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Scalable and Extensible Network Monitoring For Scalable and Extensible Network Monitoring For GENI GENI Sonia.

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Presentation on theme: "Scalable and Extensible Network Monitoring For Scalable and Extensible Network Monitoring For GENI GENI Sonia."— Presentation transcript:

1 Scalable and Extensible Network Monitoring For Scalable and Extensible Network Monitoring For GENI GENI Sonia Fahmy(Purdue University) Puneet Sharma (HP Labs)

2 2 RECAP: Scalable Sensing Service (S 3 ) Sensor pods −Measure system state from a node perspective −Web-Service enabled collection of sensors Sensing information manager −Controls pods, and aggregates measured system state −Portal to request and invoke measurements Inference engines −Infer O(n 2 ) E2E path info by measuring a few paths −Dynamically schedules measurements on pods

3 3 Sensor Pod Secure Web Interface Controller Latency Loss Bandwidth Load Capacity Memory Repositor y Configuration & Data API: query, control, and notification Web-Service (WS) enabled collection of sensors

4 Sensor Pod Secure Web Interface Controller Latency Lossrate Bandwidth Load Capacity Memory Repositor y Configuration & Data API: query, control, and notification Web-Service (WS) enabled collection of sensors Secure Web Interface: Standard communication protocols Flexible interface

5 Basic Measurement Invocation Invocation node Tool/Sensor to be invoked Sensor Parameters Example 5

6 Sensor Pod Secure Web Interface Controller Latency Lossrate Bandwidth Load Capacity Memory Repository Configuration & Data API: query, control, and notification Web-Service (WS) enabled collection of sensors Archive measurement data for sharing Store sensor invocation configurations

7 Sensor Pod Secure Web Interface Controller Latency Lossrate Bandwidth Load Capacity Memory Repository Configuration & Data API: query, control, and notification Web-Service (WS) enabled collection of sensors Process requests, invoke sensors according to installed configurations

8 8 Sensing Information Manager −Control the sensor-pods −Aggregate data from sensor −Answer researcher queries Sensing Information Manager/Portal

9 Chaining Sensor Pods Tools that need to be started at both ends simultaneously −Capacity Pathrate −Available BW PathChirp Spruce Node A Node B Measure CAP(A  B) CAP(B) 1)Start CAP_SEND 2)Start CAP_RCV at B 3) Measure Start CAP_RCV

10 Host Landmark Router (Milestone) d1 d2 … dn d1 d2 … dn d1 d2 … dn d1 d2 … dn d1 d2 … dn Use landmark vectors for local clustering Leverage Route Information traceroute to landmarks Landmar k Vector Complex Sensors: E.g. Netvigator

11 For each node invoke traceroute to each landmark i :46000/cgi-bin/csi.cgi?COMMAND=TRACEROUTE&DEST=LM1 i :46000/cgi-bin/csi.cgi?COMMAND=TRACEROUTE&DEST=LM2 i :46000/cgi-bin/csi.cgi?COMMAND=TRACEROUTE&DEST=LM3http://node i :46000/cgi-bin/csi.cgi?COMMAND=TRACEROUTE&DEST=LM3... Extract vectors and run clustering algorithm 11

12 Related Extensions Security/Access Control Semantic Data Store 12

13 Scalable Access Control “Scalable Access Control ForWeb Services”, Gayatri Swamynathan, Tyler Close, Sujata Banerjee, Rick McGeer, Fifth International Conference on Creating, Connecting and Collaborating through Computing (C5), Kyoto, Japan, January 2007 Capabilities based URL-Rewriter Service 13

14 Semantic Data Store “Temporal Views over RDF Store”, Geetha Manjunath, Badrinath Ramamurthy, Craig Sayers, Venugopal KS, WWW'2008, Beijing, April 2008 Convert the measurement results into RDF store Create temporal views to maintain liveness of data SPARQL queries on the RDF store 14

15 15

16 Example View Specification 16

17 Questions/Comments/Code 17


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