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Business Models for Dynamically Provisioned Optical Networks Tal Lavian DWDM RAM DWDM RAM Defense Advanced Research Projects Agency BUSINESS.

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Presentation on theme: "Business Models for Dynamically Provisioned Optical Networks Tal Lavian DWDM RAM DWDM RAM Defense Advanced Research Projects Agency BUSINESS."— Presentation transcript:

1 Business Models for Dynamically Provisioned Optical Networks Tal Lavian DWDM RAM DWDM RAM Data@LIGHTspeed Defense Advanced Research Projects Agency BUSINESS WITHOUT BOUNDARIES

2 Concept for “Utility” Bandwidth Low latency, high bandwidth services (>1Gb/s) are emerging requirements for business, medical, education, government and industry New applications development and business models could be stimulated by affordable and easily accessible high bandwidth in both local and wide area networks High bandwidth connections are typically full period today but full period 7x24 bandwidth is not always needed. Technologies are now available that suggest plausible new business model options to offer time slots for high bandwidth services –Dynamic provisioning of lambda and sub-lambda time slots –Periodically scheduled (N time slots per day, per week) or ad hoc

3 Application Profile A – Lightweight users, browsing, mailing, home use B – Current business applications, multicast, streaming, VPNs, mostly LAN C – Emerging business, government, industry & scientific applications, data grids, virtual-presence Network Profile A – Internet routing, one to many B – VPN services on/and full Internet routing, several to several C – Very fat pipes (both full and non-full period services), limited multiple Virtual Organizations, few to few BW requirements # of users A ADSL C A B GE User/Bandwidth Profile

4 Dynamic Wave Provisioning Service Business Model Examples Business Continuity/Disaster Recovery –Remote file storage/back-up –Recovery after equipment or path failure –Alternate site operations due to natural or man-made disaster Storage and data on demand –Rapid expansion of network attached storage capacity –Archival storage and retrievals –Logistical networking – pre-fetch and cache Financial community and transaction GRIDs –Distributed computational and storage resources –Shared use of very high bandwidth network resources –Utility computing for pay-as-you-go business models

5 100s of transactions per second Remote storage / processing location Dynamically provisioned carrier or large enterprise network – switched lambdas and sub-lambdas Core network is a shared resource SLAs for graduated performance Fixed time slots − Lambdas & sub-lambdas Dynamically allocated

6 Transaction GRID Demonstration Real-time transactions processed and buffered at collection sites for Businesses “BB” & “SRU” Periodic transfer to remote site for batch processing using fixed timeslot dynamic lambda provisioning High bandwidth/low holding time connection provides periodically scheduled shared use path between collection and remote sites.

7 Sheridan PP8600 Federal PP8600 1 x GE Taylor 10GE ( 1) 10GE ( 2) 7.2 km 6.7 km 10.3 km Lakeshore 10GE ( 3) 24.9 km 24.1 km Photonic Switch OMNInet PP8600 McCormick Place Demo Display Station LakeShoreHost (192.26.85.147/26) SheridanHost1 (192.26.85.169/26) SheridanHost2 (192.26.85.170/26) FederalHost (192.26.85.130/ 26) GRIDBRICK Advantage: By having this setup we have contention for Red λ2 between Lakeshore and Sheridan when App A & B try for the same timeslot. Media Converter/ Local Sw/hub Logical Demo Layout 100 Mbps ControlHost (129.105.25.103/24) NRM (129.105.220.101/24) ODIN (129.105.220.46/24) DemoSender1 DemoSender2 DemoReceiver1 DemoReceiver2 DemoControl nrm odinserver DemoGUI

8 Demonstration Parameters All parameters are dynamic and updated in real time ParameterUnits Transaction Collection RateRecords/sec Record sizeKbytes Queue LoadNumber of records Queue sizeKbytes Queue fill rateKbytes/sec Next queue deliveryDate:hour:min:sec Time to next queue deliveryHour:min:sec Last delivery average throughputKbps

9 DWDM-RAM Architecture Charts

10 DWDM-RAM Architecture Data Center 1 n 1 n Data Center Data-Intensive Applications Network Resource Scheduler Network Resource Service Data Handler Service Information Service Application Middleware Layer Network Resource Middleware Layer Connectivity and Fabric Layers  OGSI-ification API NRS Grid Service API DTS API Optical path control Data Transfer Service Dynamic Lambda, Optical Burst, etc., Grid services Basic Network Resource Service

11 DWDM-RAM Architecture Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

12 DWDM-RAM Architecture ODIN – Optical Domain Intelligent Network Software suite that controls the OMNInet through lower- level API calls Designed for high-performance, long-term flow with flexible and fine grained control Stateless server, which includes an API to provide path provisioning and monitoring to the higher layers Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

13 DWDM-RAM Architecture Communication Protocols Standard off-the-shelf communication protocol suites Provide communication between application clients and DWDM-RAM services and between DWDM-RAM components Communication consists of mainly SOAP messages in HTTP envelopes transported over TCP/IP connections Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

14 DWDM-RAM Architecture Network Resource Scheduling Essentially a resource management service Maintains schedules and provisions resources in accordance with the schedule Provides an OGSI compliant interface to request the optical network resources Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

15 DWDM-RAM Architecture Data Transfer Scheduling Direct extension of NRS service, provides an OGSI interface Shares same backend scheduling engine & resides on same host Provides a high-level functionality Allow applications to schedule data transfers without the need to directly reserve lightpaths The service also perform the actual data transfer once the network is allocated Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

16 Data Transfer Scheduling Uses standard ftp Uses NRS to allocate lambdas Uses OGSI calls to request network resources λ Data ReceiverData Source FTP clientFTP server DTS NRS Client App

17 DWDM-RAM Architecture Applications Target is data-intensive applications since their requirements make them the perfect costumer for DWDM networks Applications Data Transfer Scheduling Network Resource Scheduling Communication Protocols ODIN OMNInet Fabric Connectivity Resource Collective Application

18 DWDM-RAM Modes Applications may request a data transfer Applications Resource Allocator Network Resource Scheduling Applications may request a set of resources through a resource allocator, which will handle the network reservation Applications Data Transfer Scheduling Network Resource Scheduling

19 The Network Service NRS is the key for providing network as a resource –It is a service with an application-level interface –Used for requesting, releasing, and managing the underlying network resources –Understands the topology of the network –Maintains schedules and provisions resources in accordance with the schedule –Keeps one scheduling map for each lambda in each segment

20 The Network Service Scheduling maps: Each with a vector of time intervals for keeping the reservations. Scheduling maps for each segment

21 The Network Service NRS –Provides an OGSI-based interface to network resources –Request parameters Network addresses of the hosts to be connected Window of time for the allocation Duration of the allocation Minimum and maximum acceptable bandwidth (future) –Provides the network resource On demand By advance reservation –Network is requested within a window Constrained Under-constrained

22 The Network Service On Demand –Constrained window: right now! –Under-constrained window: ASAP! Advance Reservation –Constrained window Tight window, fits the transference time closely –Under-constrained window Large window, fits the transference time loosely Allows flexibility in the scheduling

23 The Network Service Under-constrained window 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. Both requests are satisfied. 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 4:305:005:304:003:30 W 4:305:005:304:003:30 X 4:305:005:304:003:30 W X

24 0.5s174s 9. ODIN Server Processing 10. File transfer complete, path released 1. File transferrequest 8. Path Deallocation request 7. Data Transfer (20 GB) 4. Path ID returned 3. ODIN Server Processing 2. Path Allocation request 5. Network reconfiguration 6. Transport setup End-to-end Transfer Time (Un-optimized) 20GB File Transfer Set up: 29.7s Transfer: 174s Tear down: 11.3s Transfer rate: 920Mb/sEffective rate:744Mb/s 3.6s0.5s0.3s11s25s0.14s GigE  L2 Switch  10GE  switched lambdas For a 200GB file: Transfer rate:920Mb/sEffective rate: 898Mb/s

25 20GB File Transfer

26 8.5 x 11 charts 24x36 poster board 4” banner for title or just leave blank DWDM RAM DWDM RAM Data@LIGHTspeed 1.5” margin ¾” margin


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