Application-Defined Network

1. Application-Defined Network iRODS Optimization of Data Routing on Software-Defined Networks Hao Xu and Shu Huang, Yufeng Xin, Leesa Brieger, Reagan Moore and Arcot Rajasekar

2. iRODS Meets Software-Defined Networks • iRODS (integrated Rule-Oriented Data System) • Data grid middleware • Policy-based data operations and management • SDN (Software-Defined Network) • Separate the control from data forwarding to make the network programmable • Two rule-based systemscommunicating to optimize performance • A new paradigm: applications direct the network (Application-Defined Network) iRODS rules: if condition(data) do: copy(data, from, to) Openflow rules: if matches(packet) do: forward(packet, output_port)

3. iRODS Data Grid iRODS View of Distributed Data User Client User sees a single collection My Data: disk, filesystem, site-specific storage, ... My Data: tape, database, filesystem, ... Partner’s Data remote disk, tape, filesystem, site-specific storage,… • iRODS installs over heterogeneous data resources • Users can share & manage distributed data as a single collection

4. iRODS Policy Implementation Microservices and Rules • Microservice – the functional unit of work (C programs) • Rules – workflows of microservices (and rules) • Provide server-side (data-side) services • Event-triggered rule execution (PEP: Policy Enforcement Points)

5. ExoGENI • A GENI testbed • Links GENI to open cloud computing (OpenStack) and dynamic circuit fabrics • Provides a networked infrastructure-as-a-service (NIaaS) platform • flexible networking operations using traditional VLAN-based switching and OpenFlow • Uses ORCA (Open Resource Control Architecture) control framework software • Served as testbed for this demo Presentation title goes here

6. Resource Provisioning -- ExoGENI

7. iRODS meets SDN • From tradition waterfall model to workflow model: tie together the network and the data management components of the infrastructure Application Management Network Management Data Management Polices Storage Resource Management Computation Resource Management

8. Multiple Possible Paths Between Nodes Presentation title goes here

9. Allow iRODS to Control Routing(Parallel Transfer) • Parallel transfer can be enhanced • independent routes for individual threads • adapt independently to network traffic • New PEP (policy enforcement points) trigger the network control mechanism iRODS OpenFlow • iRODS gets network state information from the Graph DB • iRODS rules direct OpenFlow to optimize the routes of the threads Presentation title goes here

10. Unification of data and network rules Rule Engine Data Policies Network Policies iCAT DB GraphDB OF Controller iRODS Server iRODS Server iRODS Server

11. New iRODS PEPs and Actions Network Rules irepl -R demoResc 100m: for each thread: Compute Shortest Path Data Rules Generate OpenFlow Rules acPreProcForServerPortal Update Link Cost Save OpenFlow Rule Info Transfer Thread Load OpenFlow Rule Info acPostProcForServerPortal Delete OpenFlow Rules Update Link Cost

12. Without the parallel trigger on network control, three active nodes: $time irepl -R demoResc 100m : 1m28.198s With iRODS network control, 8 active nodes: $time irepl -R demoResc 100m : 0m44.198s

13. Demo: data movement