Abstract
Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption by industrial Internet of Things applications in recent years. A WSAN typically connects sensors, actuators, and controllers in industrial facilities, such as steel mills, oil refineries, chemical plants, and infrastructures implementing complex monitoring and control processes. IEEE 802.15.4–based WSANs operate at low power and can be manufactured inexpensively, which makes them ideal where battery lifetime and costs are important. Recent studies have shown that the selection of network parameters has a significant effect on network performance. However, the current practice of parameter selection is largely based on experience and rules of thumb involving a coarse-grained analysis of expected network load and dynamics or measurements during a few field trials, resulting in non-optimal decisions in many cases. In this work, we develop P-SAFE (Parameter Selection and Adaptation FramEwork), which optimally selects the network parameters based on the application quality-of-service demands and adapts the parameter configuration at runtime to consistently satisfy the dynamic requirements. We implement P-SAFE and evaluate it on three physical testbeds. Experimental results show that our solution can significantly better meet the application quality-of-service demand compared to the state of the art.
- IEEE 802.15. 2012. IEEE-802.15.4e WPAN Task Group. Retrieved September 28, 2018 from http://www.ieee802.org/15/pub/TG4e.htmlGoogle Scholar
- Nicola Accettura, Elvis Vogli, Maria Rita Palattella, Luigi Alfredo Grieco, Gennaro Boggia, and Mischa Dohler. 2015. Decentralized traffic aware scheduling in 6TiSCH networks: Design and experimental evaluation. In IEEE Internet of Things, Vol. 2. IEEE, Los Alamitos, CA, 17.Google Scholar
Cross Ref
- Mansoor Alicherry, Randeep Bhatia, and Li Li. 2005. Joint channel assignment and routing for throughput optimization in multi-radio wireless mesh networks. In Proceedings of the 11th Annual International Conference on Mobile Computing and Networking (MobiCom’05). ACM, New York, NY, 58--72. DOI:https://doi.org/10.1145/1080829.1080836Google Scholar
Digital Library
- Mikael Johansson B. Aminian, Jose Araujo and Karl H. Johansson. 2013. GISOO: A virtual testbed for wireless cyber-physical systems. In Proceedings of the Annual Conference of the IEEE Industrial Electronics Society (IECON’13). IEEE, Los Alamitos, CA, 6.Google Scholar
- Nouha Baccour, Anis Koubâa, Luca Mottola, Marco Antonio Zúñiga, Habib Youssef, Carlo Alberto Boano, and Mário Alves. 2012. Radio link quality estimation in wireless sensor networks: A survey. ACM Transactions on Sensor Networks 8, 4 (2012), Article 34, 33 pages. DOI:https://doi.org/10.1145/2240116.2240123Google Scholar
Digital Library
- Marcos Almeida Bezerra, Ricardo Erthal Santelli, Eliane Padua Oliveira, Leonardo Silveira Villar, and Luciane Amélia Escaleira. 2008. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 76, 5 (2008), 965--977.Google Scholar
Cross Ref
- Carlo Alberto Boano, Thiemo Voigt, Claro Noda, Kay Römer, and Marco Zúñiga. 2011. JamLab: Augmenting sensornet testbeds with realistic and controlled interference generation. In Proceedings of the International Conference on Information Processing (IPSN’11). IEEE, Los Alamitos, CA, 12.Google Scholar
- Michael Buettner, Gary V. Yee, Eric Anderson, and Richard Han. 2006. X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks. In Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys’06). ACM, New York, NY, 307--320. DOI:https://doi.org/10.1145/1182807.1182838Google Scholar
Digital Library
- Anton Cervin. 2018. TrueTime: Simulation of Networked and Embedded Control Systems. Retrieved June 4, 2020 from http://www.control.lth.se/truetime/.Google Scholar
- Miral Changela and Ankit Kumar. 2015. Designing a controller for two tank interacting system. International Journal of Science and Research 4, 5 (2015), 589--593.Google Scholar
- Indraneel Das and John Dennis. 1997. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. In Structural Optimization, Vol. 14. Springer, New York, NY, 7.Google Scholar
- Kalyanmoy Deb. 2014. Multi-objective optimization. In Search Methodologies, E. K. Burke and G. Kendall (Eds.). Springer, New York, NY, 403--449.Google Scholar
- Kalyanmoy Deb, Amrit Pratap, Sameer Agarwa, and T. Meyarivan. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6 (2002), 16.Google Scholar
- Manjunath Doddavenkatapp, Mun Choon Chan, and B. Leong. 2011. Improving link quality by exploiting channel diversity in wireless sensor networks. In Proceedings of the IEEE Real-Time Systems Symposium (RTSS’11). IEEE, Los Alamitos, CA, 11.Google Scholar
- Wei Dong, Chun Chen, Xue Liu, Yuan He, Yunhao Liu, Jiajun Bu, and Xianghua Xu. 2014. Dynamic packet length control in wireless sensor networks. IEEE Transactions on Wireless Communications 13 (2014), 10.Google Scholar
Cross Ref
- Wei Dong, Jie Yu, and Pingxin Zhang. 2015. Exploiting error estimating codes for packet length adaptation in low-power wireless networks. IEEE Transactions on Mobile Computing 14 (2015), 14.Google Scholar
Cross Ref
- Simon Duquennoy, Beshr Al Nahas, Olaf Landsiedel, and Thomas Watteyne. 2015. Orchestra: Robust mesh networks through autonomously scheduled TSCH. In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems (SenSys’15). ACM, New York, NY, 337--350. DOI:https://doi.org/10.1145/2809695.2809714Google Scholar
Digital Library
- Emerson. 2016. System Engineering Guidelines IEC 62591 WirelessHART by Emerson Process Management. Retrieved June 4, 2020 from https://www.emerson.com/documents/automation/emerson-wirelesshart-system-engineering-guide-en-41252.pdf.Google Scholar
- Emerson. 2019. Emerson Wireless Technology. Retrieved June 4, 2020 from https://www.emerson.com/en-us/expertise/automation/industrial-internet-things/pervasive-sensing-solutions/wireless-technology.Google Scholar
- Design Expert. 2018. DesignExpert 10. Retrieved June 4, 2020 from https://cdnm.statease.com/pubs/why_DX10_tops.pdf.Google Scholar
- Emeka Eyisi, Jia Bai, Derek Riley, Jiannian Weng, Yan Wei, Yuan Xue, Xenofon D. Koutsoukos, and Janos Sztipanovits. 2012. NCSWT: An integrated modeling and simulation tool for networked control systems. In Proceedings of the International Conference on Hybrid Systems: Computation and Control (HSCC’12). 22.Google Scholar
Digital Library
- Songwei Fu, Yan Zhang, Yuming Jiang, Chengchen Hu, Chia-Yen Shih, and Pedro Jose Marron. 2015. Experimental study for multi-layer parameter configuration of WSN links. In Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS’15). IEEE, Los Alamitos, CA, 10.Google Scholar
Cross Ref
- Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, and Karel Crombecq. 2010. A surrogate modeling and adaptive sampling toolbox for computer based design. Journal of Machine Learning Research 11 (Aug. 2010), 2051--2055.Google Scholar
- Dolvara Gunatilaka and Chenyang Lu. 2018. Conservative channel reuse in real-time industrial wireless sensor-actuator networks. In Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS’18). IEEE, Los Alamitos, CA, 10.Google Scholar
Cross Ref
- Dolvara Gunatilaka, Mo Sha, and Chenyang Lu. 2017. Impacts of channel selection on industrial wireless sensor-actuator networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’17). IEEE, New York, NY, 9.Google Scholar
Cross Ref
- Song Han, Xiuming Zhu, Aloysius K. Mok, Deji Chen, and Mark Nixon. 2011. Reliable and real-time communication in industrial wireless mesh networks. In Proceedings of the 2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium. IEEE, Los Alamitos, CA, 3--12. DOI:https://doi.org/10.1109/RTAS.2011.9Google Scholar
Digital Library
- IETF. 2013. 6TiSCH: IPv6 over the TSCH Mode of IEEE 802.15.4e. Retrieved September 28, 2018 from https://datatracker.ietf.org/wg/6tisch/documents/.Google Scholar
- Indriya Testbed. 2011. INDRIYA: A Wireless Sensor Network Testbed. Retrieved June 4, 2020 from https://indriya.comp.nus.edu.sg/.Google Scholar
- ISA100 Wireless. 2009. ISA100. Retrieved September 28, 2018 from http://www.isa100wci.org/.Google Scholar
- Romain Jacob, Marco Zimmerling, Pengcheng Huang, Jan Beutel, and Lothar Thiele. 2016. End-to-end real-time guarantees in wireless cyber-physical systems. In Proceedings of the IEEE Real-Time Systems Symposium (RTSS’16). IEEE, Los Alamitos, CA, 12.Google Scholar
Cross Ref
- Youngmin Kim, Hyojeong Shin, and Hojung Cha. 2008. Y-MAC: An energy-efficient multi-channel MAC protocol for dense wireless sensor networks. In Proceedings of the ACM/IEEE International Symposium on Information Processing in Sensor Networks (IPSN’08). IEEE, Los Alamitos, CA, 11.Google Scholar
Digital Library
- Murali Kodialam and Thyaga Nandagopal. 2005. Characterizing the capacity region in multi-radio multi-channel wireless mesh networks. In Proceedings of the 11th Annual International Conference on Mobile Computing and Networking (MobiCom’05). ACM, New York, NY, 73--87. DOI:https://doi.org/10.1145/1080829.1080837Google Scholar
Digital Library
- Hieu Khac Le, Dan Henriksson, and Tarek Abdelzaher. 2007. A control theory approach to throughput optimization in multi-channel collection sensor networks. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN’07). ACM, New York, NY, 31--40. DOI:https://doi.org/10.1145/1236360.1236365Google Scholar
Digital Library
- Hieu Khac Le, Dan Henriksson, and Tarek Abdelzaher. 2008. A practical multi-channel media access control protocol for wireless sensor networks. In Proceedings of the ACM/IEEE International Symposium on Information Processing in Sensor Networks (IPSN’08). IEEE, Los Alamitos, CA, 12.Google Scholar
Digital Library
- HyungJune Lee, Alberto Cerpa, and Philip Levis. 2007. Improving wireless simulation through noise modeling. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN’07). ACM, New York, NY, 21--30. DOI:https://doi.org/10.1145/1236360.1236364Google Scholar
Digital Library
- HyungJune Lee, Alberto Cerpa, and Philip Levis. 2007. Improving wireless simulation through noise modeling. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN’07). ACM, New York, NY, 21--30. DOI:https://doi.org/10.1145/1236360.1236364Google Scholar
Digital Library
- Philip Levis, Nelson Lee, Matt Welsh, and David Culler. 2003. TOSSIM: Accurate and scalable simulation of entire TinyOS applications. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys’03). ACM, New York, NY, 126--137. DOI:https://doi.org/10.1145/958491.958506Google Scholar
Digital Library
- Chieh-Jan Mike Liang, Nissanka Bodhi Priyantha, Jie Liu, and Andreas Terzis. 2010. Surviving wi-fi interference in low power ZigBee networks. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys’10). ACM, New York, NY, 309--322. DOI:https://doi.org/10.1145/1869983.1870014Google Scholar
Digital Library
- Xiaojun Lin and Shahzada Rasool. 2007. A distributed joint channel-assignment, scheduling and routing algorithm for multi-channel ad-hoc wireless networks. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’07). IEEE, New York, NY, 9.Google Scholar
Digital Library
- Chenyang Lu, Abusayeed Saifullah, Bo Li, Mo Sha, Humberto Gonzalez, Dolvara Gunatilaka, Chengjie Wu, Lanshun Nie, and Yixin Chen. 2016. Real-time wireless sensor-actuator networks for industrial cyber-physical systems. Proceedings of the IEEE: Special Issue on Industrial Cyber Physical Systems 104 (2016), 12.Google Scholar
- James Manyika, Michael Chui, Jacques Bughin, Richard Dobbs, Peter Bisson, and Alex Marrs. 2013. Disruptive technologies: Advances that will transform life, business, and the global economy. McKinsey Digital. Retrieved June 4, 2020 from http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/disruptive-technologies.Google Scholar
- C. D. McAllister, T. W. Simpson, K. Hacker, K. Lewis, and A. Messac. 2005. Integrating linear physical programming within collaborative optimization for multiobjective multidisciplinary design optimization. Structural and Multidisciplinary Optimization 29, 3 (2005), 178--189.Google Scholar
Cross Ref
- MEMSIC. 2004. TelosB Datasheet. Retrieved June 4, 2020 from http://www.memsic.com/userfiles/files/Datasheets/WSN/telosb_datasheet.pdf.Google Scholar
- Achille Messac. 1996. Physical programming: Effective optimization for computational design. AIAA Journal 34 (1996), 11.Google Scholar
Cross Ref
- Achille Messac. 2006. Multiobjective decision-making using physical programming. In Decision Making in Engineering Designs, K. E. Lewis, W. Chen, and L. C. Schmidt (Eds.). ASME, New York, NY, 155--172.Google Scholar
- Razvan Musaloiu-E., Chieh-Jan Mike Liang, and Andreas Terzis. 2008. Koala: Ultra-low power data retrieval in wireless sensor networks. In Proceedings of the International Symposium on Information Processing in Sensor Networks (IPSN’08). IEEE, Los Alamitos, CA, 12.Google Scholar
- Yang Peng, Zi Li, Daji Qiao, and Wensheng Zhang. 2013. I2C: A holistic approach to prolong the sensor network lifetime. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’13). IEEE, New York, NY, 9.Google Scholar
- Bhaskaran Raman. 2006. Channel allocation in 802.11-based mesh networks. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’06). IEEE, New York, NY, 10.Google Scholar
Cross Ref
- Abusayeed Saifullah, Dolvara Gunatilaka, Paras Tiwari, Mo Sha, Chenyang Lu, Bo Li, Chengjie Wu, and Yixin Chen. 2015. Schedulability analysis under graph routing in WirelessHART networks. In Proceedings of the IEEE Real-Time Systems Symposium (RTSS’15). IEEE, Los Alamitos, CA, 10.Google Scholar
Digital Library
- Jan Seeger, Arne Bröring, Marc-Oliver Pahl, and Ermin Sakic. 2019. Rule-based translation of application-level QoS constraints into SDN configurations for the IoT. In Proceedings of the 2019 European Conference on Networks and Communications (EuCNC’19). 432--437.Google Scholar
Cross Ref
- Junyang Shi and Mo Sha. 2019. Parameter self-configuration and self-adaptation in industrial wireless sensor-actuator networks. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’19). IEEE, New York, NY, 658--666.Google Scholar
Cross Ref
- Junyang Shi, Mo Sha, and Zhicheng Yang. 2018. DiGS: Distributed graph routing and scheduling for industrial wireless sensor-actuator networks. In Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS’18). IEEE, Los Alamitos, CA, 11.Google Scholar
Cross Ref
- Timothy Simpson, Timothy Mauery, John Korte, and Farrokh Mistree. 2001. Kriging models for global approximation in simulation-based multidisciplinary design optimization. AIAA Journal 39 (2001), 9.Google Scholar
Cross Ref
- Simulink. 2019. Home Page. Retrieved June 4, 2020 https://www.mathworks.com/products/simulink.html.Google Scholar
- Kannan Srinivasan, Prabal Dutta, Arsalan Tavakoli, and Philip Levis. 2006. Understanding the causes of packet delivery success and failure in dense wireless sensor networks. In Proceedings of the 4th International Conference on Embedded Networked Sensor Systems (SenSys’06). ACM, New York, NY, 419--420. DOI:https://doi.org/10.1145/1182807.1182885Google Scholar
Digital Library
- BU Testbed. 2017. BU Testbed at Binghamton University. Retrieved June 4, 2020 from http://www.cs.binghamton.edu/%7Emsha/testbed.Google Scholar
- TSCH. 2015. Using IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) in the Internet of Things (IoT): Problem Statement. Retrieved April 10, 2019 from https://tools.ietf.org/html/rfc7554.Google Scholar
- Jiliang Wang, Zhichao Cao, Xufei Mao, and Yunhao Liu. 2014. Sleep in the dins: Insomnia therapy for duty-cycled sensor networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’14). IEEE, New York, NY, 9.Google Scholar
Cross Ref
- Thomas Watteyne, Vlado Handziski, Xavier Vilajosana, Simon Duquennoy, Oliver Hahm, Emmanuel Baccelli, and Adam Wolisz. 2016. Industrial wireless IP-based cyber-physical systems. Proceedings of the IEEE: Special Issue on Industrial Cyber Physical Systems 104 (2016), 14.Google Scholar
- CPSL. 2013. WCPS: Wireless Cyber-Physical Simulator. Retrieved June 4, 2020 from http://wsn.cse.wustl.edu/index.php/WCPS:_Wireless_Cyber-Physical_Simulator.Google Scholar
- FieldComm Group. 2004. WirelessHART. Retrieved June 4, 2020 from https://fieldcommgroup.org/technologies/hart.Google Scholar
- Chengjie Wu, Dolvara Gunatilaka, Abusayeed Saifullah, Mo Sha, Paras Babu Tiwari, Chenyang Lu, and Yixin Chen. 2016. Maximizing network lifetime of WirelessHART networks under graph routing. In Proceedings of the IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI’16). IEEE, Los Alamitos, CA, 11.Google Scholar
Cross Ref
- Chengjie Wu, Dolvara Gunatilaka, Mo Sha, and Chenyang Lu. 2018. Real-time wireless routing for industrial Internet of Things. In Proceedings of the IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI’18). IEEE, Los Alamitos, CA, 6.Google Scholar
Cross Ref
- CPSL. 2015. The WUSTL Wireless Sensor Network Testbed. Retrieved June 4, 2020 from http://cps.cse.wustl.edu/index.php/Testbed.Google Scholar
- Jerry Zhao and Ramesh Govindan. 2003. Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (SenSys’03). ACM, New York, NY, 1--13. DOI:https://doi.org/10.1145/958491.958493Google Scholar
Digital Library
- Gang Zhou, Tian He, Sudha Krishnamurthy, and John A. Stankovic. 2004. Impact of radio irregularity on wireless sensor networks. In Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services (MobiSys’04). ACM, New York, NY, 125--138. DOI:https://doi.org/10.1145/990064.990081Google Scholar
- Gang Zhou, Chengdu Huang, Ting Yan, Tian He, and John A. Stankovic. 2006. MMSN: Multi-frequency media access control for wireless sensor networks. In Proceedings of the IEEE International Conference on Computer Communications (INFOCOM’06). IEEE, New York, NY, 13.Google Scholar
- Marco Zimmerling, Federico Ferrari, Luca Mottolay, Thiemo Voigty, and Lothar Thiele. 2012. pTunes: Runtime parameter adaptation for low-power MAC protocols. In Proceedings of the 11th International Conference on Information Processing in Sensor Networks (IPSN’12). ACM, New York, NY, 173--184. DOI:https://doi.org/10.1145/2185677.2185730Google Scholar
Digital Library
Index Terms
Parameter Self-Adaptation for Industrial Wireless Sensor-Actuator Networks
Recommendations
Autonomous Traffic-Aware Scheduling for Industrial Wireless Sensor-Actuator Networks
Recent years have witnessed rapid adoption of low-power Wireless Sensor-Actuator Networks (WSANs) in process industries. To meet the critical demand for reliable and real-time communication in harsh industrial environments, the industrial WSAN standards ...
Sensor-actuator communication protocols in wireless networks
NBiS'07: Proceedings of the 1st international conference on Network-based information systemsA wireless sensor-actuator network (WSAN) is composed of sensor and actuator nodes interconnected in a wireless channel. Sensor nodes can deliver messages to only nearer nodes due to weak radio and messages are forwarded by sensor nodes to an actuator ...
Testbed Environment for Wireless Sensor and Actuator Networks
ICSNC '10: Proceedings of the 2010 Fifth International Conference on Systems and Networks CommunicationsThe Wireless Sensor and Actuator Networks (WSAN’s), defines collaborative operations between the sensors and the actuators, enabling distributed sensing of a physical phenomenon. In this paper, an integrated testbed consisted of wireless sensor network, ...






Comments