GENI Experiments in Optimizing Network Environments using XSP Ezra Kissel and Martin Swany University of Delaware Abstract Our proposal is to build, deploy.

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GENI Experiments in Optimizing Network Environments using XSP Ezra Kissel and Martin Swany University of Delaware Abstract Our proposal is to build, deploy and study an Optimizing Network Environment (ONE) based on our eXtensible Session Protocol (XSP) within the NSF's Global Environment for Network Innovation (GENI.) Our approach for this work is based on a new layer of protocols and services that exists architecturally atop the current Internet architecture, while incorporating support for emerging technologies like the reconfigurable networks enabled by GMPLS and Passive Optical Networks (PONs.) To this end, we have designed ONE, which is an architecture that enables network adaptation using network service gateways and more visibility and control of the underlying infrastructure. Research Objectives We intend to investigate a network service-oriented framework on GENI that allows future experiments based on the expressive power of our session- based network inlay. A number of proposed experiments will exercise the XSP and ONE concept and will utilize a number of existing GENI components as well as unique resources such as the Supercharged Planetlab Platform (SPP). We intend to address a number of network research problems in this exploratory work: Routing, pathfinding, and intelligent resource allocation algorithms Current and Proposed Publications Our research efforts have resulted in the following publications: [1] Session Layer Burst Switching for High Performance Data Movement. Kissel, E., Swany, M. In Proceedings of PFLDNet The proposed research effort hopes to result in the following theses/dissertations: [2] Improving WAN Performance with XSP – A Protocol for New Internet Architectures. Ezra Kissel, PhD Dissertation, Expected 2012 Acknowledgements Internet2 – Matt Zekauskas, Jason Zurawski Utah Emulab – Rob Ricci, Leigh Stoller GPO/BBN – Mark Berman, Tom Mitchell Use of GENI Infrastructure Our running experiments utilize some of the currently available GENI resources including Emulab PCs and backbone nodes and Planetlab virtual PCs. We were able to achieve the ability to create ION circuits between ProtoGENI backbone nodes and existing PGs, which we plan to further evaluate in future testing. We have also investigated some of the I&M systems (LAMP and INSTTOOLS) under development in order to instrument our experiments and provide measurement feedback. As a result of this early testing, we have identified the ability to allocate and setup a stable set of resources as a major challenge in performing long- term experiments. Existing resources are often being contended for among developers and other experimenters alike, which does makes the process exciting. We expect to take advantage of additional unique GENI resources as they become more fully integrated and available. Initial Experiments Phoebus-XSP “Inlay”– Providing location- independent access to private experiment network resources remains a challenge. We have investigated a solution where XSP has the ability to “stitch” various GENI components via transparent pathfinding and forwarding over Phoebus Gateways (PGs). XSP establishes a communication session with the PG currently mapping the specified endpoint ID (e.g. RFC1918 address) allowing external hosts the ability to access a GENI experiment as if they were on the same network. Our experiment has tested this functionality across existing ProtoGENI and Planetlab resources. Adapting to Network Conditions – Utilizing the inlay described above, we evaluated the ability of PGs to accelerate transfers over ION and ProtoGENI backbone resources. Phoebus implements protocol translation and adaptation that can significantly improve performance over LFNs and challenged network paths. Our early testing shows a % improvement when utilizing the Phoebus-XSP approach for common network transfer tools and benchmarks such as GridFTP and iperf (Figure 1). Future experiments will allow PGs to select optimal paths based on prevailing network conditions. 1 st DFG/GENI Doctoral Consortium, San Juan, PR March 13 th -15 th, 2011 pg Phoebus Gateway (At Internet2 PoPs) ProtoGENI backbone node (Running Phoebus Gateway) 1G experiment tunnel 1G ION circuit Utah exp /24 headnode LBL GridFTP UDEL GridFTP pg PL WestPL EastPL South GENI stitching via XSP and Phoebus e.g.: ‘ssh headnode’ Fig 2: SLaBS versus direct transfers with increasing latency. 4 parallel GridFTP streams competing for 5G bottleneck link [1]. Fig 1: GridFTP and iperf transfers between UDEL and LBL. Direct connections compared to using Phoebus-XSP inlay over ION and Protogeni backbone tunnels. Session Layer Burst Switching – Our previous SLaBS work [1] demonstrates the ability of an intelligent buffer-and-burst approach to improve transfer performance over dedicated and bottleneck network paths. To avoid contention and increase utilization, XSP enables framing of incoming flows into “right-sized” bursts that can be intelligently scheduled for transmission across a network of SLaBS devices (PGs). Figure 2 shows SLaBS performance on a 10G network testbed. Our proposed experiments aim to evaluate SLaBS fast-path optimizations using programmable network resources such as NetFPGAs and SPP. We intend to investigate distributed SLaBS burst scheduling approaches across the available dynamic backbone resources and existing PGs. Empirical evaluation of performance benefits over a wide variety of network conditions and applications Investigation of scalability of the architecture, including forwarding performance, state management and authentication Provide location and identification separation via XSP and session-aware network gateways Acting on network measurement and topology information to optimize network performance and access Future Work Extend Phoebus-XSP inlay to configure Openflow switches and other configurable network devices Develop SLaBS “fast path” support using programmable hardware platforms and RDMA Integrate with I&M systems and actively use measurement feedback and topology information Explore optimizing wireless node and sensor mote communications over wide area networks