Utilizing Synchronous Flooding for Reliable and Scalable SDN in Low-Power Wireless Networks

The adoption of Software Defined Networking (SDN) within traditional networks has provided operators the ability to manage diverse resources and easily reconfigure or re-purpose networks as requirements change. Recent research has extended this concept to IEEE 802.15.4 low-power wireless networks, which form a key component of the Internet of Things (IoT). It is, however, difficult to apply the high-overhead approach of SDN, which requires both regularly scheduled and reactive asynchronous communication, to the low-bandwidth, unreliable environment present in IEEE 802.15.4. Although recent research has attempted to address this issue through optimization, interoperability with the low-power IPv6 stack inevitably results in trade-offs and contention with other protocols. This paper introduces Atomic-SDN: a low-latency, reliable, and energyefficient cross-layer architecture for SDN control in low-power wireless networks. Atomic-SDN utilizes synchronous flooding, which has recently been shown as a highly capable solution for fast and reliable communication in low-power mesh networks. Additionally, Atomic-SDN introduces cross-layer architecture to satisfy the different traffic patterns required by SDN, through configuration and scheduling of multiple synchronous flooding protocols. Using this approach, controller communication is facilitated at theoretical lower bounds of latency. We demonstrate the practicality of Atomic-SDN through emulation, with extremely high reliability and minimal latency as the mesh scales; presenting end-to-end delivery ratios of over 99.99% for SDN traffic, and controller association within milliseconds as opposed to seconds. We evaluate the Atomic-SDN in comparison to other SDN architectural configurations for IEEE 802.15.4, showing how Atomic-SDN improves SDN performance by orders-of-magnitude across latency, reliability, and energy-efficiency metrics.

[1]  Hwee Pink Tan,et al.  Enhancing responsiveness and scalability for OpenFlow networks via control-message quenching , 2012, 2012 International Conference on ICT Convergence (ICTC).

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

[3]  Lothar Thiele,et al.  Competition: Robust Flooding using Back-to-Back Synchronous Transmissions with Channel-Hopping , 2017, EWSN.

[4]  Yong Xiang,et al.  Software-Defined Wireless Networking Opportunities and Challenges for Internet-of-Things: A Review , 2016, IEEE Internet of Things Journal.

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

[6]  Reza Nejabati,et al.  Evolving SDN for Low-Power IoT Networks , 2018, 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft).

[7]  Athanasios V. Vasilakos,et al.  Software-Defined Networking for Internet of Things: A Survey , 2017, IEEE Internet of Things Journal.

[8]  Pascal Thubert An Architecture for IPv6 over the TSCH mode of IEEE 802.15.4 , 2019 .

[9]  Tryfon Theodorou,et al.  CORAL-SDN: A software-defined networking solution for the Internet of Things , 2017, 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN).

[10]  Hwee Pink Tan,et al.  Sensor OpenFlow: Enabling Software-Defined Wireless Sensor Networks , 2012, IEEE Communications Letters.

[11]  Olaf Landsiedel,et al.  Competition: Towards Low-Power Wireless Networking that Survives Interference with Minimal Latency , 2017, EWSN.

[12]  Reza Nejabati,et al.  Isolating SDN control traffic with layer-2 slicing in 6TiSCH industrial IoT networks , 2018, 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN).

[13]  Thomas Watteyne,et al.  Constructive Interference in 802.15.4: A Tutorial , 2019, IEEE Communications Surveys & Tutorials.

[14]  Haoyu Song,et al.  Protocol-oblivious forwarding: unleash the power of SDN through a future-proof forwarding plane , 2013, HotSDN '13.

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

[16]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[17]  Amy L. Murphy,et al.  Data Prediction + Synchronous Transmissions = Ultra-low Power Wireless Sensor Networks , 2016, SenSys.

[18]  Jirka Klaue,et al.  Competition: RedFixHop with Channel Hopping , 2017, EWSN.

[19]  Amy L. Murphy,et al.  Competition: CRYSTAL Clear: Making Interference Transparent , 2018, EWSN.

[20]  Olaf Landsiedel,et al.  Network-wide Consensus Utilizing the Capture Effect in Low-power Wireless Networks , 2017, SenSys.

[21]  Fernando Moreno-Cruz,et al.  Competition: BigBangBus , 2018, EWSN.

[22]  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.

[23]  Nael B. Abu-Ghazaleh,et al.  Wireless Software Defined Networking: A Survey and Taxonomy , 2016, IEEE Communications Surveys & Tutorials.

[24]  Laura Galluccio,et al.  SDN-WISE: Design, prototyping and experimentation of a stateful SDN solution for WIreless SEnsor networks , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[25]  Giacomo Morabito,et al.  Software Defined Wireless Networks: Unbridling SDNs , 2012, 2012 European Workshop on Software Defined Networking.

[26]  Amy L. Murphy,et al.  Interference-Resilient Ultra-Low Power Aperiodic Data Collection , 2018, 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

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

[28]  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.