Energy-efficient Real-time Communication in Multi-hop Low-power Wireless Networks

Low-power wireless holds the promise of improving reliability and reducing costs in control applications. The key challenge in achieving these goals is to deliver packets within real-time deadlines across devices with limited energy. Existing approaches either can not provide end-to-end guarantees due to a fully localized operation, or hardly scale as they are sensitive to dynamic changes in the network state. Our key insight is that a fully global approach can overcome these limitations by being agnostic to the current network state. To substantiate this claim, we build Blink, a real-time low-power wireless protocol that provides hard guarantees on end-to-end packet deadlines, scales to large multi-hop networks, and seamlessly handles dynamic changes in network state and real-time requirements. We achieve this by leveraging an existing best-effort protocol that uses only flooding for communication, and by designing novel scheduling algorithms based on the earliest deadline first (EDF) policy. Using a dedicated priority queue data structure, we demonstrate a viable implementation of our algorithms on resourceconstrained devices. Results from a 94-node testbed and an instruction-level emulator show that Blink: (i) meets almost 100% of packet deadlines, missing only a few due to packet losses over the wireless channel; (ii) keeps the network-wide energy consumption to a minimum; and (iii) schedules 200 real-time packet streams in less than 80 milliseconds on a 16-bit 8 MHz microcontroller.

[1]  P. N. Paraskevopoulos,et al.  Modern Control Engineering , 2001 .

[2]  Jinhui Xu,et al.  Spatiotemporal Delay Control for Low-Duty-Cycle Sensor Networks , 2009, 2009 30th IEEE Real-Time Systems Symposium.

[3]  Federico Ferrari,et al.  FlockLab: A testbed for distributed, synchronized tracing and profiling of wireless embedded systems , 2013, 2013 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[4]  Gerth Stølting Brodal A Survey on Priority Queues , 2013, Space-Efficient Data Structures, Streams, and Algorithms.

[5]  Alejandro López-Ortiz,et al.  Space-Efficient Data Structures, Streams, and Algorithms , 2013 .

[6]  James W. Layland,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[7]  Yixin Chen,et al.  Real-Time Scheduling for WirelessHART Networks , 2010, 2010 31st IEEE Real-Time Systems Symposium.

[8]  Philip Levis,et al.  Collection tree protocol , 2009, SenSys '09.

[9]  Haibo Zhang,et al.  Optimal link scheduling and channel assignment for convergecast in linear WirelessHART networks , 2009, 2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.

[10]  Michael L. Dertouzos,et al.  Control Robotics: The Procedural Control of Physical Processes , 1974, IFIP Congress.

[11]  Edward W. Knightly,et al.  Distributed multi-hop scheduling and medium access with delay and throughput constraints , 2001, MobiCom '01.

[12]  Mikael Gidlund,et al.  Future research challenges in wireless sensor and actuator networks targeting industrial automation , 2011, 2011 9th IEEE International Conference on Industrial Informatics.

[13]  Kamin Whitehouse,et al.  IAA: Interference aware anticipatory algorithm for scheduling and routing periodic real-time streams in wireless sensor networks , 2010, 2010 Seventh International Conference on Networked Sensing Systems (INSS).

[14]  Thomas Weng,et al.  Duty-cycling buildings aggressively: The next frontier in HVAC control , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[15]  Chenyang Lu,et al.  RAP: a real-time communication architecture for large-scale wireless sensor networks , 2002, Proceedings. Eighth IEEE Real-Time and Embedded Technology and Applications Symposium.

[16]  Giorgio C. Buttazzo,et al.  Rate Monotonic vs. EDF: Judgment Day , 2003, Real-Time Systems.

[17]  Chenyang Lu,et al.  A spatiotemporal communication protocol for wireless sensor networks , 2005, IEEE Transactions on Parallel and Distributed Systems.

[18]  Lothar Thiele,et al.  Low-power wireless bus , 2012, SenSys '12.

[19]  Philip Levis,et al.  An empirical study of low-power wireless , 2010, TOSN.

[20]  Giorgio Buttazzo,et al.  Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications , 1997 .

[21]  Pedro José Marrón,et al.  COOJA/MSPSim: interoperability testing for wireless sensor networks , 2009, SimuTools.

[22]  Anis Koubaa,et al.  Radio link quality estimation in wireless sensor networks , 2012, ACM Trans. Sens. Networks.

[23]  K. Leentvaar,et al.  The Capture Effect in FM Receivers , 1976, IEEE Trans. Commun..

[24]  Robert B. Dial,et al.  Algorithm 360: shortest-path forest with topological ordering [H] , 1969, CACM.

[25]  Jorge Sá Silva,et al.  The GINSENG system for wireless monitoring and control: Design and deployment experiences , 2013, TOSN.

[26]  William G. Griswold,et al.  Interference-Aware Real-Time Flow Scheduling for Wireless Sensor Networks , 2011, 2011 23rd Euromicro Conference on Real-Time Systems.

[27]  Rocquencourt,et al.  Analysis of Deadline Scheduled Real-Time Systems , 1996 .

[28]  Marco Spuri,et al.  Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms , 2013 .

[29]  Stefan Bouckaert,et al.  The w-iLab.t Testbed , 2010, TRIDENTCOM.

[30]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[31]  David E. Culler,et al.  A transmission control scheme for media access in sensor networks , 2001, MobiCom '01.

[32]  Adam Dunkels,et al.  Software-based on-line energy estimation for sensor nodes , 2007, EmNets '07.

[33]  Chenyang Lu,et al.  Mobicast: Just-in-Time Multicast for Sensor Networks under Spatiotemporal Constraints , 2003, IPSN.

[34]  Kauko Leiviskä,et al.  Wireless Sensor Networks in Industrial Automation , 2010 .

[35]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[36]  Feng Xia,et al.  Wireless Sensor/Actuator Network Design for Mobile Control Applications , 2007, Sensors.

[37]  Alan Burns,et al.  Real Time Scheduling Theory: A Historical Perspective , 2004, Real-Time Systems.

[38]  Lothar Thiele,et al.  Efficient network flooding and time synchronization with Glossy , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.