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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 predefined 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.


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  • Kartic Subr, Cyril Soler, Fredo Durand. Edge-Preserving Multiscale Image Decomposition based on Local Extrema. ACM Transactions on Graphics, Association for Computing Machinery, 2009, 28 (5), pp.147:1--147:9. <10.1145/1618452.1618493>. <inria-00461396>

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  • Simon Duquennoy, Beshr Al Nahas, Olaf Landsiedel, Thomas Watteyne. Orchestra: Robust Mesh Networks Through Autonomously Scheduled TSCH. ACM Conference on Embedded Networked Sensor Systems (Sensys), Nov 2015, Seoul, South Korea. 2015. <hal-01208403>