A Realistic Energy Consumption Model for TSCH Networks

Vilajosana, Xavier; Wang, Qin; Chraim, Fabien; Watteyne, Thomas; Chang, Tengfei; Pister, Kristofer S. J.

doi:10.1109/jsen.2013.2285411

Cited by 137 publications

(124 citation statements)

References 16 publications

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“…However, there are several which evaluate snapshots of the stack, or subsets thereof (e.g. by layer), such as in the case of CoAP in [80], where the authors show that CoAP is eicient when implemented over RPL, 6LoWPAN and ContikiMAC (and reiterate that the key eiciencies are to be gained at the link layer), and 6TiSCH [81], where a realistic energy model presented for TSCH demonstrated that under certain conditions, sub-1% duty cycles are demonstrable for real and simulated networks under reasonable trafic loads.…”

Section: Functionalities Protocolsmentioning

confidence: 99%

Energy-Efficient Communication in Wireless Networks

Boyle¹,

Kolcun²,

Yeatman³

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

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This chapter describes the evolution of, and state of the art in, energy-eicient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Speciically, emphasis is placed on energy eiciency as critical to ensuring the feasibility of long lifetime, low-maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traic paterns is discussed, in addition to their combination and evaluation as full protocol stacks.

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Section: Functionalities Protocolsmentioning

confidence: 99%

Energy-Efficient Communication in Wireless Networks

Boyle¹,

Kolcun²,

Yeatman³

2017

ICT - Energy Concepts for Energy Efficiency and Sustainability

View full text Add to dashboard Cite

show abstract

“…The function F includes a lookup-table mapping between real frequency value (in GHz) and physical channel number in the range [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. ASN presents the total number of slots since the start of TSCH networks, and it is calculated as follows: ASN = (n Á L slotframe + slotOffset), where n defines the slotframe cycle and L slotframe is the slotframe length.…”

Section: Tsch Mode In Ieee 802154ementioning

confidence: 99%

“…15 Let Q be the energy consumption of EB advertisement in single multi-slotframe at a node. Q is given by…”

Section: Energy Consumption Model Of Eb Advertisementmentioning

confidence: 99%

“…To meet strict requirements of industrial applications, several wireless standards such as Wireless HART 2 15.4e introduces time-slotted channel hopping (TSCH) mode to facilitate multi-hop operations and address fading and interference issues in wireless environments. The core of TSCH is a medium access technique using time synchronization and channel hopping to achieve ultra-low power operation and high reliability.…”

Section: Introductionmentioning

confidence: 99%

“…15 Under a high interference environment, if these packets are lost, related nodes may suffer from de-synchronization. As a result, they are required to rejoin the network.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A rapid joining scheme based on fuzzy logic for highly dynamic IEEE 802.15.4e time-slotted channel hopping networks

Duy

Dinh

Kim

2016

International Journal of Distributed Sensor Networks

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The IEEE 802.15.4e standard is an amendment of the IEEE 802.15.4-2011 protocol by introducing time-slotted channel hopping access behavior mode. However, the IEEE 802.15.4e only defines time-slotted channel hopping link-layer mechanisms without an investigation of network formation and communication scheduling which are still open issues to the research community. This article investigates the network formation issue of the IEEE 802.15.4e time-slotted channel hopping networks. In time-slotted channel hopping networks, a joining node normally takes a long time period to join the network because the node has to wait until there is at least one enhanced beacon message advertised by synchronized nodes (synchronizers) in the network on its own synchronization channel. This leads to a long joining delay and high energy consumption during the network formation phase, especially so in highly dynamic networks in which nodes join or rejoin frequently. To enable a rapid time-slotted channel hopping network formation, this article proposes a new design for slotframe structure and a novel adaptive joining scheme based on fuzzy logic. Our proposed scheme enables a synchronizer to be able to adaptively determine an appropriate number of enhanced beacons it should advertise, based on the number of available synchronizers in the network, so that joining nodes can achieve a short joining time while energy consumption of enhanced beacon advertisement at the synchronizers is optimized. Through extensive mathematical analysis and experimental results, we show that the proposed scheme achieves a significant improvement in terms of joining delay compared to state-of-the-art studies.

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CCR: Cost‐aware cell relocation in 6TiSCH networks

Chang

Watteyne

Vilajosana

et al. 2017

Trans Emerging Tel Tech

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The Internet Engineering Task Force 6TiSCH Working Group standardizes the protocol stack for the Industrial Internet of Things, which combines the industrial performance of IEEE802.15.4 time-slotted channel hopping (TSCH) with the addressability and Internet integration capabilities of Internet Protocol version 6.The 6top Protocol, which is part of 6TiSCH, allows distributed management of the TSCH communication schedule. The Scheduling Function Zero (SF0) is the default algorithm for a node to decide when to add/remove cells to its neighbors. SF0 picks the cells to add randomly; hence, it is possible that 2 nearby pairs of nodes pick the same cell, resulting in a schedule collision. This article introduces cost-aware cell relocation (CCR), which is a solution to detect and fix such schedule collisions in a distributed manner. CCR monitors the performance of individual cells and uses that information to detect collisions. When such a collision is detected on a cell, neighbor nodes communicate to relocate that cell to a different slot/channel in the TSCH schedule. We implement CCR and run it on a 5-node network on the Internet of Things Laboratory testbed. The results show that, compared with today's SF0 and for the same traffic requirements, CCR increases the average packet delivery ratio by 2% and reduces the number of cells that need to be scheduled by 27.3%.

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A Realistic Energy Consumption Model for TSCH Networks

Cited by 137 publications

References 16 publications

Energy-Efficient Communication in Wireless Networks

Energy-Efficient Communication in Wireless Networks

A rapid joining scheme based on fuzzy logic for highly dynamic IEEE 802.15.4e time-slotted channel hopping networks

CCR: Cost‐aware cell relocation in 6TiSCH networks

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