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The JOURNEY Active Network Model Maximilian Ott et al. IEEE Journal on Selected Areas in Communications, vol.19, no. 3, March 2001
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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.
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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
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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.
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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)
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Computing Router Architecture The cluster-based active router architecture (CLARA) Routing element Computing element(s) System area network (SAN) Cluster manager
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CLARA Architecture
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CLARA Functional Overview Ingress Engine DispatchCollect Egress Engine Admit
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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
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Active Media Packet Format
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Packet Programming Interface
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Admission Control for Soft-QoS Guarantees Unprocessed packet rate (UPR) Packet Admission Control (PAC) :observed delay for a packet :estimator function :current processing backlog :upper bound processing :packet’s delay budget
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Cascade Transformations with Multiple Nodes The performance goal of the active network is to bring the UPR of flows below some acceptable value.
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Scenic Routing
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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
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MPEG Transcoding Service
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Performance Measurements
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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
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Scalability in JOURNEY Manageability Self-configuration and self-healing Availability Performance Number of computing routers
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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.
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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
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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
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