Synthesizing Adaptive Protocols by Selective Enumeration (SYNAPSE)

Transcription

1 Synthesizing Adaptive Protocols by Selective Enumeration (SYNAPSE)

2 Problem Definition Solution Approach Benefits to End User Talk Overview Metrics Summary of Results to Date Lessons Learned & Future Work Advanced Technology Laboratories 2

3 Problem: Variable Tactical Network Performance Severely Degrades Internet Env. Applications (1) Source: SAPIENT Industry Day Presentation Problem: 88% Link Availability Translates to 52% Application Availability Cause: Mismatch in Network Assumed by Applications and Network Provided by TCDL IWS and TMBCS are both TCP/IP based applications designed for high availability wired networks Advanced Technology Laboratories 3

4 Problem: Variable Tactical Network Performance Severely Degrades Internet Env. Applications (2) Source: LM ATL Laboratory Experiments Problem: Link is available for 110s over a 350s window but FTP gets NO data through Cause: Mismatch in Network Assumed by Applications and Network Provided by Inmarsat TCP assumes packet loss is due to congestion and backoffs (an assumption for the original Internet) Advanced Technology Laboratories 4

5 Application Neutral Application Aware Problem: SAPIENT Research Problem Research Area Application Networking Mobile Ad Hoc Networking Wireless Comms Key Optimization Problem Operate the most effectively over the available network Create the best network (stability and performance) out of discrete channels Establish and sustain the highest performance channel Technology Research Programs COTS Custom Solutions Real One, Net Meeting General Infrastructure Solution DARPA SAPIENT DARPA CBMANET DARPA FCS Comms DARPA Control Plane DARPA XG Comms DARPA WNAN DARPA ORCA Advanced Technology Laboratories 5

6 SAPIENT Program Solution: Situation Aware Protocols In Edge networks SAPIENT Applies AI Learn Protocols that Optimize Application Performance Over A Variety of Network Conditions Breaks the Static Design Model for Network Applications Source: SAPIENT Industry Day Briefing Advanced Technology Laboratories 6

7 LM ATL SYNAPSE Solution: SYNAPSE is a bridge between the red side router and the link encrytpor As a bridge SYNAPSE has a very small installation footprint (a box per platform) and a very small integration footprint (power plus two network cables) SYNAPSE can exploit black side router information if available but it can operate albeit less optimally without it Advanced Technology Laboratories 7

8 How is SYNAPSE Implemented? SYNAPSE is implemented as a flexible protocol framework to adapt and dynamically compose transport-level protocols in order to mask network impairments from applications. Composed Protocols Packet Interceptor App Detection Packet Injector Composed Protocols Traffic Shaper Sensors Control Policy Controller Application- and network-level traffic transformations allow SYNAPSE to maintain satisfactory application-perceived network characteristics by trading some network resources for others on a per-application basis, depending on application sensitivity (e.g. latency for bandwidth, or bandwidth for loss, etc.). Advanced Technology Laboratories 8

9 Existing SYNAPSE Protocols Flow Mux/Demux IP Application Detection TCP Proxy Traffic Management Adaptive Sliding Window Application Performance Classifier Queue Network Aware VoIP (Detailed Explanation Follows) Packet Aggregation / Fragmentation Dynamic Information Dispersal Algorithm SynVent (application specific optimization for Army) Advanced Technology Laboratories 9

10 Dynamic VoIP (DVoIP) DVoIP improves VoIP call quality of service by reducing the bandwidth requirements of a given VoIP stream DVoIP can perform on-the-fly transformations to VoIP streams to ensure smooth and stable operations over a variety of network conditions DVoIP systems sit between the application and the constrained network link To maintain application transparency, any transformations performed at one endpoint must be reversed before passing the recovered packet stream to the application Advanced Technology Laboratories

11 DVoIP Transformations DVoIP effects bandwidth adaptation through two actuators: the audio transcoder and the frame aggregator Audio transcoding is translation between audio codecs, which allows the system to convert traffic being sent from the VoIP application using a high-bandwidth codec into a lower bandwidth codec suitable for transmission over a constrained link Frame aggregation allows further bandwidth reduction by compressing sequential audio frames into a single packet, reducing network overhead through a negligible increase in stream latency Advanced Technology Laboratories

12 Audio Transcoder Converts audio from one codec to another, allowing the system to make a tradeoff between speech quality and bandwidth requirements Includes a library of codec plugins that translate between a codec and standard 16-bit Pulse Code Modulation Each frame encoded in a DVoIP packet will carry its original packet information with it as part of the DVoIP packet metadata, including the original RTP header. Advanced Technology Laboratories

13 Frame Aggregation Frame aggregation trades audio frame latency for a reduction in header overhead DVoIP uses frame aggregation to combine the audio frames from multiple packets into one packet By combining multiple VoIP packet payloads into a single packet, we can eliminate the IP/UDP overhead for all but one of the packets We can compress the RTP headers associated with each packet from 12 bytes to an average of 2.5 bytes each Advanced Technology Laboratories

14 Advanced Technology Laboratories DVoIP Bandwidth Reduction (128kbps channel)

15 Advanced Technology Laboratories DVoIP Simultaneous Call Volume Improvement (128kbps channel)

16 Experimental Results We have produced a prototype implementation of DVoIP that can interface with both hardware and software VoIP terminals. To test DVoIP performance, we have designed a testbench application that replays VoIP streams that have been recorded from Cisco 7940 IP phones. The testbench generates multiple concurrent VoIP streams, which are passed through a Linux-based router with a link constraint of 128 kbps. At either end of the link we have a DVoIP endpoint capable of handling multiple simultaneous channels. We have generated results from the experimental setup above, in which 10 G.729 calls are placed across a link that has been constrained to 128 kbps. Advanced Technology Laboratories

17 10 Simultaneous G.729 Calls (128kbps channel) Each G.729 call requires 24 kbps. None of the calls reach a full 24 kbps of bandwidth, meaning that there is constantly some packet loss happening for all calls. Advanced Technology Laboratories

18 10 Simultaneous DVoIP Calls (128kbps channel) By transcoding each call from G.729 to Speex 4kbps, and aggregating every 80ms of speech, we can reduce percall bandwidth to 10.7 kbps. Advanced Technology Laboratories

19 Benefits: Internet Env. Applications Operate Usably Over a Wide Variety of Network Conditions Automatically Acceptable Everywhere Performance 1 0 Network Conditions 0 SYNAPSE enables enables smooth, smooth, consistent application consistent performance application under performance drastically under varying drastically network varying conditions. network conditions Advanced Technology Laboratories 19

20 Benefits: UNCLASS VoIP Example (1) INMARSAT with single 64kbps channel and only 48kbps is available Call uses voice codec G.711 (64kbps bitrate) Need 80kbps of bandwidth Sapient s transcoded codec is GSM (13kbps bitrate) Need 31.6kbps of bandwidth Sapient can transcode voice to use as little as 3.6kbps of bandwidth while meeting the link constraint and maintaining a reasonable call utility Advanced Technology Laboratories 20

21 Benefits: UNCLASS Video Example (2) Advanced Technology Laboratories 21

22 Metrics: Sapient performance determined by Go/No-Go Metrics Application Performance FTP : Total Throughput HTTP/IRC : Latency VoIP : E-Model Score (60+ is passing) VLC : Performance Metric (60% and above is passing) Duration Ratio Measured response time against network impairment Must be less than 3 to pass Live Testing Example: 10s impairment» Baseline: Below threshold 14s yields DR of 1.4 (14/10)» SAPIENT: Below threshold 12s yields DR of 1.2 (12/10) Combination of above metrics (multiapp metric) Overall and during impairment Advanced Technology Laboratories 22

23 Results to Date / Future Phases Performance measurements are classified Phase I (18 months, completed 9/2006) LM ATL s SYNAPSE achieved the highest overall score on the Go/No-Go testing. LM ATL selected for Phase II (one of four performers dropped) Phase II (18 months, complete 7/2008) LM ATL s SYNAPSE demonstrated strong overall performance in Phase II Phase III (12 months, to start in 7/2009) DARPA to decide whether to pursue and down select to 1 or 2 performers Shift from air-ground links (TCDL, Inmarsat) to ground tactical RF links (PRC-117, SINCGARS, others) Emphasis on live testing and transition Advanced Technology Laboratories 23

24 Black SYNAPSE Nodes Actively Probe Outgoing Links to Determine the Current Route Used to Transmit Packets to the Remote Platform Experiment Topology Air Platform Red SYNAPSE Nodes Establish a Logical Connection to Each Directly Reachable Peer; Red Nodes do NOT conduct ad hoc routing; Multi-hop routing and RF link switching is assumed to be provided by the black network infrastructure Mobile Platform Ground Node Physical Network , , PRC-117 (LOS) Advanced Technology Laboratories 24

25 Lessons Learned & Future Work Advances in memory density and processing power change the network design space such that we can put smarts in edge network devices We can sense time varying network performance characteristics We can detect application specific network uses and deploy customized protocols that Strip out redundancy Reduce overhead Ride out network transient outages efficiently Improve overall application performance as compared to stock protocols (TCP and UDP) We can align network resources to time varying priorities near that edge where the situational context is best known Advanced Technology Laboratories 25

26 Lessons Learned & Future Work Real-Time capacity sensor accuracy is sensitive to low level design features of the network topology e.g. buffering in a link encryptor and predicting whether a sequence of sensor readings is an unsolved problem We believe fusing contextual knowledge e.g. the list of known link types with real time sensor readings would enable detection of erroneous measurements Alternatively explicit signaling protocols e.g. HP Labs TIA-1039 (now a standard) protocol provide accurate measurement of the constrained bandwidth link along a path (requires new routing equipment) Advanced Technology Laboratories 26

27 Thank You! We welcome questions and comments!