1. GENI-based Delay-guarantee Communication for Smart Grid with SDN Yanyuan Qin - University of Connecticut Lingyu Ren - University of Connecticut Sourabh Kulkarni – Rochester Institute of Technology

2. Problem Description: Smart Grid Network with SDN  The communication for smart grid is very unique, control packet with stringent delay requirement needs shortest delay (e.g. guarantee <4ms).  SDN is flexible and programmable. Can SDN be used to realize delay-guarantee communication of Smart Grid?

3. Ideas for Delay Guarantee with SDN  Build SDN network with GENI  Path choosing for delay guarantee. we use active delay monitor get the real-time delay and re-route dynamically based on the requirement threshold for control packet.  Flow yield for delay guarantee. If time requirement cannot be satisfied, some flow should change to another path to yield resource to time-stringent control packets.

4. Topology and Tools Controller: Ryu Switch: OVS GENI sources: Stanford InstaGENI Programming Tools: Python Host1Host2 (node0) (node2) (node3) (node1)

5. Algorithm / Steps Delay Monitoring:  Measure RTT of path1 (Controller->Sw1->Sw2a->Sw3->Controller)  Measure RTT of path2 (Controller->Sw1->Sw2b->Sw3->Controller)  Measure delay t1 (Controller->Sw1) using STAT_REQUEST  Measure delay t2 (Controller->Sw3) using STAT_REQUEST  Delay of path1 = RTT1 - (t1+t2)/2  Delay of path2 = RTT2 – (t1+t2)/2 Delay Guarantee:  Switch path if Delay>Threshold Reference: K´evin Phemius and Mathieu Bouet, Monitoring latency with OpenFlow, 2013

6. RTT Analysis (t1) RTT from Controller to Sw1 (t1) Mean Value of Sliding Windows Mean Value of Whole Data Set Probability Density Function of t1

7. RTT Analysis Cont. (t2) RTT from Controller to Sw3 (t2) Mean Value of Sliding Windows Mean Value of Whole Data Set Probability Density Function of t2

8. Results and Analysis Parameter Setting: Window size = 4; Window step = 2; State Size=0.05 (ms); Results: DataData NumberMean Value (ms) RTT from Controller to Sw1722.2194 RTT from Controller to Sw31042.3253

9. Demo

10. Future Work  Improve accuracy of delay measurement. (Approximation and assumptions)  Increase network robustness. (Delay changes can be very fast)  Compare the performance of Ryu controller with that of the Floodlight controller (Python vs. Java)  Apply to Smart Grid communication

11. Thank you !