Orchestra: Robust Mesh Networks Through Autonomously Scheduled TSCH

Time slotted operation is a well-proven approach to achieve highly reliable low-power networking through scheduling and channel hopping. It is, however, difficult to apply time slotting to dynamic networks as envisioned in the Internet of Things. Commonly, these applications do not have pre-defined periodic traffic patterns and nodes can be added or removed dynamically. This paper addresses the challenge of bringing TSCH (Time Slotted Channel Hopping MAC) to such dynamic networks. We focus on low-power IPv6 and RPL networks, and introduce Orchestra. In Orchestra, nodes autonomously compute their own, local schedules. They maintain multiple schedules, each allocated to a particular traffic plane (application, routing, MAC), and updated automatically as the topology evolves. Orchestra (re)computes local schedules without signaling overhead, and does not require any central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules. This scheme allows Orchestra to build non-deterministic networks while exploiting the robustness of TSCH. We demonstrate the practicality of Orchestra and quantify its benefits through extensive evaluation in two testbeds, on two hardware platforms. Orchestra reduces, or even eliminates, network contention. In long running experiments of up to 72~h we show that Orchestra achieves end-to-end delivery ratios of over 99.99%. Compared to RPL in asynchronous low-power listening networks, Orchestra improves reliability by two orders of magnitude, while achieving a similar latency-energy balance.

[1]  Alexandre M. Bayen,et al.  A decentralized scheduling algorithm for time synchronized channel hopping , 2011, EAI Endorsed Trans. Mob. Commun. Appl..

[2]  Gennaro Boggia,et al.  On Optimal Scheduling in Duty-Cycled Industrial IoT Applications Using IEEE802.15.4e TSCH , 2013, IEEE Sensors Journal.

[3]  James Brown,et al.  Constructing Schedules for Time-Critical Data Delivery in Wireless Sensor Networks , 2014, TOSN.

[4]  Thomas Watteyne,et al.  Technical Overview of SmartMesh IP , 2013, 2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing.

[5]  Mun Choon Chan,et al.  Splash : Fast Data Dissemination with Constructive Interference in Wireless Sensor Networks , 2013 .

[6]  R. Wattenhofer,et al.  Dozer: Ultra-Low Power Data Gathering in Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

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

[8]  Thomas Watteyne,et al.  Label switching over IEEE802.15.4e networks , 2013, Trans. Emerg. Telecommun. Technol..

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

[10]  Paul J. M. Havinga,et al.  D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation , 2013, Sensors.

[11]  Gennaro Boggia,et al.  Traffic Aware Scheduling Algorithm for reliable low-power multi-hop IEEE 802.15.4e networks , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[12]  Lei Tang,et al.  EM-MAC: a dynamic multichannel energy-efficient MAC protocol for wireless sensor networks , 2011, MobiHoc '11.

[13]  David E. Culler,et al.  IP is dead, long live IP for wireless sensor networks , 2008, SenSys '08.

[14]  Thiemo Voigt,et al.  Low-Power Listening Goes Multi-channel , 2014, 2014 IEEE International Conference on Distributed Computing in Sensor Systems.

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

[16]  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.

[17]  Euhanna Ghadimi,et al.  Low power, low delay: Opportunistic routing meets duty cycling , 2012, 2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN).

[18]  Thomas Watteyne,et al.  Industrial IEEE802.15.4e networks: Performance and trade-offs , 2015, 2015 IEEE International Conference on Communications (ICC).

[19]  Mun Choon Chan,et al.  Indriya: A Low-Cost, 3D Wireless Sensor Network Testbed , 2011, TRIDENTCOM.

[20]  Bo Li,et al.  Accounting for Failures in Delay Analysis for WirelessHART Networks , 2012 .

[21]  Marco Zuniga,et al.  Broadcast-free collection protocol , 2012, SenSys '12.

[22]  Anna N. Kim,et al.  When HART goes wireless: Understanding and implementing the WirelessHART standard , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[23]  Mun Choon Chan,et al.  P3: A Practical Packet Pipeline using synchronous transmissions for wireless sensor networks , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[24]  Adam Dunkels,et al.  The ContikiMAC Radio Duty Cycling Protocol , 2011 .

[25]  Y.-C. Jenq On the Stability of Slotted ALOHA Systems , 1980, IEEE Trans. Commun..

[26]  Olaf Landsiedel,et al.  Let the tree Bloom: scalable opportunistic routing with ORPL , 2013, SenSys '13.

[27]  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.

[28]  Marcus Chang,et al.  Forwarder Selection in Multi-transmitter Networks , 2013, 2013 IEEE International Conference on Distributed Computing in Sensor Systems.

[29]  Ankur Mehta,et al.  Reliability through frequency diversity: why channel hopping makes sense , 2009, PE-WASUN '09.

[30]  Federico Ferrari,et al.  Chaos: versatile and efficient all-to-all data sharing and in-network processing at scale , 2013, SenSys '13.

[31]  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.

[32]  Thomas Watteyne,et al.  Adaptive synchronization in multi-hop TSCH networks , 2015, Comput. Networks.

[33]  JeongGil Ko,et al.  Industry: beyond interoperability: pushing the performance of sensor network IP stacks , 2011, SenSys.

[34]  P. Levis,et al.  BoX-MACs : Exploiting Physical and Link Layer Boundaries in Low-Power Networking , 2007 .

[35]  Matthias Hollick,et al.  Making 'Glossy' Networks Sparkle: Exploiting Concurrent Transmissions for Energy Efficient, Reliable, Ultra-Low Latency Communication in Wireless Control Networks , 2014, EWSN.

[36]  Ankur Mehta,et al.  Mitigating Multipath Fading through Channel Hopping in Wireless Sensor Networks , 2010, 2010 IEEE International Conference on Communications.

[37]  Jonathan Simon,et al.  Channel-Specific Wireless Sensor Network Path Data , 2007, 2007 16th International Conference on Computer Communications and Networks.