Cyber-Physical Event Processing Chao Wang CSE 520S References - PowerPoint PPT Presentation

Cyber-Physical Event Processing Chao Wang CSE 520S

References Ø Core material of this lecture: Wang, C., Gill, C. and Lu, C., 2017, June. Real-time middleware for cyber-physical event processing. In Quality of Service (IWQoS), 2017 IEEE/ACM 25th International Symposium on (pp. 1-6). IEEE. Ø Other references: q The specifications of CORBA, Real-time CORBA, and DDS http://www.omg.org/technology/documents/vault.htm q TAO http://www.cs.wustl.edu/~schmidt/TAO.html q Vasisht, D., Kapetanovic, Z., Won, J., Jin, X., Chandra, R., Sinha, S.N., Kapoor, A., Sudarshan, M. and Stratman, S., 2017, March. FarmBeats: An IoT Platform for Data-Driven Agriculture. In NSDI (pp. 515-529). q Khandeparkar, K., Ramamritham, K. and Gupta, R., 2017. QoS-Driven Data Processing Algorithms for Smart Electric Grids. ACM Transactions on Cyber-Physical Systems , 1 (3), p.14. q Cugola, G. and Margara, A., 2012. Complex event processing with T -REX. Journal of Systems and Software , 85 (8), pp.1709-1728. q Mayer, R., Mayer, C., Tariq, M.A. and Rothermel, K., 2016, June. GraphCEP: Real-time data analytics using parallel complex event and graph processing. In Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems (pp. 309-316). ACM. 1 10/9/17

Industrial Internet of Things (IIoT) Ø IIoT = Cyber-physical systems + Cloud Ø Cyber-physical event processing as a service 2 10/9/17

Application example Ø Monitoring a farm of 100 acres (i.e., 75+ football fields) Vasisht, D., Kapetanovic, Z., Won, J., Jin, X., Chandra, R., Sinha, S.N., Kapoor, A., Sudarshan, M. and Stratman, S., 2017, March. FarmBeats: An IoT Platform for Data-Driven Agriculture. In NSDI (pp. 515-529). 3 10/9/17

Application example Ø Monitoring a nation-wide smart electric grid Khandeparkar, K., Ramamritham, K. and Gupta, R., 2017. QoS-Driven Data Processing Algorithms for Smart Electric Grids. ACM Transactions on Cyber-Physical Systems , 1 (3), p.14. 4 10/9/17

Application example Ø Predictive maintenance q The prediction of and response to component failures q E.g., maintaining wind turbines in a wind farm 5 10/9/17

Cyber-physical event processing as a service Ø Example: sensor fusion q Reducing data noises q Creating frequency domain representation q Concatenating results for a broaden spectrum assessment EKF: Extended Kalman Filter FFT: Fast Fourier Transform CAT: Concatenation 6 10/9/17

Research challenges Ø Enforcing QoS policies q e.g., latency differentiation Ø Computationally intensive q e.g., sensor fusion q High input rate Ø Event temporal validity q Freshness of sensing data 7 10/9/17

Related work Ø Real-time event services q Real-time CORBA • Industry standard • Predictable and interoperable data exchanges between systems q TAO • CORBA-compliant C++ open-source implementation • Widely used in industry in the past two decades q Data Distribution Service (DDS) • Industry standard • Data-centric paradigm; publish-subscribe pattern Ø Complex event processing (CEP) q T -REX • Efficient implementation for a rich set of event processing rules q GraphCEP • Social network analysis (e.g., Facebook post ranking) 8 10/9/17

Related work Ø Real-time event services q Real-time CORBA • Industry standard Do not perform complex event processing … • Predictable and interoperable data exchanges between systems q TAO • CORBA-compliant C++ open-source implementation • Widely used in industry in the past two decades q Data Distribution Service (DDS) • Industry standard • Data-centric paradigm; publish-subscribe pattern Ø Complex event processing (CEP) q T -REX • Efficient implementation for a rich set of event processing rules q GraphCEP • Social network analysis (e.g., Facebook post ranking) 9 10/9/17

Related work Ø Real-time event services q Real-time CORBA Do not perform complex event processing … • Industry standard • Predictable and interoperable data exchanges between systems Ø Complex event processing (CEP) q T -REX Do not differentiate application QoS … • Efficient implementation for a rich set of event processing rules q GraphCEP • Social network analysis (e.g., Facebook post ranking) Do not support real-time at the millisecond scale … 10 10/9/17

Cyber-Physical Event Processing (CPEP) Real-time CPEP middleware ✓ Processing prioritization ✓ Processing sharing ✓ Enforcing temporal validity Wang, C., Gill, C. and Lu, C., 2017, June. Real-time middleware for cyber-physical event processing. In Quality of Service (IWQoS), 2017 IEEE/ACM 25th International Symposium on (pp. 1-6). IEEE. 11 10/9/17

System configuration Ø Constructing the graph of event streams from a file q Operator arrangement q Consumer priority levels Ø Prioritizing operators q Priority propagation from consumers s 1 o 1 o 5 c 1 High priority s 2 o 2 o 6 c 2 Middle priority s 3 o 3 o 7 s 4 c 3 Low priority o 4 s 5 c 4 Low priority 12 10/9/17

Processing prioritization Schedule the threads using a fixed-priority preemptive scheduling policy 13 10/9/17

Processing sharing Save the time for lower-priority processing! Movers don’t interfere with higher- priority processing! 14 10/9/17

Enforcing temporal validity Absolute validity intervals: The interval for S 1 The interval for S 3 The interval for S 2 An event for C 2 is temporally valid only before timepoint t 4 15 10/9/17

Enforcing temporal validity Absolute validity intervals: The interval for S 1 The interval for S 3 The interval for S 2 CPEP sheds invalid events for both correctness and efficiency An event for C 2 is temporally valid only before timepoint t 4 16 10/9/17

CPEP implementation Ø Implemented based on RT -CORBA event service q TAO real-time event channel (version 2.3.0) Ø Efficient memory management q Zero-copy of same event for downstream operators Ø Replacing older events by new instances q Data freshness for physical states 17 10/9/17

Empirical evaluation Ø Experimentation setup Machine 2 Machine 3 Machine 1 (“The middle box”) CPEP Event consumers Event suppliers Ø Evaluating performance on q Prioritization q Sharing q Shedding Ø Workload: sensor fusion emulation, etc. q Consumers of multiple priority levels q Suppliers of multiple sending rates q Sharing of operators 18 10/9/17

Graphs of event streams #1 Ø Consumers of multiple priority levels Ø Suppliers of multiple sending rates 19 10/9/17

Graphs of event streams #2 Ø Sharing of operators s 1 c 1 EKF 1 FFT 1 CAT 1 AES 1 s 2 100 Hz s 3 EKF 2 FFT 2 s 4 High priority s 5 100 Hz c 2 EKF 3 FFT 3 CAT 2 AES 2 s 6 s 7 EKF 4 FFT 4 AES 3 s 8 Middle priority Low priority c 3 CAT 3 AES 4 Ø Non-sharing s 1 c 1 EKF 1 FFT 1 CAT 1 AES 1 s 2 100 Hz s 3 EKF 2 FFT 2 s 4 High priority Middle priority 100 Hz EKF 3 FFT 3 s 5 c 2 EKF 4 FFT 4 CAT 2 AES 2 s 6 s 7 EKF 5 FFT 5 AES 3 s 8 c 3 EKF 6 FFT 6 CAT 3 AES 4 Low priority EKF 7 FFT 7 20 10/9/17

CPEP prioritization: results Protect the latency of high-priority events against contention 21 10/9/17

CPEP sharing: results Sharing reduced the latency of lower-priority processing Without sharing, no low-priority events were produced! 22 10/9/17

CPEP shedding: results Valid throughput = temporally valid events / second Shedding can improve temporally valid throughput 23 10/9/17

CPEP shedding: results Valid throughput = temporally valid events / second Shedding can improve temporally valid throughput 24 10/9/17

Summary Ø Cyber-physical event processing is vital for Industrial IoT Ø Three main contributions of the CPEP middleware ✓ Processing prioritization ✓ Processing sharing ✓ Enforcing temporal validity 25 10/9/17