Industrial IEEE802.15.4e networks: Performance and trade-offs

Watteyne, Thomas; Weiss, Joy; Doherty, Lance; Simon, J.

doi:10.1109/icc.2015.7248388

Cited by 75 publications

(69 citation statements)

References 3 publications

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“…Watteyne et al explored the capabilities of TSCH. They present a hardware model [11] to estimate the delay, power consumption and throughput of a network. This model supports SmartMesh IP, a commercial solution for highly reliable and ultra low-power wireless sensing.…”

Section: Related Workmentioning

confidence: 99%

Worst-case bound analysis for the time-critical MAC behaviors of IEEE 802.15.4e

Kurunathan

Severino

Koubâa

et al. 2017

2017 IEEE 13th International Workshop on Factory Communication Systems (WFCS)

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With an advancement towards the paradigm ofInternet of Things (IoT), in which every device will be interconnected and communicating with each other, the field of wirelesssensor networks has helped to resolve an ever-growing demandin meeting deadlines and reducing power consumption. Amongseveral standards that provide support for IoT, the recentlypublished IEEE 802.15.4e protocol is specifically designed to meetthe QoS requirements of industrial applications. IEEE 802.15.4eprovides five Medium-Access Control (MAC) behaviors, includingthree that target time-critical applications: Deterministic andSynchronous Multichannel Extension (DSME); Time SlottedChannel Hopping (TSCH) and Low Latency Deterministic Network (LLDN). However, the standard and the literature do notprovide any worst-case bound analysis of these behaviors, thusit is not possible to effectively predict their timing performancein an application and accurately devise a network in accordanceto such constraints. This paper fills this gap by contributingnetwork models for the three time-critical MAC behaviors usingNetwork Calculus. These models allow deriving the worst-caseperformance of the MAC behaviors in terms of delay andbuffering requirements. We then complement these results bycarrying out a thorough performance analysis of these MACbehaviors by observing the impact of different parameters. Abstract-With an advancement towards the paradigm of Internet of Things (IoT), in which every device will be interconnected and communicating with each other, the field of wireless sensor networks has helped to resolve an ever-growing demand in meeting deadlines and reducing power consumption. Among several standards that provide support for IoT, the recently published IEEE 802.15.4e protocol is specifically designed to meet the QoS requirements of industrial applications. IEEE 802.15.4e provides five Medium-Access Control (MAC) behaviors, including three that target time-critical applications: Deterministic and Synchronous Multichannel Extension (DSME); Time Slotted Channel Hopping (TSCH) and Low Latency Deterministic Network (LLDN). However, the standard and the literature do not provide any worst-case bound analysis of these behaviors, thus it is not possible to effectively predict their timing performance in an application and accurately devise a network in accordance to such constraints. This paper fills this gap by contributing network models for the three time-critical MAC behaviors using Network Calculus. These models allow deriving the worst-case performance of the MAC behaviors in terms of delay and buffering requirements. We then complement these results by carrying out a thorough performance analysis of these MAC behaviors by observing the impact of different parameters. Worst-Case BoundAnalysis for the Time-

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Section: Related Workmentioning

confidence: 99%

Worst-case bound analysis for the time-critical MAC behaviors of IEEE 802.15.4e

Kurunathan

Severino

Koubâa

et al. 2017

2017 IEEE 13th International Workshop on Factory Communication Systems (WFCS)

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“…IoT deployments in the smart city [4], smart building [8] and industrial [12] application domains use a wide number of peripherals with varying network requirements [20]. These peripherals can either be a sensor to monitor the operational environment or an actuator to control devices.…”

Section: A Heterogenous Trafficmentioning

confidence: 99%

“…It is therefore crucial to minimize the number of radio retransmissions due to 1) radio collisions; 2) errors induced by the wireless channel. Over the years, field experience has proven that Time Division Multiple Access (TDMA) techniques enable efficient operation by avoiding collisions and minimising the time spent in idle listening mode [21]. Channel hopping techniques provide robustness against external interference and multi-path fading that are typical causes of wireless errors.…”

Section: B Time-slotted Channel Hopping (6tisch)mentioning

confidence: 99%

Building Dynamic and Dependable Component-Based Internet-of-Things Applications with Dawn

Ramachandran

Matthys

Daniels

et al. 2016

2016 19th International ACM SIGSOFT Symposium on Component-Based Software Engineering (CBSE)

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The Internet of Things (IoT) embeds sensors, actuators and computation into everyday 'things' such as lights and thermostats. These things form low-power wireless networks connecting to the Internet via IPv6 for monitoring and control. Such IoT systems are increasingly subject to runtime reconfiguration, wherein new hardware and software may be installed dynamically to accommodate changing application objectives. Supporting runtime reconfiguration, while maintaining reliability and low-power operation requires crosslayer optimisation of network resources. This paper introduces Dawn, a network optimisation approach for component-based systems that automatically extracts and enforces bandwidth requirements from component compositions. Dawn allows application developers to build extremely flexible and yet dependable IoT networks. We implemented a prototype of Dawn for a 50-node testbed composed of state-of-the-art embedded IoT devices. Our evaluation shows that Dawn preserves 100% end-to-end reliability in the face of network reconfiguration, while extending battery lifetime three-fold compared to a onesize-fits-all network configuration with minimal memory and performance overhead.

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“…This includes works on configuring and improving performance of TSCH itself such as [8,25,30,36,37], and also works that consider the layers on top of TSCH such as [12,13,18,23,24,34]. However, to meet the stringent requirements of industrial applications such as sub-second latency and reliable communications in in-vehicle networks, more work needs to be done [38]. IEEE 802.15.4 [5] defines 16 frequency channels in the license-free 2.4 GHz ISM band.…”

Section: Introductionmentioning

confidence: 99%

Dependable Interference-Aware Time-Slotted Channel Hopping for Wireless Sensor Networks

Tavakoli

Nabi

Basten

et al. 2018

ACM Trans. Sen. Netw.

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IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) aims to improve communication reliability in Wireless Sensor Networks (WSNs) by reducing the impact of the medium access contention, multipath fading, and blocking of wireless links. While TSCH outperforms single channel communications, cross-technology interference on the license-free ISM bands may affect the performance of TSCH-based WSNs. For applications such as in-vehicle networks for which interference is dynamic over time, it leads to non-guaranteed reliability of the communications over time. This paper proposes an Enhanced version of the TSCH protocol together with a Distributed Channel Sensing technique (ETSCH+DCS) which dynamically detects good quality channels to be used for communication. The quality of channels is extracted using a combination of a central and a distributed channel-quality estimation technique. The central technique uses Non-Intrusive Channel-quality Estimation (NICE) technique which proactively performs energy detections in the idle part of each timeslot at the coordinator of the network. NICE enables ETSCH to follow dynamic interference, while it does not reduce throughput of the network. The distributed channel quality estimation technique is executed by all the nodes in the network, based on their communication history, to detect interference sources that are hidden from the coordinator. We did two sets of lab experiments with controlled interferers and a number of simulations using real-world interference data sets to evaluate ETSCH. Experimental and simulation results show that ETSCH improves reliability of network communications, compared to basic TSCH and the state of the art solution (ATSCH). In some experimental scenarios NICE itself has been able to increase the average packet reception ratio by 22% and shorten the length of burst packet losses by half, compared to the plain TSCH protocol. Further experiments show that DCS can reduce the effect of hidden interference (which is not detectable by NICE) on the packet reception ratio of the affected links by 50%.

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Industrial IEEE802.15.4e networks: Performance and trade-offs

Cited by 75 publications

References 3 publications

Worst-case bound analysis for the time-critical MAC behaviors of IEEE 802.15.4e

Worst-case bound analysis for the time-critical MAC behaviors of IEEE 802.15.4e

Building Dynamic and Dependable Component-Based Internet-of-Things Applications with Dawn

Dependable Interference-Aware Time-Slotted Channel Hopping for Wireless Sensor Networks

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