An Architecture for Data Intensive Service Enabled by Next Generation Optical Networks
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The document discusses the challenges posed by growing data-intensive applications and presents the DWDW-RAM architecture, which is designed to leverage next-generation optical networks for high-performance data flow and scalability. It introduces concepts like lambda data grids and dynamic lightpath provisioning, demonstrating their effectiveness through experimental setups. The findings suggest that traditional network infrastructures are inadequate for current demands, highlighting the necessity for more advanced optical solutions.
An Architecture for Data Intensive Service Enabled by Next Generation Optical Networks
- 1. DWDM RAM Data@LIGHTspeed An Architecture for Data Intensive Service Enabled by Next Generation Optical Networks Tal Lavian : Nortel Networks Labs Nortel Networks International Center for Advanced Internet Research (iCAIR), NWU, Chicago Santa Clara University, California University of Technology, Sydney NNTTOONNC C
- 2. Agenda • Challenges – Growth of Data-Intensive Applications • Architecture – Lambda Data Grid • Lambda Scheduling • Result – Demos and Experiment • Summary
- 3. Radical mismatch: L1 – L3 • Radical mismatch between the optical transmission world and the electrical forwarding/routing world. • Currently, a single strand of optical fiber can transmit more bandwidth than the entire Internet core • Current L3 architecture can’t effectively transmit PetaBytes or 100s of TeraBytes • Current L1-L0 limitations: Manual allocation, takes 6-12 months - Static. – Static means: not dynamic, no end-point connection, no service architecture, no glue layers, no applications underlay routing
- 4. Growth of Data-Intensive Applications • IP data transfer: 1.5TB (1012) , 1.5KB packets – Routing decisions: 1 Billion times (109) – Over every hop • Web, Telnet, email – small files • Fundamental limitations with data-intensive applications – multi TeraBytes or PetaBytes of data – Moving 10KB and 10GB (or 10TB) are different (x106, x109) – 1Mbs & 10Gbs are different (x106)
- 5. Lambda Hourglass • Data Intensive app requirements – HEP – Astrophysics/Astronomy – Bioinformatics – Computational Chemistry • Inexpensive disk – 1TB < $1,000 • DWDM – Abundant optical bandwidth • One fiber strand – 280 λs, OC-192 CERN 1-PB Data-Intensive Applications Lambda Data Grid Abundant Optical Bandwidth 2.8 Tbs on single fiber strand
- 6. DWDM RAM Data@LIGHTspeed Challenge: Emerging data intensive applications require: Extremely high performance, long term data flows Scalability for data volume and global reach Adjustability to unpredictable traffic behavior Integration with multiple Grid resources Response: DWDM-RAM - An architecture for data intensive Grids enabled by next generation dynamic optical networks, incorporating new methods for lightpath provisioning
- 7. DWDM RAM Data@LIGHTspeed DWDM-RAM: An architecture designed to meet the networking challenges of extremely large scale Grid applications. Traditional network infrastructure cannot meet these demands, especially, requirements for intensive data flows DWDM-RAM Components Include: •Data management services •Intelligent middleware •Dynamic lightpath provisioning •State-of-the-art photonic technologies •Wide-area photonic testbed implementation
- 8. Agenda • Challenges – Growth of Data-Intensive Applications • Architecture – Lambda Data Grid • Lambda Scheduling • Result – Demos and Experiment • Summary
- 9. Northwestern U 4x10G E Optical Switching Platform Passport 8600 Application Cluster UIC 8x1GE 4x10GE Application Cluster Application Cluster Optical Switching Platform Optical Switching Platform Passport 8600 OPTera Metro 5200 StarLight Passport 8600 4x10GE CA*net3--Chicago Optical Switching Platform Passport 8600 • A four-node multi-site optical metro testbed network in Chicago -- the first 10GE service trial! • A test bed for all-optical switching and advanced high-speed services • OMNInet testbed Partners: SBC, Nortel, iCAIR at Northwestern, EVL, CANARIE, ANL Closed loop 8x1GE 4x10GE 8x1GE 8x1GE Loop OMNInet Core Nodes
- 10. What is Lambda Data Grid? • A service architecture – comply with OGSA – Lambda as an OGSI service – on-demand and scheduled Lambda • GT3 implementation • Demos in booth 1722 Grid Computing Applications Grid Middleware Data Grid Service Plane Network Service Plane Centralize Optical Network Control Lambda Service
- 11. DWDM-RAM Service Control Architecture GRID Service Request Network Service Request ODIN OmniNet Control Plane Optical Control Network Optical Control Network UNI-N Data Transmission Plane ODIN UNI-N Connection Control L3 router L2 switch Service Control Data Path Control Data storage switch Data Path Control DDAATTAA G GRRIDID S SEERRVVICICEE P PLLAANNEE l1 ln Data Center l1 ln l1 ln Data Path Data Center Service Control NNEETTWWOORRKK S SEERRVVICICEE P PLLAANNEE
- 12. Data Path Control Connection Control Data storage switch Data Data Transmission Plane L3 router Center l1 ln l1 ln Data Path Data Center Applications Optical Control Plane Data Transfer Scheduler Storage Resource Service Dynamic Optical Network Basic Network Resource Service Other Services Processing Resource Service Network Resource Scheduler Basic Data Transfer Service Data Transfer Service External Services Network Transfer Service
- 13. Data Management Services •OGSA/OGSI compliant •Capable of receiving and understanding application requests •Has complete knowledge of network resources •Transmits signals to intelligent middleware •Understands communications from Grid infrastructure •Adjusts to changing requirements •Understands edge resources •On-demand or scheduled processing •Supports various models for scheduling, priority setting, event synchronization
- 14. Intelligent Middleware for Adaptive Optical Networking •OGSA/OGSI compliant •Integrated with Globus •Receives requests from data services •Knowledgeable about Grid resources •Has complete understanding of dynamic lightpath provisioning •Communicates to optical network services layer •Can be integrated with GRAM for co-management •Architecture is flexible and extensible
- 15. Dynamic Lightpath Provisioning Services •Optical Dynamic Intelligent Networking (ODIN) •OGSA/OGSI compliant •Receives requests from middleware services •Knowledgeable about optical network resources •Provides dynamic lightpath provisioning •Communicates to optical network protocol layer •Precise wavelength control •Intradomain as well as interdomain •Contains mechanisms for extending lightpaths through •E-Paths - electronic paths
- 16. Agenda • Challenges – Growth of Data-Intensive Applications • Architecture – Lambda Data Grid • Lambda Scheduling • Result – Demos and Experiment • Summary
- 17. Design for Scheduling • Network and Data Transfers scheduled • Data Management schedule coordinates network, retrieval, and sourcing services (using their schedulers) • Network Management has own schedule • Variety of request models • Fixed – at a specific time, for specific duration • Under-constrained – e.g. ASAP, or within a window • Auto-rescheduling for optimization • Facilitated by under-constrained requests • Data Management reschedules • for its own requests • request of Network Management
- 18. Example 1: Time Shift • Request for 1/2 hour between 4:00 and 5:30 on Segment D granted to User W at 4:00 • New request from User X for same segment for 1 hour between 3:30 and 5:00 • Reschedule user W to 4:30; user X to 3:30. Everyone is happy. D 3:30 4:00 4:30 5:00 5:30 W 3:30 4:00 4:30 5:00 5:30 D W 3:30 4:00 4:30 5:00 5:30 Route allocated for a time slot; new request comes in; 1st route can be rescheduled for a later slot within window to accommodate new request
- 19. Example 2: Reroute • Request for 1 hour between nodes A and B between 7:00 and 8:30 is granted using Segment X (and other segments) for 7:00 • New request for 2 hours between nodes C and D between 7:00 and 9:30 This route needs to use Segment E to be satisfied • Reroute the first request to take another path thru the topology to free up Segment E for the 2nd request. Everyone is happy A B D C X 7:00-8:00 A B D C Y X 7:00-8:00 Route allocated; new request comes in for a segment in use; 1st route can be altered to use different path to allow 2nd to also be serviced in its time window
- 22. Agenda • Challenges – Growth of Data-Intensive Applications • Architecture – Lambda Data Grid • Lambda Scheduling • Result – Demos and Experiment • Summary
- 23. Path Allocation Overhead as a % of the Total Transfer Time • Knee point shows the file size for which overhead is insignificant Setup time = 2 sec, Bandwidth=100 Mbps 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1 1 10 100 1000 10000 File Size (MBytes) Setup time / Total Transfer Time 1GB Setup time = 2 sec, Bandwidth=300 Mbps 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1 1 10 100 1000 10000 File Size (MBytes) Setup time / Total Transfer Time 5GB Setup time = 48 sec, Bandwidth=920 Mbps 0% 100 1000 10000 100000 1000000 10000000 File Size (MBytes) Setup time / Total Transfer Time 500GB
- 24. Packet Switched vs Lambda Network Setup time tradeoffs (Optical path setup time = 2 sec) 5000.0 4500.0 4000.0 3500.0 3000.0 2500.0 2000.0 1500.0 1000.0 500.0 250.0 200.0 150.0 100.0 50.0 0.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Time (s) Data Transferred (MB) Packet sw itched (300 Mbps) Lambda switched (500 Mbps) Lambda switched (750 Mbps) Lambda switched (1 Gbps) Lambda switched (10Gbps) Packet Switched vs Lambda Network Setup time tradeoffs (Optical path setup time = 48 sec) 0.0 0.0 20.0 40.0 60.0 80.0 100.0 120.0 Time (s) Data Transferred (MB) Packet switched (300 Mbps) Lambda switched (500 Mbps) Lambda switched (750 Mbps) Lambda switched (1 Gbps) Lambda switched (10Gbps)
- 25. Agenda • Challenges – Growth of Data-Intensive Applications • Architecture – Lambda Data Grid • Lambda Scheduling • Result – Demos and Experiment • Summary
- 26. Summary •Next generation optical networking provides significant new capabilities for Grid applications and services, especially for high performance data intensive processes •DWDM-RAM architecture provides a framework for exploiting these new capabilities •These conclusions are not only conceptual – they are being proven and demonstrated on OMNInet – a wide-area metro advanced photonic testbed
- 27. Thank you !
- 28. NRM OGSA Compliance OGSI interface GridService PortType with two application-oriented methods: allocatePath(fromHost, toHost,...) deallocatePath(allocationID) Usable by a variety of Grid applications Java-oriented SOAP implementation using the Globus Toolkit 3.0
- 29. Network Resource Manager • Presents application-oriented OGSI / Web Services interfaces for network resource (lightpath) allocation • Hides network details from applications •Implemented in Java Items in blue are planned
- 30. Scheduling : Extending Grid Services OGSI interfaces Web Service implemented using SOAP and JAX-RPC Non-OGSI clients also supported GARA and GRAM extensions Network scheduling is new dimension Under-constrained (conditional) requests Elective rescheduling/renegotiation Scheduled data resource reservation service (“Provide 2 TB storage between 14:00 and 18:00 tomorrow”) DWDM-RAM October 2003 Architecture Page 6
- 31. Lightpath Services Enabling High Performance Support for Data-Intensive Services With On-Demand Lightpaths Created By Dynamic Lambda Provisioning, Supported by Advanced Photonic Technologies OGSA/OGSI Compliant Service Optical Service Layer: Optical Dynamic Intelligent Network (ODIN) Services Incorporates Specialized Signaling Utilizes Provisioning Tool: IETF GMPLS New Photonic Protocols
- 32. Fiber Span Length KM MI NWUEN Link 1* 35.3 22.0 2 10.3 6.4 3* 12.4 7.7 4 7.2 4.5 5 24.1 15.0 6 24.1 15.0 7* 24.9 15.5 8 6.7 4.2 9 5.3 3.3 CAMPUS FIBER (16) CAMPUS FIBER (4) Grid OMNInet W Taylor Sheridan 1 l l l 10 GE 1 l l l 10/100/ Clusters GIGE 10 GE 10 GE To Ca*Net 4 Lake Shore 5200 OFA l 2 3 Optera 5200 OFA Photonic Node 5200 OFA NWUEN-8 NWUEN-9 S. Federal Photonic Node Photonic Node 10/100/ GIGE 10/100/ GIGE 10/100/ GIGE 10 GE Optera 5200 10Gb/s TSPR Photonic Node l4 PP 8600 10 GE PP 8600 PP 8600 2 3 4 l l l 1 Optera 5200 10Gb/s TSPR 10 GE Optera 5200 10Gb/s TSPR 2 3 4 l 10 GE Optera 5200 10Gb/s TSPR 1 l l l 2 3 4 l 1310 nm 10 GbE WAN PHY interfaces 10 GE PP 8600 … EVL/UIC OM5200 INITIAL CONFIG: 10 LAMBDA (all GIGE) LAC/UIC OM5200 StarLight Interconnect with other research networks 10GE LAN PHY (Dec 03) TECH/NU-E OM5200 CAMPUS FIBER (4) INITIAL CONFIG: 10 LAMBDAS (ALL GIGE) Optera Metro 5200 OFA NWUEN-1 NWUEN-5 NWUEN-2 NWUEN-6 NWUEN-3 NWUEN-4 NWUEN-7 Fiber in use Fiber not in use 5200 OFA • 8x8x8l Scalable photonic switch • Trunk side – 10 G WDM • OFA on all trunks
- 33. Fiber power Relative Relative l power code Tone Physical Layer Optical Monitoring and Adjustment Fault isolation Set point DSP Algorithms A/D Management & OSC Routing PPS Control Middleware D/A FLIP Rapid Detect OSC cct PhotoDetector PhotoDetector OFA tap D/A VOA Power measurement switch Switch Control AWG Temp. Control alg. + - D/A A/D Heater AWG & Measurement tap Drivers/data translation Connection verification Path ID Corr. Gain l Leveling Controller Transient compensator Power Corr. + - LOS + - Photonics Database 100FX PHY/MAC Splitter Photonic H/W
- 34. Summary (I) • Allow applications/services – to be deployed over the Lambda Data Grid • Expand OGSA – for integration with optical network • Extend OGSI – interface with optical control – infrastructure and mechanisms • Extend GRAM and GARA – to provide framework for network resources optimization • Provide generalized framework for multi-party data scheduling
- 35. Summary (II) • Treating the network as a Grid resource • Circuit switching paradigm moving large amounts of data over the optical network, quickly and efficiently • Demonstration of on-demand and advance scheduling use of the optical network • Demonstration of under-constrained scheduling requests • The optical network as a shared resource – may be temporarily dedicated to serving individual tasks – high overall throughput, utilization, and service ratio. • Potential applications include – support of E-Science, massive off-site backups, disaster recovery, commercial data replication (security, data mining, etc.)
- 36. Extension of Under-Constrained Concepts • Initially, we use simple time windows • More complex extensions – any time after 7:30 – within 3 hours after Event B happens – cost function (time) – numerical priorities for job requests Extend (eventually) concept of under- constrained to user-specified utility functions for costing, priorities, callbacks to request scheduled jobs to be rerouted/rescheduled (client can say yea or nay)