCX) that has been proposed in the framework of the GN3plus project. Its aim is to provide cloud aware network infrastructure to power and support modern data intensive research at European universities and research organisations. The paper describes the OCX concept,(More)
Advanced network infrastructure plays an important role in the e-Science environment to provide high quality connections between largely distributed data sensors, and computing and storage elements. However, the quality of the network services has so far rarely been considered in composing and executing scientific workflows. Currently, scientific(More)
The ever increasing demands of data intensive eScience applications have pushed the limits of computer networks. With the launch of the new 40 Gigabit Ethernet standard , 802.3ba, applications can go beyond the common 10 Gigabit/s per data stream barrier for both local area and, as it shall be presented in this report, wide area setups. This report focuses(More)
The quality of the network services has so far rarely been considered in composing and executing scientific workflows. Currently, scientific applications tune the execution quality of workflows neglecting network resources, and by selecting only optimal software services and computing resources. One reason is that IP-based networks provide few possibilities(More)
Many scientific workflow applications are driven by simulation generated data, or data collected from sensors or instruments, and the processing of the data is commonly done at a different location from where the data is stored. Moving large quantities of data among different locations is thus a frequently invoked process in scientific workflow(More)