1 / 22

The JOURNEY Active Network Model

The JOURNEY Active Network Model. Maximilian Ott et al. IEEE Journal on Selected Areas in Communications, vol.19, no. 3, March 2001. Introduction. Processing at the terminal end Processing at the server end The goal is to provide processing as an additional network service.

nitza
Download Presentation

The JOURNEY Active Network Model

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The JOURNEY Active Network Model Maximilian Ott et al. IEEE Journal on Selected Areas in Communications, vol.19, no. 3, March 2001

  2. Introduction • Processing at the terminal end • Processing at the server end • The goal is to provide processing as an additional network service. • The request-response processing model is transferred to continuous transformations on the date streams.

  3. JOURNEY Network Model • The transformation of a media unit (MU) is considered as a independent processing job. • A sequence of jobs pass through a JOURNEY node, which consists of multiple stages: • Classification stage • Admission stage • Routing stage

  4. Computation as a Network Service • Streams of MUs are injected into the network for routing and customizing. • An MU is independently processed anywhere along the path guided by routing. • A computing router utilize local condition of resource availability for deciding whether to process an MU.

  5. Computation as a Network Service • Similar to IP networks, the best-effort processing collocates with error recovery at higher layers. • Customization information can be originated at any point of the stream path, such as a client node or a resource manager. • Specific path routing is required for dealing with fragmentation of MUs. (MPLS, IP source routing)

  6. Computing Router Architecture • The cluster-based active router architecture (CLARA) • Routing element • Computing element(s) • System area network (SAN) • Cluster manager

  7. CLARA Architecture

  8. Engine Engine Engine Admit Dispatch Collect Ingress Egress CLARA Functional Overview

  9. Router Programming Framework • The CLARA software framework is also designed to support: • Accounting of the resource utilization of a packet or stream; • Division and vending of portions of the computational resources available on a router; • Dynamic addition of customization functionality • Functionality repositories

  10. Active Media Packet Format

  11. Packet Programming Interface

  12. :observed delay for a packet :estimator function :current processing backlog :upper bound processing :packet’s delay budget Admission Control for Soft-QoS Guarantees • Unprocessed packet rate (UPR) • Packet Admission Control (PAC)

  13. Cascade Transformations with Multiple Nodes • The performance goal of the active network is to bring the UPR of flows below some acceptable value.

  14. Scenic Routing

  15. Experience and Evaluation • Media gateway • Dropping frames, removing color, stronger uniform compression • Meta-information • MPEG4, MPEG7 • The trend toward thin and mobile clients • The scalability problem at the gateway

  16. MPEG Transcoding Service

  17. Performance Measurements

  18. Analysis • The larger the input/output bit-rate ratio, the less time it takes to transcode. • Frame drop and/or spatial resolution adjustments • DCT requantization • The total store-processing forward-service is double the processing time. • User-space routing engine • IP over Myrinet

  19. Scalability in JOURNEY • Manageability • Self-configuration and self-healing • Availability • Performance • Number of computing routers

  20. Conclusions • The JOURNEY network model provides computation as a scalable network services. • The computation model trades off hard guarantees for computation in favor of architectural simplicity. • The CLARA architecture collocates computing and routing functionality.

  21. Future Works • Studying the performance of the admission control and routing mechanisms at different traffic loads • Development of a management framework for the discovery and on-demand deployment of transcoding services • Development algorithms for admission control and load distribution within a CLARA computing router

  22. Possible Directions • Handing computation from proxies into the network • Mobile computing, WAP • Improving efficiency of multicast routing with heterogeneous receivers • Pre-customization of data streams • Active flow and congestion control • Re-transcoding and/or re-routing of data streams • Layered multimedia multicast tree

More Related